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Purpose Accurate prognostic markers are urgently needed to identify diffuse large B-Cell lymphoma (DLBCL) patients at high risk of progression or relapse. Our purpose was to investigate the potential added value of baseline radiomics features to the international prognostic index (IPI) in predicting outcome after first-line treatment. Methods Three hundred seventeen newly diagnosed DLBCL patients were included. Lesions were delineated using a semi-automated segmentation method (standardized uptake value ≥ 4.0), and 490 radiomics features were extracted. We used logistic regression with backward feature selection to predict 2-year time to progression (TTP). The area under the curve (AUC) of the receiver operator characteristic curve was calculated to assess model performance. High-risk groups were defined based on prevalence of events; diagnostic performance was assessed using positive and negative predictive values. Results The IPI model yielded an AUC of 0.68. The optimal radiomics model comprised the natural logarithms of metabolic tumor volume (MTV) and of SUVpeak and the maximal distance between the largest lesion and any other lesion (Dmaxbulk, AUC 0.76). Combining radiomics and clinical features showed that a combination of tumor- (MTV, SUVpeak and Dmaxbulk) and patient-related parameters (WHO performance status and age > 60 years) performed best (AUC 0.79). Adding radiomics features to clinical predictors increased PPV with 15%, with more accurate selection of high-risk patients compared to the IPI model (progression at 2-year TTP, 44% vs 28%, respectively). Conclusion Prediction models using baseline radiomics combined with currently used clinical predictors identify patients at risk of relapse at baseline and significantly improved model performance. Trial registration number and date EudraCT: 2006–005,174-42, 01–08-2008.

Background Machine learning studies require a large number of images often obtained on different PET scanners. When merging these images, the use of harmonized images following EARL-standards is essential. However, when including retrospective images, EARL accreditation might not have been in place. The aim of this study was to develop a convolutional neural network (CNN) that can identify retrospectively if an image is EARL compliant and if it is meeting older or newer EARL-standards. Materials and methods 96 PET images acquired on three PET/CT systems were included in the study. All images were reconstructed with the locally clinically preferred, EARL1, and EARL2 compliant reconstruction protocols. After image pre-processing, one CNN was trained to separate clinical and EARL compliant reconstructions. A second CNN was optimized to identify EARL1 and EARL2 compliant images. The accuracy of both CNNs was assessed using fivefold cross-validation. The CNNs were validated on 24 images acquired on a PET scanner not included in the training data. To assess the impact of image noise on the CNN decision, the 24 images were reconstructed with different scan durations. Results In the cross-validation, the first CNN classified all images correctly. When identifying EARL1 and EARL2 compliant images, the second CNN identified 100% EARL1 compliant and 85% EARL2 compliant images correctly. The accuracy in the independent dataset was comparable to the cross-validation accuracy. The scan duration had almost no impact on the results. Conclusion The two CNNs trained in this study can be used to retrospectively include images in a multi-center setting by, e.g., adding additional smoothing. This method is especially important for machine learning studies where the harmonization of images from different PET systems is essential.

Interim 18F-fluorodeoxyglucose positron emission tomography (Interim- 18F-FDG-PET,hereafter I-PET) has the potential to guide treatment of patients with diffuse large B-celllymphoma (DLBCL) if the prognostic value is known. The aim of this study was to determinethe optimal timing and response criteria for evaluating prognosis with I-PET in DLBCL.Individual patient data from 1692 patients with de novo DLBCL were combined and scans were harmonized. I-PET was performed at various time points during treatment with rituximab plus cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP) therapy. Scans were interpreted using the Deauville score (DS) and change in maximum standardized uptake value (DSUVmax ). Multilevel Cox proportional hazards models corrected for International Prognostic Index (IPI) score were used to study the effects oftiming and response criteria on 2-year progression-free survival (PFS). I-PET after 2 cycles (I-PET2) and I-PET4 significantly discriminated good responders from poor responders, with the highest hazard ratios (HRs) for I-PET4. Multivariable HRs for a PET-positive result at I-PET2 and I-PET4 were 1.71 and 2.95 using DS4-5, 4.91 and 6.20 using DS5, and 2.93 and 4.65 using DSUVmax , respectively. DSUVmax identified a larger proportion of poor respondersthan DS5 did. For all criteria, the negative predictive value was >80%, and positivepredictive values ranged from 30% to 70% at I-PET2 and I-PET4. Unlike I-PET1, I-PET3discriminated good responders from poor responders using DS4-5 and DS5 thresholds (HRs,2.94 and 4.67, respectively). I-PET2 and I-PET4 predict good response equally during R-CHOPtherapy in DLBCL. Optimal timing and response criteria depend on the clinical context. Goodresponse at I-PET2 is suggested for de-escalation trials, and poor response using DSUVmax atI-PET4 is suggested for randomized trials that are evaluating new therapies

Background: Better biomarkers are needed to predict treatment outcome in NSCLC patients treated with anti PD-(L)1 checkpoint inhibitors. PD-L1 immunohistochemistry has limited predictive value, possibly due to tumor heterogeneity of PD-L1 expression. Noninvasive PD-L1 imaging using 89Zr-durvalumab might provide a better reflection of tumor PD-L1 expression and can therefore support treatment decision making. Patients and Methods: NSCLC patients eligible for second line immunotherapy treatment were enrolled. Patients received two injections of 89Zr-durvalumab; one without a preceding dose of unlabeled durvalumab (‘tracer dose only’) and one with a preceding dose of 750 mg durvalumab, directly prior to tracer injection. Up to four PET/CT scans were obtained after tracer injection. Post-imaging acquisition, patients were treated with 750mg durvalumab every two weeks. Tracer biodistribution and tumor uptake were visually assessed and quantified as standardized uptake value (SUV) and both imaging acquisitions were compared. Tumor tracer uptake was correlated with PD-L1 expression and clinical outcome, defined as treatment response to durvalumab treatment. Results: Thirteen patients were included and ten completed all scheduled PET scans. No tracer related adverse events were observed and all patients started durvalumab treatment. Biodistribution analysis showed 89Zr-durvalumab accumulation in the blood pool, liver and spleen. Serial imaging showed that image acquisition 120 hours post injection delivered the best tumor to blood pool ratio. Most tumor lesions were visualized with the tracer-dose only versus the co-injection imaging acquisition (25% vs 13.5% of all lesions). Uptake heterogeneity was observed within (range SUVpeak 0.2 to 15.1) and between patients. Tumor uptake was higher in patients with treatment response or stable disease, compared to patients with disease progression according to RECIST 1.1. However, this difference was not statistically significant (median SUVpeak 4.9 vs 2.4, P = 0.06). SUVpeak correlated better with the combined tumor and immune cell PD-L1 score than with PD-L1 expression on tumor cells, although both were not statistically significant (P = 0.06 and P = 0.93, respectively). Conclusion:89Zr-durvalumab was safe without any tracer related adverse events and more tumor lesions were visualized using the tracer dose only imaging acquisition. 89Zr-durvalumab tumor uptake was higher in patients with response to durvalumab treatment, but did not correlate with tumor PD-L1 IHC.

Metabolic tumor volume (MTV) is a promising biomarker of pretreatment risk in diffuse large B-cell lymphoma (DLBCL). Different segmentation methods can be used that predict prognosis equally well but give different optimal cutoffs for risk stratification. Segmentation can be cumbersome; a fast, easy, and robust method is needed. Our aims were to evaluate the best automated MTV workflow in DLBCL; determine whether uptake time, compliance or noncompliance with standardized recommendations for (18)F-FDG scanning, and subsequent disease progression influence the success of segmentation; and assess differences in MTVs and discriminatory power of segmentation methods. Methods: One hundred forty baseline (18)F-FDG PET/CT scans were selected from U.K. and Dutch studies on DLBCL to provide a balance between scans at 60 and 90 min of uptake, parameters compliant and noncompliant with standardized recommendations for scanning, and patients with and without progression. An automated tool was applied for segmentation using an SUV of 2.5 (SUV2.5), an SUV of 4.0 (SUV4.0), adaptive thresholding (A50P), 41% of SUV(max) (41%), a majority vote including voxels detected by at least 2 methods (MV2), and a majority vote including voxels detected by at least 3 methods (MV3). Two independent observers rated the success of the tool to delineate MTV. Scans that required minimal interaction were rated as a success; scans that missed more than 50% of the tumor or required more than 2 editing steps were rated as a failure. Results: One hundred thirty-eight scans were evaluable, with significant differences in success and failure ratings among methods. The best performing was SUV4.0, with higher success and lower failure rates than any other method except MV2, which also performed well. SUV4.0 gave a good approximation of MTV in 105 (76%) scans, with simple editing for a satisfactory result in additionally 20% of cases. MTV was significantly different for all methods between patients with and without progression. The 41% segmentation method performed slightly worse, with longer uptake times; otherwise, scanning conditions and patient outcome did not influence the tool’s performance. The discriminative power was similar among methods, but MTVs were significantly greater using SUV4.0 and MV2 than using other thresholds, except for SUV2.5. Conclusion: SUV4.0 and MV2 are recommended for further evaluation. Automated estimation of MTV is feasible.

> History is the unfolding of miscalculation. > > —Barbara W. Tuchman, American historian In celebrating 60 years of JNM, it is hard to conceive of molecular imaging without 18F-FDG PET, particularly in oncology. Recognizing the importance of metabolic reprogramming in malignant transformation

This is the first comprehensive review on methods and materials for use in optical sensing of pH values and on applications of such sensors. The Review starts with an introduction that contains subsections on the definition of the pH value, a brief look back on optical methods for sensing of pH, on the effects of ionic strength on pH values and pKa values, on the selectivity, sensitivity, precision, dynamic ranges, and temperature dependence of such sensors. Commonly used optical sensing schemes are covered in a next main chapter, with subsections on methods based on absorptiometry, reflectometry, luminescence, refractive index, surface plasmon resonance, photonic crystals, turbidity, mechanical displacement, interferometry, and solvatochromism. This is followed by sections on absorptiometric and luminescent molecular probes for use pH in sensors. Further large sections cover polymeric hosts and supports, and methods for immobilization of indicator dyes. Further and more specific sections summarize the state of the art in materials with dual functionality (indicator and host), nanomaterials, sensors based on upconversion and 2-photon absorption, multiparameter sensors, imaging, and sensors for extreme pH values. A chapter on the many sensing formats has subsections on planar, fiber optic, evanescent wave, refractive index, surface plasmon resonance and holography based sensor designs, and on distributed sensing. Another section summarizes selected applications in areas, such as medicine, biology, oceanography, bioprocess monitoring, corrosion studies, on the use of pH sensors as transducers in biosensors and chemical sensors, and their integration into flow-injection analyzers, microfluidic devices, and lab-on-a-chip systems. An extra section is devoted to current challenges, with subsections on challenges of general nature and those of specific nature. A concluding section gives an outlook on potential future trends and perspectives.

Purpose In primary prostate cancer (PCa) patients, accurate staging and histologic grading are crucial to guide treatment decisions. 18F-DCFPyL (PSMA)-PET/CT has been successfully introduced for (re)staging PCa, showing high accuracy to localise PCa in lymph nodes and/or osseous structures. The diagnostic performance of 18F-DCFPyL-PET/CT in localizing primary PCa within the prostate gland was assessed, allowing for PSMA-guided targeted-prostate biopsy. Methods Thirty patients with intermediate-/high-risk primary PCa were prospectively enrolled between May 2018 and May 2019 and underwent 18F-DCFPyL-PET/CT prior to robot-assisted radical prostatectomy (RARP). Two experienced and blinded nuclear medicine physicians assessed tumour localisation within the prostate gland on PET/CT, using a 12-segment mapping model of the prostate. The same model was used by a uro-pathologist for the RARP specimens. Based on PET/CT imaging, a potential biopsy recommendation was given per patient, based on the size and PET-intensity of the suspected PCa localisations. The biopsy recommendation was correlated to final histopathology in the RARP specimen. Sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for clinically significant PCa (csPCa, Gleason score ≥ 3 + 4 = 7) were assessed. Results The segments recommended for potential targeted biopsy harboured csPCA in 28/30 patients (93%), and covered the highest Gleason score PCa segment in 26/30 patient (87%). Overall, 122 of 420 segments (29.0%) contained csPCa at final histopathological examination. Sensitivity, specificity, PPV and NPV for csPCa per segment using 18F-DCFPyL-PET/CT were 61.4%, 88.3%, 68.1% and 84.8%, respectively. Conclusions When comparing the PCa-localisation on 18F-DCFPyL-PET/CT with the RARP specimens, an accurate per-patient detection (93%) and localisation of csPCa was found. Thus, 18F-DCFPyL-PET/CT potentially allows for accurate PSMA-targeted biopsy.

PURPOSE Immunochemotherapy with rituximab plus cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP) has become standard of care for patients with diffuse large B-cell lymphoma (DLBCL). This randomized trial assessed whether rituximab intensification during the first 4 cycles of R-CHOP could improve the outcome of these patients compared with standard R-CHOP. PATIENTS AND METHODS A total of 574 patients with DLBCL age 18 to 80 years were randomly assigned to induction therapy with 6 or 8 cycles of R-CHOP-14 with (RR-CHOP-14) or without (R-CHOP-14) intensification of rituximab in the first 4 cycles. The primary end point was complete remission (CR) on induction. Analyses were performed by intention to treat. RESULTS CR was achieved in 254 (89%) of 286 patients in the R-CHOP-14 arm and 249 (86%) of 288 patients in the RR-CHOP-14 arm (hazard ratio [HR], 0.82; 95% CI, 0.50 to 1.36; P = .44). After a median follow-up of 92 months (range, 1-131 months), 3-year failure-free survival was 74% (95% CI, 68% to 78%) in the R-CHOP-14 arm versus 69% (95% CI, 63% to 74%) in the RR-CHOP-14 arm (HR, 1.26; 95% CI, 0.98 to 1.61; P = .07). Progression-free survival at 3 years was 74% (95% CI, 69% to 79%) in the R-CHOP-14 arm versus 71% (95% CI, 66% to 76%) in the RR-CHOP-14 arm (HR, 1.20; 95% CI, 0.94 to 1.55; P = .15). Overall survival at 3 years was 81% (95% CI, 76% to 85%) in the R-CHOP-14 arm versus 76% (95% CI, 70% to 80%) in the RR-CHOP-14 arm (HR, 1.27; 95% CI, 0.97 to 1.67; P = .09). Patients between ages 66 and 80 years experienced significantly more toxicity during the first 4 cycles in the RR-CHOP-14 arm, especially neutropenia and infections. CONCLUSION Early rituximab intensification during R-CHOP-14 does not improve outcome in patients with untreated DLBCL.

Radiomics features may predict outcome in diffuse large B-cell lymphoma (DLBCL). Currently, multiple segmentation methods are used to calculate metabolic tumor volume (MTV). We assessed the influence of segmentation method on the discriminative power of radiomics features in DLBCL at the patient level and for the largest lesion. Methods: Fifty baseline (18)F-FDG PET/CT scans of DLBCL patients with progression or relapse within 2 years after diagnosis were matched on uptake time and reconstruction method with 50 baseline PET/CT scans of DLBCL patients without progression. Scans were analyzed using 6 semiautomatic segmentation methods (SUV threshold of 4.0 [SUV4.0], SUV threshold of 2.5, 41% of SUV(max), 50% of SUV(peak), a majority vote segmenting voxels detected by ≥2 methods, and a majority vote segmenting voxels detected by ≥3 methods). On the basis of these segmentations, 490 radiomics features were extracted at the patient level, and 486 features were extracted for the largest lesion. To quantify the agreement between features extracted from different segmentation methods, the intraclass correlation (ICC) agreement was calculated for each method compared with SUV4.0. The feature space was reduced by deleting features that had high Pearson correlations (≥0.7) with the previously established predictors MTV or SUV(peak). Model performance was assessed using stratified repeated cross validation with 5 folds and 2,000 repeats, yielding the mean receiver-operating-characteristics curve integral for all segmentation methods using logistic regression with backward feature selection. Results: The percentage of features yielding an ICC of at least 0.75, compared with the SUV4.0 segmentation, was lowest for 50% of SUV(peak) both at the patient level and for the largest lesion, with 77.3% and 66.7% of the features yielding an ICC of at least 0.75, respectively. Features did not correlate strongly with MTV, with at least 435 features at the patient level and 409 features for the largest lesion for all segmentation methods having a correlation coefficient of less than 0.7. Features correlated strongly with SUV(peak) (at least 190 at patient level and 134 for the largest lesion were uncorrelated to SUV(peak), respectively). Receiver-operating-characteristics curve integrals ranged between 0.69 ± 0.11 and 0.84 ± 0.09 at the patient level and between 0.69 ± 0.11 and 0.73 ± 0.10 at the lesion level. Conclusion: Even though there are differences in the actual radiomics feature values derived and selected features among segmentation methods, there is no substantial difference in the discriminative power of radiomics features among segmentation methods.

The tumor programmed death ligand 1 (PD-L1) proportion score is the current method for selecting non-small cell lung cancer (NSCLC) patients for single-agent treatment with pembrolizumab, a programmed cell death 1 (PD-1) monoclonal antibody. However, not all patients respond to therapy. Better understanding of in vivo drug behavior may help in the selection of patients who will benefit the most. Methods: NSCLC patients eligible for pembrolizumab mono-therapy as first- or later-line therapy were enrolled. Patients received 2 injections of 89Zr-pembrolizumab, 1 without a preceding dose of pembrolizumab and 1 with a preceding dose of 200 mg of pembrolizumab, directly before tracer injection. Up to 4 PET/CT scans were obtained after tracer injection. After imaging acquisition, patients were treated with 200 mg of pembrolizumab every 3 wk. Tumor uptake and tracer biodistribution were visually assessed and quantified as the SUV. Tumor tracer uptake was correlated with PD-1 and PD-L1 expression and response to pembrolizumab treatment. Results: Twelve NSCLC patients were included. One patient experienced grade 3 myalgia after tracer injection. 89Zr-pembrolizumab was observed in the blood pool, liver, and spleen. Tracer uptake was visualized in 47.2% of 72 tumor lesions measuring BXP20 mm in the long-axis diameter, and substantial uptake heterogeneity was observed within and between patients. Uptake was higher in patients with a response to pembrolizumab treatment (n 5 3) than in patients without a response (n 5 9), although this finding was not statistically significant (median SUVpeak, 11.4 vs. 5.7; P 5 0.066). No significant correlations were found with PD-L1 or PD-1 immunohistochemistry. Conclusion: 89Zr-pembrolizumab injection was safe, with only 1 grade 3 adverse event-possibly immune-related-in 12 patients. 89Zr-pembrolizumab tumor uptake was higher in patients with a response to pembrolizumab treatment but did not correlate with PD-L1 or PD-1 immunohistochemistry.

Purpose MYC gene rearrangements in diffuse large B-cell lymphoma (DLBCL) patients are associated with poor prognosis. Our aim was to compare patterns of 2[18F]fluoro-2-deoxy-D-glucose positron emission tomography computed tomography (PET/CT) response in MYC + and MYC- DLBCL patients. Methods Interim PET/CT (I-PET) and end of treatment PET/CT (EoT-PET) scans of 81 MYC + and 129 MYC- DLBCL patients from 2 HOVON trials were reviewed using the Deauville 5-point scale (DS). DS1-3 was regarded as negative and DS4-5 as positive. Standardized uptake values (SUV) and metabolic tumor volume (MTV) were quantified at baseline, I-PET, and EoT-PET. Negative (NPV) and positive predictive values (PPV) were calculated using 2-year overall survival. Results MYC + DLBCL patients had significantly more positive EoT-PET scans than MYC- patients (32.5 vs 15.7%, p = 0.004). I-PET positivity rates were comparable (28.8 vs 23.8%). In MYC + patients 23.2% of the I-PET negative patients converted to positive at EoT-PET, vs only 2% for the MYC- patients (p = 0.002). Nine (34.6%) MYC + DLBCL showed initially uninvolved localizations at EoT-PET, compared to one (5.3%) MYC- patient. A total of 80.8% of EoT-PET positive MYC + patients showed both increased lesional SUV and MTV compared to I-PET. In MYC- patients, 31.6% showed increased SUV and 42.1% showed increased MTV. NPV of I-PET and EoT-PET was high for both MYC subgroups (81.8–94.1%). PPV was highest at EoT-PET for MYC + patients (61.5%). Conclusion MYC + DLBCL patients demonstrate aberrant PET response patterns compared to MYC- patients with more frequent progression during treatment after I-PET negative assessment and new lesions at sites that were not initially involved. Trial registration number and date of registration HOVON-84: EudraCT: 2006–005,174-42, retrospectively registered 01–08-2008. HOVON-130: EudraCT: 2014–002,654-39, registered 26–01-2015

We aimed to determine the added value of baseline metabolic tumor volume (MTV) and interim PET (I-PET) to the age-adjusted international prognostic index (aaIPI) to predict 2-y progression-free survival (PFS) in diffuse large B-cell lymphoma. Secondary objectives were to investigate optimal I-PET response criteria (using Deauville score [DS] or quantitative change in SUV(max) [ΔSUV(max)] between baseline and I-PET4 [observational I-PET scans after 4 cycles of rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone administered in 2-wk intervals with intensified rituximab in the first 4 cycles [R(R)-CHOP14]). Methods: I-PET4 scans in the HOVON-84 (Hemato-Oncologie voor Volwassenen Nederland [Haemato Oncology Foundation for Adults in the Netherlands]) randomized clinical trial (EudraCT 2006-005174-42) were centrally reviewed using DS (cutoff, 4–5). Additionally, ΔSUV(max) (prespecified cutoff, 70%) and baseline MTV were measured. Multivariable hazard ratio (HR), positive predictive value (PPV), and negative predictive value (NPV) were obtained for 2-y PFS. Results: In total, 513 I-PET4 scans were reviewed according to DS, and ΔSUV(max) and baseline MTV were available for 367 and 296 patients. The NPV of I-PET ranged between 82% and 86% for all PET response criteria. Univariate HR and PPV were better for ΔSUV(max) (4.8% and 53%, respectively) than for DS (3.1% and 38%, respectively). aaIPI and ΔSUV(max) independently predicted 2-y PFS (HR, 3.2 and 5.0, respectively); adding MTV brought about a slight improvement. Low or low-intermediate aaIPI combined with a ΔSUV(max) of more than 70% (37% of patients) yielded an NPV of 93%, and the combination of high-intermediate or high aaIPI and a ΔSUV(max) of 70% or less yielded a PPV of 65%. Conclusion: In this study on diffuse large B-cell lymphoma, I-PET after 4 cycles of R(R)-CHOP14 added predictive value to aaIPI for 2-y PFS, and both were independent response biomarkers in a multivariable Cox model. We externally validated that ΔSUV(max) outperformed DS in 2-y PFS prediction.

Purpose Quantitative prostate-specific membrane antigen (PSMA) PET analysis may provide for non-invasive and objective risk stratification of primary prostate cancer (PCa) patients. We determined the ability of machine learning-based analysis of quantitative [18F]DCFPyL PET metrics to predict metastatic disease or high-risk pathological tumor features. Methods In a prospective cohort study, 76 patients with intermediate- to high-risk PCa scheduled for robot-assisted radical prostatectomy with extended pelvic lymph node dissection underwent pre-operative [18F]DCFPyL PET-CT. Primary tumors were delineated using 50–70% peak isocontour thresholds on images with and without partial-volume correction (PVC). Four hundred and eighty standardized radiomic features were extracted per tumor. Random forest models were trained to predict lymph node involvement (LNI), presence of any metastasis, Gleason score ≥ 8, and presence of extracapsular extension (ECE). For comparison, models were also trained using standard PET features (SUVs, volume, total PSMA uptake). Model performance was validated using 50 times repeated 5-fold cross-validation yielding the mean receiver-operator characteristic curve AUC. Results The radiomics-based machine learning models predicted LNI (AUC 0.86 ± 0.15, p p p p Conclusion Machine learning-based analysis of quantitative [18F]DCFPyL PET metrics can predict LNI and high-risk pathological tumor features in primary PCa patients. These findings indicate that PSMA expression detected on PET is related to both primary tumor histopathology and metastatic tendency. Multicenter external validation is needed to determine the benefits of using radiomics versus standard PET metrics in clinical practice.

In oncology, Positron Emission Tomography (PET) is frequently performed for cancer staging and treatment monitoring. Metabolic active tumor volume (MATV) as well as total MATV (TMATV - including primary tumor, lymph nodes and metastasis) derived from PET images have been identified as prognostic factor or for evaluating treatment efficacy in cancer patients. To this end a segmentation approach with high precision and repeatability is important. Moreover, to derive TMATV, a reliable segmentation of the primary tumor as well as all metastasis is essential. However, the implementation of a repeatable and accurate segmentation algorithm remains a challenge. In this work, we propose an artificial intelligence based segmentation method based on textural features (TF) extracted from the PET image. From a large number of textural features, the most important features for the segmentation task were selected. The selected features are used for training a random forest classifier to identify voxels as tumor or background. The algorithm is trained, validated and tested using a lung cancer PET/CT dataset and, additionally, applied on a fully independent test-retest dataset. The approach is especially designed for accurate and repeatable segmentation of primary tumors and metastasis in order to derive TMATV. The segmentation results are compared with conventional segmentation approaches in terms of accuracy and repeatability. In summary, the TF segmentation proposed in this study provided better repeatability and accuracy than conventional segmentation approaches. Moreover, segmentations were accurate for both primary tumors and metastasis and the proposed algorithm is therefore a good candidate for PET tumor segmentation.

Radiolabeled prostate-specific membrane antigen (PSMA) PET has demonstrated promising results for prostate cancer (PCa) imaging. Quantification of PSMA radiotracer uptake is desired as it enables reliable interpretation of PET images, use of PSMA uptake as an imaging biomarker for tumor characterization, and evaluation of treatment effects. The aim of this study was to perform a full pharmacokinetic analysis of 2-(3-(1-carboxy-5-[(6- 18F-fluoro-pyridine-3-carbonyl)-amino]-pentyl)-ureido)-pentanedioic acid ( 18F-DCFPyL), a second-generation 18F-labeled PSMA ligand. On the basis of the pharmacokinetic analysis (reference method), simplified methods for quantification of 18F-DCFPyL uptake were validated. Methods: Eight patients with metastasized PCa were included. Dynamic PET acquisitions were performed at 0-60 and 90-120 min after injection of a median dose of 313 MBq of 18F-DCFPyL (range, 292-314 MBq). Continuous and manual arterial blood sampling provided calibrated plasma tracer input functions. Time-activity curves were derived for each PCa metastasis, and 18F-DCFPyL kinetics were described using standard plasma input tissue-compartment models. Simplified methods for quantification of 18F-DCFPyL uptake (SUVs; tumor-to-blood ratios [TBRs]) were correlated with kinetic parameter estimates obtained from full pharmacokinetic analysis. Results: In total, 46 metastases were evaluated. A reversible 2-tissue-compartment model was preferred for 18F-DCFPyL kinetics in 59% of the metastases. The observed k 4 was small, however, resulting in nearly irreversible kinetics during the course of the PET study. Hence, k 4 was fixated (0.015) and net influx rate, K i, was preferred as the reference kinetic parameter. Whole-blood TBR provided an excellent correlation with K i from full kinetic analysis (R 2 = 0.97). This TBR could be simplified further by replacing the blood samples with an image-based, single measurement of blood activity in the ascending aorta (image-based TBR, R 2 = 0.96). SUV correlated poorly with K i (R 2 = 0.47 and R 2 = 0.60 for SUV normalized to body weight and lean body mass, respectively), most likely because of deviant blood activity concentrations (i.e., tumor tracer input) in patients with higher tumor volumes. Conclusion: 18F-DCFPyL kinetics in PCa metastases are best described by a reversible 2-tissue-compartment model. Image-based TBRs were validated as a simplified method to quantify 18F-DCFPyL uptake and might be applied to clinical, whole-body PET scans. SUV does not provide reliable quantification of 18F-DCFPyL uptake.

BACKGROUND There are only limited data available on changes in the etiology, management, and clinical outcomes in patients with lower gastrointestinal bleeding over the past decade. STUDY We compared 2 groups of consecutive patients hospitalized with lower gastrointestinal bleeding during 2 time periods: 2005 to 2007 (301 patients) and 2015 to 2017 (249 patients). RESULTS Compared with the 2005 to 2007 group, the mean Charlson comorbidity index in the 2015 to 2017 group was higher (5.0±2.6 vs. 6.0±3.0, P=0.028), whereas the use of computerized tomographic angiography and small bowel capsule endoscopy was more common (12.9% vs. 58.1%, P

Objectives The reversibility of interstitial lung disease (ILD) in SSc is difficult to assess by current diagnostic modalities and there is clinical need for imaging techniques that allow for treatment stratification and monitoring. 18F-Fluorodeoxyglucose (FDG) PET/CT scanning may be of interest for this purpose by detection of metabolic activity in lung tissue. This study aimed to investigate the potential role of 18F-FDG PET/CT scanning for the quantitative assessment of SSc-related active ILD. Methods 18F-FDG PET/CT scans and high resolution CT scans of eight SSc patients, including five with ILD, were analysed. For comparison, reference groups were included: eight SLE patients and four primary Sjögren’s syndrome (pSS) patients, all without ILD. A total of 22 regions of interest were drawn in each patient at apical, medial and dorsobasal lung levels. 18F-FDG uptake was measured as mean standardized uptake value (SUVmean) in each region of interest. Subsequently, basal/apical (B/A) and medial/apical (M/A) ratios were calculated at patient level (B/A-p and M/A-p) and at tissue level (B/A-t and M/A-t). Results SUVmean values in dorsobasal ROIs and B/A-p ratios were increased in SSc with ILD compared with SSc without ILD (P = 0.04 and P = 0.07, respectively), SLE (P = 0.003 and P = 0.002, respectively) and pSS (P = 0.03 and P = 0.02, respectively). Increased uptake in the dorsobasal lungs and increased B/A-t ratios corresponded to both ground glass and reticulation on high resolution CT. Conclusion Semi-quantitative assessment of 18F-FDG PET/CT is able to distinguish ILD from non-affected lung tissue in SSc, suggesting that it may be used as a new biomarker for SSc-ILD disease activity.

Background 89Zirconium-immuno-positron emission tomography (89Zr-immuno-PET) is used for assessment of target status to guide antibody-based therapy. We aim to determine the relation between antibody tumor uptake and target concentration to improve future study design and interpretation. Methods The relation between tumor uptake and target concentration was predicted by mathematical modeling of 89Zr-labeled antibody disposition in the tumor. Literature values for trastuzumab kinetics were used to provide an example. Results 89Zr-trastuzumab uptake initially increases with increasing target concentration, until it levels off to a constant value. This is determined by the total administered mass dose of trastuzumab. For a commonly used imaging dose of 50 mg 89Zr-trastuzumab, uptake can discriminate between immunohistochemistry score (IHC) 0 versus 1–2–3. Conclusion The example for 89Zr-trastuzumab illustrates the potential to assess target expression. The pitfall of false-positive findings depends on the cut-off to define clinical target positivity (i.e., IHC 3) and the administered mass dose.

BackgroundAccurate staging of early breast cancer (BC) patients is essential for tailored treatment. Currently, the preferred imaging modality for staging is positron emission tomography with [18F]Fluorodeoxyglucose (FDG PET) combined with a diagnostic computed tomography (CT) scan of the thorax/abdomen. However, FDG PET might be insufficient for detection of malignant lesions in grade 1–2, estrogen receptor positive (ER+) BC, due to its low metabolic activity. The main aim of this study was to retrospectively investigate the diagnostic accuracy of FDG PET in this patient population.Methods74 patients diagnosed with grade 1–2, ER + clinical stage IIB/III or locoregional recurrent BC were included. Suspect tumor lesions detected on conventional imaging (mammography, ultrasound, magnetic resonance imaging, diagnostic CT, bone scintigraphy) and FDG PET were confirmed with pathology or follow-up. FDG PET-positive lesions were (semi)quantified with standardized uptake values (SUV) and total lesion glycolysis (TLG), and these FDG PET parameters were correlated with pathological features such as histological subtype, grade, ER, PR and HER2 expression and mitotic activity index.ResultsPre-operative imaging identified 155 lesions that were pathologically verified. Based on pathology, 115/155 (74.2%) lesions identified on FDG PET were classified as true positive, i.e. malignant (in 67 patients) and 17/155 (10.8%) lesions as false positive, i.e. benign (in 9 patients); 7/155 (4.5%) as false negative (in 7 patients) and 16/155 (10.3%) as true negative (in 14 patients). FDG PET incorrectly staged 16/70 (22.9%) patients: 3/70 (4.3%) were downstaged whereas 13/70 (18.6%) were upstaged. SUV did not help to discriminate between true- and false positive lesions (median SUVmax 4.23, IQR: 2.54–6.37 vs. 3.07, IQR: 2.14–5.58, P = 0.44 respectively). For true positive lesions, FDG uptake correlated with histological subtype, showing higher uptake in ductal carcinoma compared to lobular carcinoma (P

Contains fulltext : 238182.pdf (Publisher’s version ) (Closed access) Sorafenib leads to clinical benefit in a subgroup of patients, whereas all are exposed to potential toxicity. Currently, no predictive biomarkers are available. The purpose of this study was to evaluate whether (11)C-sorafenib and (15)O-H(2)O PET have potential to predict treatment efficacy. Methods: In this prospective exploratory study, 8 patients with advanced solid malignancies and an indication for sorafenib treatment were included. Microdose (11)C-sorafenib and perfusion (15)O-H(2)O dynamic PET scans were performed before and after 2 wk of sorafenib therapy. The main objective was to assess whether tumor (11)C-sorafenib uptake predicts sorafenib concentrations during therapy in corresponding tumor biopsy samples measured with liquid chromatography tandem mass spectrometry. Secondary objectives included determining the association of (11)C-sorafenib PET findings, perfusion (15)O-H(2)O PET findings, and sorafenib concentrations after therapeutic dosing with response. Results: (11)C-sorafenib PET findings did not predict sorafenib concentrations in tumor biopsy samples during therapy. In addition, sorafenib plasma and tumor concentrations were not associated with clinical outcome in this exploratory study. Higher (11)C-sorafenib accumulation in tumors at baseline and day 14 of treatment showed an association with poorer prognosis and correlated with tumor perfusion (Spearman correlation coefficient = 0.671, P = 0.020). Interestingly, a decrease in tumor perfusion measured with (15)O-H(2)O PET after only 14 d of therapy showed an association with response, with a decrease in tumor perfusion of 56% ± 23% (mean ± SD) versus 18% ± 32% in patients with stable and progressive disease, respectively. Conclusion: Microdose (11)C-sorafenib PET did not predict intratumoral sorafenib concentrations after therapeutic dosing, but the association between a decrease in tumor perfusion and clinical benefit warrants further investigation.

INTRODUCTION Nurse-Administered Propofol Continuous Infusion Sedation (NAPCIS) is a new nonanesthesia propofol delivery method for gastrointestinal endoscopy. NAPCIS is adopted from the computer-assisted propofol sedation (CAPS) protocol. We evaluated the effectiveness, efficiency, and safety of NAPCIS in low-risk subjects. METHODS Between December 2016 and July 2017, patients who underwent esophagogastroduodenoscopy or colonoscopy with NAPCIS at our center were compared against 2 historical control groups of similar patients who had undergone procedures with CAPS or midazolam and fentanyl (MF) sedation. RESULTS The mean age of the NAPCIS cohort (N = 3,331) was 55.2 years (45.8% male) for 945 esophagogastroduodenoscopies and 57.8 years (48.7% male) for 2,386 colonoscopies. The procedural success rates with NAPCIS were high (99.1%-99.2%) and similar to those seen in 3,603 CAPS (98.8%-99.0%) and 3,809 MF (99.0%-99.3%) controls. NAPCIS recovery times were shorter than both CAPS and MF (24.8 vs 31.7 and 52.4 minutes, respectively; P < 0.001). On arrival at the recovery unit, 86.6% of NAPCIS subjects were recorded as "Awake" compared with 82.8% of CAPS and 40.8% of MF controls (P < 0.001). Validated clinician and patient satisfaction scores were generally higher for NAPCIS compared with CAPS and MF subjects. For NAPCIS, there were only 4 cases of oxygen desaturation requiring transient mask ventilation and no serious sedation-related complications. These low complication rates were similar to those seen with CAPS (8 cases of mask ventilation) and MF (3 cases). DISCUSSION NAPCIS seems to be a safe, effective, and efficient means of providing moderate sedation for upper endoscopy and colonoscopy in low-risk patients.

Background: Retrospective studies suggest that low molecular weight heparin may delay the development of metastasis in patients with resected NSCLC. Methods: Multicentre phase 3 study with patients with completely resected NSCLC who were randomised after surgery to receive chemotherapy with or without nadroparin. The main exclusion criteria were R1/2 and wedge/segmental resection. FDG-PET was required. The primary endpoint was recurrence-free survival (RFS). Results: Among 235 registered patients, 202 were randomised (nadroparin: n = 100; control n = 102). Slow accrual enabled a decrease in the number of patients needed from 600 to 202, providing 80% power to compare RFS with 94 events (α = 0.05; 2-sided). There were no differences in bleeding events between the two groups. The median RFS was 65.2 months (95% CI, 36—NA) in the nadroparin arm and 37.7 months (95% CI, 22.7—NA) in the control arm (HR 0.77 (95% CI, 0.53–1.13, P = 0.19). FDG-PET SUVmax ≥10 predicted a greater likelihood of recurrence in the first year (HR 0.48, 95% CI 0.22–0.9, P = 0.05). Conclusions: Adjuvant nadroparin did not improve RFS in patients with resected NSCLC. In this study, a high SUVmax predicted a greater likelihood of recurrence in the first year. Clinical trial registration: Netherlands Trial registry: NTR1250/1217.

PET is increasingly used for prostate cancer (PCa) diagnostics. Important PCa radiotracers include 68Ga-prostate-specific membrane antigen HBED-CC ( 68Ga-PSMA), 18F-DCFPyL, 18F-fluorome-thylcholine ( 18F-FCH), and 18F-dihydrotestosterone ( 18F-FDHT). Knowledge on the variability of tracer uptake in healthy tissues is important for accurate PET interpretation, because malignancy is suspected only if the uptake of a lesion contrasts with its background. Therefore, the aim of this study was to quantify uptake variability of PCa tracers in healthy tissues and identify stable reference regions for PET interpretation. Methods: A total of 232 PCa PET/CT scans from multiple hospitals was analyzed, including 87 68Ga-PSMA scans, 50 18F-DCFPyL scans, 68 18F-FCH scans, and 27 18F-FDHT scans. Tracer uptake was assessed in the blood pool, lung, liver, bone marrow, and muscle using several SUVs (SUV max, SUV mean, SUV peak). Variability in uptake between patients was analyzed using the coefficient of variation (COV%). For all tracers, SUV reference ranges (95th percentiles) were calculated, which could be applicable as image-based quality control for future PET acquisitions. Results: For 68Ga-PSMA, the lowest uptake variability was observed in the blood pool (COV, 19.9%), which was significantly more stable than all other tissues (COV, 29.8%–35.2%; P 5 0.001–0.024). For 18F-DCFPyL, the lowest variability was observed in the blood pool and liver (COV, 14.4% and 21.7%, respectively; P 5 0.001–0.003). The least variable 18F-FCH uptake was observed in the liver, blood pool, and bone marrow (COV, 16.8%–24.2%; P 5 0.001–0.012). For 18F-FDHT, low uptake variability was observed in all tissues, except the lung (COV, 14.6%–23.6%; P 5 0.001–0.040). The different SUV types had limited effect on variability (COVs within 3 percentage points). Conclusion: In this multicenter analysis, healthy tissues with limited uptake variability were identified, which may serve as reference regions for PCa PET interpretation. These reference regions include the blood pool for 68Ga-PSMA and 18F-DCFPyL and the liver for 18F-FCH and 18F-FDHT. Healthy tissue SUV reference ranges are presented and applicable as image-based quality control.

RATIONALE: This study evaluates the lymphatic drainage patterns and determines the accuracy of the sentinel lymph node biopsy (SLNB) in patients diagnosed with a cT1-2N0 OSCC and a history of neck surgery or radiotherapy in three Dutch head and neck centers.MATERIALS AND METHODS: Retrospective analysis of 53 cT1-2N0 OSCC patients, who underwent SLNB between 2007 and 2016, after a history of neck surgery or radiotherapy. Ten patients had previous treatment of the neck only contralateral from the current tumour. These ten patients were not used for the analysis of lymphatic drainage patterns. The 43 patients with previous ipsilateral or bilateral treatment of the neck had a history of ipsilateral SLN extirpation (n = 9; 21%), neck dissection (n = 16; 37%), radiotherapy (n = 10; 23%), or combined neck dissection and radiotherapy (n = 8; 19%).RESULTS: SLNs were detected in 45 patients, resulting in an identification rate of 85% (45/53). Three patients (7%) had at least one positive SLN. One patient (1/45; 2%) was diagnosed with regional recurrence during the follow-up after a negative SLNB (sensitivity 75%, negative predictive value 98%). The first SLN was detected in level I-III in 58% of the patients, unexpected drainage patterns were observed in 30% (first SLN level IV 9% and level V 5% and contralateral neck in well-lateralized tumours 16%). In 12% no lymphatic drainage pattern was visible.CONCLUSIONS: SLNB seems to be a reliable procedure for neck staging of cT1-2N0 OSCC patients with a previously treated neck. SLNB determines the individual lymphatic drainage patterns, enabling visualization of unexpected drainage pattern variability in 30% of these patients.

PURPOSE: In-vivo quantification of tumor uptake of 89-zirconium (89Zr)-labelled monoclonal antibodies (mAbs) with PET provides a potential tool in strategies to optimize tumor targeting and therapeutic efficacy. A specific challenge for 89Zr-immuno-PET is low tumor contrast. This is expected to result in interobserver variation in tumor delineation. Therefore, the aim of this study was to determine interobserver reproducibility of tumor uptake measures by tumor delineation on 89Zr-immuno-PET scans.METHODS: Data were obtained from previously published clinical studies performed with 89Zr-rituximab, 89Zr-cetuximab and 89Zr-trastuzumab. Tumor lesions on 89Zr-immuno-PET were identified as focal uptake exceeding local background by a nuclear medicine physician. Three observers independently manually delineated volumes of interest (VOI). Maximum, peak and mean standardized uptake values (SUVmax, SUVpeak and SUVmean) were used to quantify tumor uptake. Interobserver variability was expressed as the coefficient of variation (CoV). The performance of semi-automatic VOI delineation using 50% of background-corrected ACpeak was described.RESULTS: In total, 103 VOI were delineated (3-6 days post injection (D3-D6)). Tumor uptake (median, interquartile range) was 9.2 (5.2-12.6), 6.9 (4.0-9.6) and 5.5 (3.3-7.8) for SUVmax, SUVpeak and SUVmean. Interobserver variability was 0% (0-12), 0% (0-2) and 7% (5-14), respectively (n = 103). The success rate of the semi-automatic method was 45%. Inclusion of background was the main reason for failure of semi-automatic VOI.CONCLUSIONS: This study shows that interobserver reproducibility of tumor uptake quantification on 89Zr-immuno-PET was excellent for SUVmax and SUVpeak using a standardized manual procedure for tumor segmentation. Semi-automatic delineation was not robust due to limited tumor contrast.

Introduction Fecal microbiota transplantation resolves recurrent Clostridium difficile infections in greater than 82% of patients. Highly screened, processed universal donor fecal material is available. We compared cost and scheduling efficiency of fecal microbiota transplantation by universal donors to patient-directed donors. Methods Medical records from a prospectively maintained database of recurrent C. difficile patients who underwent fecal microbiota transplantation between 2012 and 2017 were reviewed retrospectively. Patient-directed donor stool was prepared in our microbiology laboratory using protocol-based screening. We transitioned to purchasing and using universal donor fecal material in 2015. Clinical outcomes, adverse events, time between consult to infusion, consultation fees, and material costs were compared. This was a retrospective comparison of two historical cohorts. Results A total of 111 fecal microbiota transplantations were performed on 105 patients (56 from patient-directed donors and 55 from universal donors). Median recipient age was 66 years (18–96) with male to female ratio of 1:2.7, equivalent in both cohorts. Total consultation fees were significantly lower in the universal donor group owing to fewer infectious disease consultations. Costs for donor screening and stool preparation were lower in the universal donor cohort ($485.0 vs. $1189.90 ± 541.4, p

OBJECTIVES: There is increased interest in various new quantitative uptake metrics beyond standardized uptake value (SUV) in oncology PET/CT studies. The purpose of this study is to investigate the variability and test-retest repeatability (TRT) of metabolically active tumor volume (MATV) measurements and several other new quantitative metrics in non-small cell lung cancer (NSCLC) using [18F]FDG PET/CT with different segmentation methods, user interactions, uptake intervals, and reconstruction protocols. METHODS: Ten advanced NSCLC patients received two whole-body [18F]FDG PET/CT scans at both 60 and 90 min post-injection. PET data were reconstructed with four different protocols. Eight segmentation methods were applied to delineate lesions with and without a tumor mask. MATV, maximum and mean SUV (SUVmax, SUVmean), total lesion glycolysis (TLG), and intralesional heterogeneity features were derived. Variability and repeatability were evaluated using a generalized estimating equations statistical model with Bonferroni correction for multiple comparisons. The statistical model, including interaction between uptake interval and reconstruction protocol, was applied individually to the data obtained from each segmentation method. RESULTS: Without masking, none of the segmentation methods could delineate all lesions correctly. MATV was affected by both uptake interval and reconstruction settings for most segmentation methods. Similar observations were obtained for the uptake metrics SUVmax, SUVmean, TLG, homogeneity, entropy, and zone percentage. No effect of uptake interval was observed on TRT metrics, while the reconstruction protocol affected the TRT of SUVmax. Overall, segmentation methods showing poor quantitative performance in one condition showed better performance in other (combined) conditions. For some metrics, a clear statistical interaction was found between the segmentation method and both uptake interval and reconstruction protocol. CONCLUSION: All segmentation results need to be reviewed critically. MATV and other quantitative uptake metrics, as well as their TRT, depend on segmentation method, uptake interval, and reconstruction protocol. To obtain quantitative reliable metrics, with good TRT performance, the optimal segmentation method depends on local imaging procedure, the PET/CT system and/or reconstruction protocol. Rigid harmonization of imaging procedure and PET/CT performance will be helpful in mitigating this variability.

Background and purpose: In head and neck squamous cell carcinoma (HNSCC) (chemo)radiotherapy is increasingly used to preserve organ functionality. The purpose of this study was to identify predictive pretreatment DWI- and 18F-FDG-PET/CT-parameters for treatment failure (TF), locoregional recurrence (LR) and death in HNSCC patients treated by (chemo)radiotherapy. Materials and methods: We retrospectively included 134 histologically proven HNSCC patients treated with (chemo)radiotherapy between 2012-2017. In 58 patients pre-treatment DWI and 18F-FDG-PET/CT were performed, in 31 patients DWI only and in 45 patients 18F-FDG-PET/CT only. Primary tumor (PT) and largest lymph node (LN) metastasis were quantitatively assessed for TF, LR and death. Multivariate analysis was performed for 18F-FDG-PET/CT and DWI separately and thereafter combined. In patients with both imaging modalities, positive and negative predictive value in TF and differences in LR and death, were assessed. Results: Mean follow-up was 25.6 months (interquartile-range; 14.0–37.1 months). Predictors of treatment failure, corrected for TNM-stage and HPV-status, were SUVmax-PT, ADCmax-PT, total lesion glycolysis (TLG-LN), ADCp20-LN (P = 0.049, P = 0.024, P = 0.031, P = 0.047, respectively). TLG-PT was predictive for LR (P = 0.003). Metabolic active tumor volume (MATV-PT) (P = 0.003), ADCGTV-PT (P < 0.001), ADCSD (P = 0.048) were significant predictors for death. In patients with both imaging modalities SUVmax-PT remained predictive for treatment failure (P = 0.049), TLG-LN for LR (P = 0.003) and ADCGTV-PT for death (P < 0.001). Higher predictive value for treatment failure was found for the combination of SUVmax-PT and ADCmax-PT, compared to either one separately. Conclusion: Both DWI- and 18F-FDG-PET/CT-parameters appear to have predictive value for treatment failure, locoregional recurrence and death. Combining SUVmax-PT and ADCmax-PT resulted in better prediction of treatment failure compared to single parameter assessment.

Objective 18F FDG-PET is superior to other imaging techniques in revealing residual laryngeal cancer after radiotherapy. Unfortunately, its specificity is low, due to FDG uptake in inflammation and in anaerobic conditions. PET imaging with the amino acid-based radiopharmaceutical C11-methionine (MET) should be less influenced by post-radiation conditions. The aim of this study was to investigate the potential of MET in diagnosing recurrent laryngeal cancer after radiotherapy as compared to 18F-FDG. Methods Forty-eight patients with a clinical suspicion of local residual disease at least 3 months after completion of radiotherapy or chemoradiotherapy for a T2-4 laryngeal carcinoma, along with an indication for direct laryngoscopy, were included. They received MET-PET and FDG-PET prior to the direct laryngoscopy. One senior nuclear medicine physician assessed both the FDG-PET and MET-PET images visually for the degree of abnormal uptake. The gold standard was a biopsy-proven recurrence 12 months after PET. The nuclear physician had no access to the medical charts and was blinded to the results of the other PET. Sensitivity, specificity and positive and negative predictive value were calculated. Results The sensitivity of FDG was 77.3% and the specificity 56.0% after the conservative reading, with these values equalling 54.5% and 76.0% for MET. The positive predictive value of FDG was 60.7% and the negative predictive value 73.7%. The PPV of MET was 66.7%, and the NPV was 65.5%. The McNemar test within diseased (sensitivity comparison) shows a p-value of 0.125, and the McNemar test within non-diseased (specificity comparison) shows a P-value of 0.180. Conclusion MET-PET is not superior to FDG-PET in terms of identifying recurrent laryngeal cancer.

Introduction: Estrogen receptor (ER) expression largely determines the therapy choice for patients diagnosed with metastatic breast cancer (MBC). Given potential conversion of ER-status, the current golden standard for ER assessment is by immunohistochemistry (IHC) on metastatic tissue. Since a biopsy is cumbersome and sometimes not feasible, ER-status assessments by means of [18F]-fluorestradiol (FES)-PET or circulating tumor cells (CTCs) might be potential alternatives. We hypothesize that FES-PET or CTCs can determine ER status in patients with MBC, in a more efficient and patient friendly way than IHC. Methods: In the Dutch multicenter IMPACT-MBC trial (NCT01832051) patients with non-rapidly progressive MBC at first presentation, regardless of subtype, underwent extensive molecular imaging (including FES-PET, 89Zr-trastuzumab-PET and serial [18F]-fluorodeoxyglucose (FDG)-PET), a metastasis biopsy and blood sampling to obtain a whole body molecular profile of their disease. ER-status on the metastasis biopsy was evaluated by IHC and considered positive if ≥10% of the tumor cells showed ER expression. The FES-PET was considered positive when the maximum standardized uptake value (SUVmax) of at least one lesion was ≥ 1.5. Reverse transcription polymerase chain reaction was used to quantify the ESR1 expression in CTCs. ER-positivity was defined as an ESR1 mRNA ΔCq level ≥ -7.86, corrected for background healthy donor blood signal, only in samples with ≥5 CTCs/7.5ml and a sufficient mRNA signal of reference and epithelial genes. Sensitivity, specificity, positive and negative predictive values were calculated (PPV and NPV). Results: From 178 patients of 201 evaluable patients both metastasis IHC and FES-PET could be assessed. 129 of these 178 patients had an IHC ER positive metastasis (72%) and 133 patients had a positive FES-PET (75%). The PPV and NPV for IHC by FES-PET were 91% and 82%, respectively. From 54 of the 178 patients, blood samples contained sufficient CTCs for ESR1 analysis, allowing combined assessment of IHC, FES-PET and CTCs. ER positive CTCs were present in 45 patients (83%). Table 1 Metastasis ER positive (n=42)Metastasis ER negative (n=12)Sensitivity(%)PPV(%)Specificity(%)NPV(%)FES-PET positive4159889 CTC ER positive3879084 FES-PET and CTC positive3849090 FES-PET negative17 5888CTC ER negative45 4256FES-PET and CTC negative14 3380 Conclusion: In newly diagnosed patients with MBC, ER-status in metastatic lesions could be predicted by means of non-invasive FES-PET scan or CTCs. Prediction was most optimal with FES-PET compared to CTCs, and combining FES-PET with CTCs did not essentially improve this. Furthermore, CTCs were not detectable in most of these patients with non-rapidly progressive MBC, limiting their applicability for the present purpose. However, as CTC assessment is most patient friendly, CTCs might be considered as first step in determining MBC ER-status. If ER positive CTCs are detected, ER positive disease is very likely; if no- or ER negative CTCs are detected, MBC ER-status needs to be further assessed by means of tissue confirmation or FES-PET. Funding: Dutch Cancer Society grant RUG 2012-5565, project EMCR 16-8196 Citation Format: Eisses B, Angus L, van der Vegt B, Sieuwerts AM, Kraan J, Martens JW, Glaudemans AW, Brouwers AH, Hoekstra OS, Oyen W, Emmering J, Gerritse S, Menke-van der Houven van Oordt CW, Boon E, van Herpen CM, Jager A, Sleijfer S, de Vries EG, Schröder CP. Non-invasive estrogen receptor assessment by [18F]-fluorestradiol(FES)-PET or circulating tumor cells predicts receptor status in patients with metastatic breast cancer [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr PD4-09.

Antibody fragment F8-mediated interleukin 10 (IL10) delivery is a novel treatment for rheumatoid arthritis (RA). F8 binds to the extra-domain-A of fibronectin (ED-A). In this study, in vivo biodistribution and arthritis targeting of radiolabeled F8-IL10 were investigated in RA patients, followed by further animal studies. Therefore, three RA patients (DAS28 > 3.2) received 0.4 mg of 30–74 megabecquerel [124I]I–F8–IL10 for PET-CT and blood sampling. In visually identified PET-positive joints, target-to-background was calculated. Healthy mice, rats, and arthritic rats were injected with iodinated F8-IL10 or KSF-IL10 control antibody. Various organs were excised, weighed, and counted for radioactivity. Tissue sections were stained for fibronectin ED-A. In RA patients, [124I]I–F8–IL10 was cleared rapidly from the circulation with less than 1% present in blood after 5 min. PET-CT showed targeting in 38 joints (11–15 per patient) and high uptake in the liver and spleen. Mean target-to-background ratios of PET-positive joints were 2.5 ± 1.2, 1.5 times higher for clinically active than clinically silent joints. Biodistribution of radioiodinated F8-IL10 in healthy mice showed no effect of the radioiodination method. [124I]I–F8–IL10 joint uptake was also demonstrated in arthritic rats, ∼14-fold higher than that of the control antibody [124I]I-KSF-IL10 (p < 0.001). Interestingly, liver and spleen uptake were twice as high in arthritic than in healthy rats and were related to increased (∼7×) fibronectin ED-A expression in these tissues. In conclusion, [124I]I–F8–IL10 uptake was observed in arthritic joints in RA patients holding promise for visualization of inflamed joints by PET-CT imaging and therapeutic targeting. Patient observations and, subsequently, arthritic animal studies pointed to awareness of increased [124I]I–F8–IL10 uptake in the liver and spleen associated with moderate systemic inflammation. This translational study demonstrated the value of in vivo biodistribution and PET-CT-guided imaging in development of new and potential antirheumatic drugs’., Molecular Pharmaceutics, 16 (1), ISSN:1543-8384, ISSN:1543-8392

Purpose Positron emission tomography (PET) with Zirconium-89 (Zr-89)-labeled antibodies can be used for in vivo quantification of antibody uptake. Knowledge about measurement variability is required to ensure correct interpretation. However, no clinical studies have been reported on measurement variability of Zr-89 immuno-PET. As variability due to low signal-to-noise is part of the total measurement variability, the aim of this study was to assess noise-induced variability of Zr-89 -immuno-PET using count-reduced clinical images. Procedures Data were acquired from three previously reported clinical studies with [89Zr]antiCD20 (74 MBq, n = 7), [89Zr]antiEGFR (37 MBq, n = 7), and [89Zr]antiCD44 (37 MBq, n = 13), with imaging obtained 1 to 6 days post injection (D0–D6). Volumes of interest (VOIs) were manually delineated for liver, spleen, kidney, lung, brain, and tumor. For blood pool and bone marrow, fixed-size VOIs were used. Original PET list mode data were split and reconstructed, resulting in two count-reduced images at 50 % of the original injected dose (e.g., 37 MBq74inj). Repeatability coefficients (RC) were obtained from Bland-Altman analysis on standardized uptake values (SUV) derived from VOIs applied to these images. Results The RC for the combined manually delineated organs for [89Zr] antiCD20 (37 MBq74inj) increased from D0 to D6 and was less than 6 % at all time points. Blood pool and bone marrow had higher RC, up to 43 % for 37 MBq74inj at D6. For tumor, the RC was up to 42 % for [89Zr]antiCD20 (37 MBq74inj). For [89Zr]antiCD20, (18 MBq74inj), [89Zr]antiEGFR (18 MBq37inj), and [89Zr]antiCD44 (18 MBq37inj), measurement variability was independent of the investigated antibody. Conclusions Based on this study, noise-induced variability results in a RC for Zr-89-immuno-PET (37 MBq) around 6 % for manually delineated organs combined, increasing up to 43 % at D6 for blood pool and bone marrow, assuming similar biodistribution of antibodies. The signal-to-noise ratio leads to tumor RC up to 42 %. Electronic supplementary material The online version of this article (10.1007/s11307-018-1200-4) contains supplementary material, which is available to authorized users.

PD-L1 immunohistochemistry correlates only moderately with patient survival and response to PD-(L)1 treatment. Heterogeneity of tumor PD-L1 expression might limit the predictive value of small biopsies. Here we show that tumor PD-L1 and PD-1 expression can be quantified non-invasively using PET-CT in patients with non-small-cell lung cancer. Whole body PD-(L)1 PET-CT reveals significant tumor tracer uptake heterogeneity both between patients, as well as within patients between different tumor lesions., Assessment of PD-1 and PD-L1 expression can be predictive of immunotherapy response in lung cancer. Here the authors assess the clinical toxicity, safety and quality of non-invasive imaging of PD-1 and PD-L1 expression in 13 patients with advanced lung cancer prior to treatment with immunotherapy and show it correlates with response.

Purpose The detection of lymph-node metastases (N1) with conventional imaging such as magnetic resonance imaging (MRI) and computed tomography (CT) is inadequate for primarily diagnosed prostate cancer (PCa). Prostate-specific membrane antigen (PSMA) PET/CT is successfully introduced for the staging of (biochemically) recurrent PCa. Besides the frequently used 68gallium-labelled PSMA tracers, 18fluorine-labelled PSMA tracers are available. This study examined the diagnostic accuracy of 18F-DCFPyL (PSMA) PET/CT for lymph-node staging in primary PCa. Methods This was a prospective, multicentre cohort study. Patients with primary PCa underwent 18F-DCFPyL PET/CT prior to robot-assisted radical prostatectomy (RARP) with extended pelvic lymph-node dissection (ePLND). Patients were included between October 2017 and January 2020. A Memorial Sloan Kettering Cancer Centre (MSKCC) nomogram risk probability of ≥ 8% of lymph-node metastases was set to perform ePLND. All images were reviewed by two experienced nuclear physicians, and were compared with post-operative histopathologic results. Results A total of 117 patients was analysed. Lymph-node metastases (N1) were histologically diagnosed in 17/117 patients (14.5%). The sensitivity, specificity, positive predictive value and negative predictive value for the 18F-DCFPyL PET/CT detection of pelvic lymph-node metastases on a patient level were 41.2% (confidence interval (CI): 19.4–66.5%), 94.0% (CI 86.9–97.5%), 53.8% (CI 26.1–79.6%) and 90.4% (CI 82.6–95.0%), respectively. Conclusion 18F-DCFPyL PET/CT showed a high specificity (94.4%), yet a limited sensitivity (41.2%) for the detection of pelvic lymph-node metastases in primary PCa. This implies that current PSMA PET/CT imaging cannot replace diagnostic ePLND. Further research is necessary to define the exact place of PSMA PET/CT imaging in the primary staging of PCa.

Aim/Introduction Up to one third of diffuse large B-cell lymphoma (DLBCL) patients experience relapse or fail to achieve complete remission during first-line treatment. Identification of poor prognosis patients might be further improved by radiomics. Radiomics analysis of imaging data provides quantitative features of tumor characteristics such as intensity, shape, volume, texture and intra- and inter-lesion heterogeneity. The objective of this study was to assess the added value of baseline quantitative radiomics features in DLBCL patients compared to currently used clinical characteristics such as the IPI score. Materials and Methods 317 newly diagnosed DLBCL patients with baseline 18F-FDG PET/CT scans from the HOVON84 trial (Lugtenburg et al, JCO 2020) were included. Lesions were delineated using a fully automated preselection of 18F-FDG avid structures defined by a SUV ≥ 4.0 and volume >3mL. Missed lesions were added and non-tumour regions were removed (accurate tool, https://petralymphoma.org). Next, 490 radiomics features were extracted from the volume of interest using RaCat software (Pfaehler et al, 2019). To reduce feature space dimensions, we made a preselection of clinically most relevant radiomics features based on literature (SUVmax, SUVmean, SUVpeak, total lesion glycolysis, metabolic tumor volume (MTV), dissemination features and sphericity) and used logistic regression with backward feature selection to predict 2-year time to progression (TTP), defined as time from baseline PET/CT to progression. Patients who died without progression were censored at date of death. Furthermore, we tested the predictive value of known clinical predictors (age (cut off: >60 years), WHO performance status (cut-off: ≥ 1 and ≥2), Ann Arbor stage, extranodal involvement (cut-off: ≥ 1 and >1), lactate dehydrogenase (LDH) level and bulky disease (≥ 10 cm)) and of a model that combined radiomics and clinical parameters. Model performance was assessed using repeated cross-validation (5 folds, 2000 repeats) yielding the mean receiver-operator-characteristics curve integral (AUC). High- and low-risk groups were defined based on prevalence of events, diagnostic performance was assessed using positive- and negative predictive values. Patients censored before 2 years of follow-up were excluded for the prediction models and diagnostic performance. Results The categorical IPI score yielded in a cross-validated AUC (CV-AUC) of 0.68 (Figure 1). The highest performance for the radiomics model was observed for the natural logarithms of MTV and SUVpeak and the maximal distance between the largest lesion and any other lesion (Dmaxbulk), which yielded in a cross-validated AUC (CV-AUC) of 0.75±0.07, which was significantly higher than the discriminative power of the MTV model (CV-AUC: 0.66±0.08, p=0.01). LDH/upper limit of normal, WHO performance status ≥1 and extranodal involvement ≥1 showed the highest performance for the clinical prediction model with a CV-AUC of 0.71±0.08. When combining radiomics features with clinical predictors, the highest performance was observed for the natural logarithms of MTV and SUVpeak, Dmaxbulk, WHO performance status ≥ 1 and age, with a CV-AUC of 0.77±0.07, which was significantly higher than the IPI model (p=0.003). Adding radiomics features to clinical predictors increased the positive predictive value with 15%, with more accurate selection of high-risk patients compared to the IPI model (progression at 2-year TTP: 28.3% vs 43.8%, respectively). Conclusion Combining quantitative radiomics features extracted from baseline 18F-FDG PET/CT scans with components of the IPI score significantly improved identification of patients at risk of relapse at baseline. Adding radiomics features can significantly increase the efficiency of clinical trials in poor prognosis patients. Figure Disclosures Lugtenburg: Incyte: Honoraria; Celgene: Honoraria; Genmab: Honoraria; Genentech: Honoraria; Roche: Research Funding; Servier: Honoraria, Research Funding; Takeda: Honoraria, Research Funding. Zijlstra:Roche: Research Funding.

The aim of this work was to quantify the uptake of F-18-BMS-986192, a programmed cell death ligand 1 (PD-L1) adnectin PET tracer, in patients with non-small cell lung cancer. To this end, plasma input kinetic modeling of dynamic tumor uptake data with online arterial blood sampling was performed. In addition, the accuracy of simplified uptake metrics such as SUV was investigated. Methods: Data from a study with F-18-BMS-986192 in patients with advanced-stage non-small cell lung cancer eligible for nivolumab treatment were used if a dynamic scan was available and lesions were present in the field of view of the dynamic scan. After injection of F-18-BMS-986192, a 60-min dynamic PET/CT scan was started, followed by a 30-min whole-body PET/CT scan. Continuous arterial and discrete arterial and venous blood sampling were performed to determine a plasma input function. Tumor time-activity curves were fitted by several plasma input kinetic models. Simplified uptake parameters included tumor-to-blood ratio as well as several SUV measures. Results: Twenty-two tumors in 9 patients were analyzed. The arterial plasma input single-tissue reversible compartment model with fitted blood volume fraction seems to be the most preferred model as it best fitted 11 of 18 tumor time-activity curves. The distribution volume (V-T) ranged from 0.4 to 4.8 mL.cm(-3). Similar values were obtained with an image-derived input function. From the simplified measures, SUV normalized for body weight at 50 and 67 min after injection correlated best with V-T, with an R-2 of more than 0.9. Conclusion: A single-tissue reversible model can be used to quantify tumor uptake of the PD-L1 PET tracer F-18-BMS-986192. SUV at 60 min after injection, normalized for body weight, is an accurate simplified parameter for uptake assessment of baseline studies. To assess its predictive value for response evaluation during programmed cell death protein 1 or PD-L1 immune checkpoint inhibition, further validation of SUV against V-T based on an image-derived input function is recommended.

Abstract Background Radiomics is aimed at image-based tumor phenotyping, enabling application within clinical-decision-support-systems to improve diagnostic accuracy and allow for personalized treatment. The purpose was to identify predictive 18-fluor-fluoro-2-deoxyglucose (18F-FDG) positron-emission tomography (PET) radiomic features to predict recurrence, distant metastasis, and overall survival in patients with head and neck squamous cell carcinoma treated with chemoradiotherapy. Methods Between 2012 and 2018, 103 retrospectively (training cohort) and 71 consecutively included patients (validation cohort) underwent 18F-FDG-PET/CT imaging. The 434 extracted radiomic features were subjected, after redundancy filtering, to a projection resulting in outcome-independent meta-features (factors). Correlations between clinical, first-order 18F-FDG-PET parameters (e.g., SUVmean), and factors were assessed. Factors were combined with 18F-FDG-PET and clinical parameters in a multivariable survival regression and validated. A clinically applicable risk-stratification was constructed for patients’ outcome. Results Based on 124 retained radiomic features from 103 patients, 8 factors were constructed. Recurrence prediction was significantly most accurate by combining HPV-status, SUVmean, SUVpeak, factor 3 (histogram gradient and long-run-low-grey-level-emphasis), factor 4 (volume-difference, coarseness, and grey-level-non-uniformity), and factor 6 (histogram variation coefficient) (CI = 0.645). Distant metastasis prediction was most accurate assessing metabolic-active tumor volume (MATV)(CI = 0.627). Overall survival prediction was most accurate using HPV-status, SUVmean, SUVmax, factor 1 (least-axis-length, non-uniformity, high-dependence-of-high grey-levels), and factor 5 (aspherity, major-axis-length, inversed-compactness and, inversed-flatness) (CI = 0.764). Conclusions Combining HPV-status, first-order 18F-FDG-PET parameters, and complementary radiomic factors was most accurate for time-to-event prediction. Predictive phenotype-specific tumor characteristics and interactions might be captured and retained using radiomic factors, which allows for personalized risk stratification and optimizing personalized cancer care. Trial registration Trial NL3946 (NTR4111), local ethics commission reference: Prediction 2013.191 and 2016.498. Registered 7 August 2013, https://www.trialregister.nl/trial/3946

Background: Positron Emission Tomography (PET) is routinely used for cancer staging and treatment follow up. Metabolic active tumor volume (MATV) as well as total MATV (TMATV - including primary tumor, lymph nodes and metastasis) and/or total lesion glycolysis (TLG) derived from PET images have been identified as prognostic factor or for the evaluation of treatment efficacy in cancer patients. To this end a segmentation approach with high precision and repeatability is important. However, the implementation of a repeatable and accurate segmentation algorithm remains an ongoing challenge. Methods: In this study, we compare two artificial intelligence (AI) based segmentation methods with conventional segmentation approaches in terms of repeatability. One segmentation approach is based on a textural feature (TF) segmentation approach designed for accurate and repeatable segmentation of primary tumors and metastasis. Moreover, a Convolutional Neural Network (CNN) is trained. The algorithms are trained, validated and tested using a lung cancer PET dataset. The segmentation accuracy of both segmentation approaches is compared using the jaccard coefficient (JC). Additionally, the approaches are applied on a fully independent test-retest dataset. The repeatability of the methods is compared with the repeatability of two majority vote (MV2, MV3) approaches, 41%SUVMAX, and a SUV>4 segmentation (SUV4). Repeatability is assessed with test-retest coefficients (TRT%) and intraclass correlation coefficient (ICC). A TRT% of 0 indicates perfect repeatability and an ICC>0.9 was regarded as representing excellent repeatability.Results: The accuracy of the segmentations with the reference segmentation was good (JC median TF: 0.7, CNN: 0.73) Both segmentation approaches outperformed together with the MV2 approach the other conventional segmentation methods in terms of test-retest coefficient (TRT% mean: TF: 13.0%, CNN: 13.9%, MV2: 14.1%, MV3: 28.1%, 41%SUVMAX: 28.1%, SUV4: 18.1% ) and ICC (TF: 0.98, MV2: 0.97, CNN: 0.99, MV3: 0.73, SUV4: 0.81, and 41%SUVMAX: 0.68).Conclusion: The AI based segmentation approaches used in this study provided better repeatability than conventional segmentation approaches. Moreover, both algorithms lead to accurate segmentations for both primary tumors as well as metastasis and are therefore good candidates for PET tumor segmentation.

Purpose This pilot study aimed to determine interobserver reliability and ease of use of three workflows for measuring metabolic tumor volume (MTV) and total lesion glycolysis (TLG) in diffuse large B cell lymphoma (DLBCL). Procedures Twelve baseline [18F]FDG PET/CT scans from DLBCL patients with wide variation in number and size of involved organs and lymph nodes were selected from the international PETRA consortium database. Three observers analyzed scans using three workflows. Workflow A: user-defined selection of individual lesions followed by four automated segmentations (41%SUVmax, A50%SUVpeak, SUV≥2.5, SUV≥4.0). For each lesion, observers indicated their “preferred segmentation.” Individually selected lesions were summed to yield total MTV and TLG. Workflow B: fully automated preselection of [18F]FDG-avid structures (SUV≥4.0 and volume≥3ml), followed by removing non-tumor regions with single mouse clicks. Workflow C: preselected volumes based on Workflow B modified by manually adding lesions or removing physiological uptake, subsequently checked by experienced nuclear medicine physicians. Workflow C was performed 3 months later to avoid recall bias from the initial Workflow B analysis. Interobserver reliability was expressed as intraclass correlation coefficients (ICC). Results Highest interobserver reliability in Workflow A was found for SUV≥2.5 and SUV≥4.0 methods (ICCs for MTV 0.96 and 0.94, respectively). SUV≥4.0 and A50%Peak were most and SUV≥2.5 was the least preferred segmentation method. Workflow B had an excellent interobserver reliability (ICC = 1.00) for MTV and TLG. Workflow C reduced the ICC for MTV and TLG to 0.92 and 0.97, respectively. Mean workflow analysis time per scan was 29, 7, and 22 min for A, B, and C, respectively. Conclusions Improved interobserver reliability and ease of use occurred using fully automated preselection (using SUV≥4.0 and volume≥3ml, Workflow B) compared with individual lesion selection by observers (Workflow A). Subsequent manual modification was necessary for some patients but reduced interobserver reliability which may need to be balanced against potential improvement on prognostic accuracy.

5079 Background: In metastatic clear cell renal cell carcinoma (mccRCC), the number of International Metastatic Database Consortium (IMDC) risk factors plus metastatic sites may identify patients with rapid or slow disease progression in a period of watchful waiting (WW) (median WW of 8.4 vs 22.2 months; Rini et al. Lancet Oncol. 2016). We aimed to validate this and prospectively assess the added value of baseline PET with [18F]FDG and [89Zr]Zr-DFO-girentuximab to predict the WW-period in the multicenter IMaging PAtients for Cancer drug selecTion (IMPACT)-RCC cohort study. (NCT02228954). Methods: Between February 2015 and March 2018, 40 treatment-naïve mccRCC patients with a good (n=13) or intermediate prognosis (n=25) according to IMDC, were enrolled. Following baseline CT, [18F]FDG and [89Zr]Zr-DFO-girentuximab-PET, CT scans (RECIST1.1) were acquired at 2, 4, 6, 9, 12 months and thereafter every 4 months. Primary endpoint was time to radiological and/or clinical disease progression, requiring systemic treatment. Patients were assigned to a favorable (max) were measured in PET-positive lesions measuring ≥10mm, or 15mm in lymph nodes. High and low-uptake groups were defined based on median geometric mean (gm) SUVmax across patients. A one-sided test was used to validate observations by Rini et al; other tests were two-sided. Results: The median WW-period was 9.3 months in the unfavorable WW-group (n=19) vs 20.4 months in the favorable WW-group (n=21) (HR 1.89 95%CI 0.94-3.89; p=0.037), confirming observations of Rini et al. Patients with high [18F]FDG uptake had a median WW-period of 8.5 months compared to 25.2 months in the low-uptake group (HR 4.08 95%CI 1.89-9.28; p=0.0002). Patients with high [89Zr]Zr-DFO-girentuximab uptake had a median WW-period of 10.7 versus 16.4 months in the low-uptake group (HR 1.37; 95%CI 0.69-2.76; p=0.37). [18F]FDG uptake groups improved a Cox-model for WW based on the prognostic groups of Rini et al (p=0.0015); [89Zr]Zr-DFO-girentuximab did not (p=0.98). Conclusions: The IMPACT-RCC study validated the observations by Rini et al. and shows that adding baseline [18F]FDG PET further improves the prediction of the duration of the WW-period in mccRCC patients. Clinical trial information: NCT02228954 .

Immunotherapy has changed the treatment paradigm of many cancers. Monoclonal antibodies (mAbs) targeting specific immune checkpoints, in particular the programmed-death 1 (PD-1), programmed death ligand 1 (PD-L1), and cytotoxic T-lymphocyte–associated antigen 4 (CTLA-4) receptors, are active

Purpose Correct identification of tumour receptor status is important for treatment decisions in breast cancer. [18F]FES PET and [18F]FDHT PET allow non-invasive assessment of the oestrogen (ER) and androgen receptor (AR) status of individual lesions within a patient. Despite standardised analysis techniques, interobserver variability can significantly affect the interpretation of PET results and thus clinical applicability. The purpose of this study was to determine visual and quantitative interobserver variability of [18F]FES PET and [18F]FDHT PET interpretation in patients with metastatic breast cancer. Methods In this prospective, two-centre study, patients with ER-positive metastatic breast cancer underwent both [18F]FES and [18F]FDHT PET/CT. In total, 120 lesions were identified in 10 patients with either conventional imaging (bone scan or lesions > 1 cm on high-resolution CT, n = 69) or only with [18F]FES and [18F]FDHT PET (n = 51). All lesions were scored visually and quantitatively by two independent observers. A visually PET-positive lesion was defined as uptake above background. For quantification, we used standardised uptake values (SUV): SUVmax, SUVpeak and SUVmean. Results Visual analysis showed an absolute positive and negative interobserver agreement for [18F]FES PET of 84% and 83%, respectively (kappa = 0.67, 95% CI 0.48–0.87), and 49% and 74% for [18F]FDHT PET, respectively (kappa = 0.23, 95% CI − 0.04–0.49). Intraclass correlation coefficients (ICC) for quantification of SUVmax, SUVpeak and SUVmean were 0.98 (95% CI 0.96–0.98), 0.97 (95% CI 0.96–0.98) and 0.89 (95% CI 0.83–0.92) for [18F]FES, and 0.78 (95% CI 0.66–0.85), 0.76 (95% CI 0.63–0.84) and 0.75 (95% CI 0.62–0.84) for [18F]FDHT, respectively. Conclusion Visual and quantitative evaluation of [18F]FES PET showed high interobserver agreement. These results support the use of [18F]FES PET in clinical practice. In contrast, visual agreement for [18F]FDHT PET was relatively low due to low tumour-background ratios, but quantitative agreement was good. This underscores the relevance of quantitative analysis of [18F]FDHT PET in breast cancer. Trial registration ClinicalTrials.gov, NCT01988324. Registered 20 November 2013, https://clinicaltrials.gov/ct2/show/NCT01988324?term=FDHT+PET&draw=1&rank=2.

Patients who chronically use alcohol, marijuana, or opioids, or suffer from post-traumatic stress disorder (PTSD), can be difficult to sedate with midazolam and fentanyl, and often are referred for monitored anesthesia care during endoscopy. Nurse-administered propofol continuous infusion sedation (NAPCIS), which confers the benefit of propofol-based sedation without the added expense of anesthesia, is effective and safe for sedation of healthy patients. We investigated whether NAPCIS also is effective for patients who are difficult to sedate.We performed a retrospective study of patients who underwent upper endoscopy or colonoscopy with NAPCIS at a single center from January 2018 through April 2018. We reviewed records from patients who were heavy users of alcohol (n = 105), daily users of marijuana (n = 267) or opioids (n = 178), had a diagnosis of PTSD (n = 91), or were none of these (controls, n = 786). We compared mean fentanyl and propofol doses (adjusted for body weight), procedure and recovery times, procedure success rates, and adverse events.Compared with the controls, the marijuana group required higher mean adjusted sedative doses for colonoscopies (0.6 vs 0.4 mcg/kg fentanyl and 5.0 vs 4.7 mg/kg propofol; P ≤ .025 for both) and upper endoscopies (0.8 vs 0.3 mcg/kg fentanyl and 3.7 vs 3.2 mg/kg propofol; P ≤ .021 for both), the PTSD group required a higher dose of fentanyl for colonoscopies (0.6 vs 0.4 mcg/kg; P = .009), and the alcohol group required a higher dose of fentanyl for upper endoscopies (0.7 vs 0.3 mcg/kg; P.001). Procedure success rates were high (95.1%-100%) and did not differ significantly between the difficult-to-sedate groups and controls; mean procedure times (7.0-9.0 minutes for upper endoscopies, 21.1-22.9 minutes for colonoscopies) and recovery times (22.5-29.6 minutes) also were similar among groups. Upper endoscopies were associated with lower sedative doses and shorter procedure and recovery times than colonoscopies. Sedation-related adverse events were rare in all groups (only 26 cases total), and there were no serious complications or deaths.NAPCIS seems to be a safe and effective means of providing sedation for endoscopy to patients who may be difficult to sedate owing to alcohol, marijuana, or opioid use, or PTSD.

INTRODUCTION AND OBJECTIVE:Accurate detection of pelvic lymph node metastases (N-stage) in patients with primary prostate cancer (PCa) is important for disease prognostics, therapeutic decisions, a...

Background Surgical resection and irradiation of diffuse glioma are guided by standard MRI: T2/fluid attenuated inversion recovery (FLAIR)–weighted MRI for non-enhancing and T1-weighted gadolinium-enhanced (T1G) MRI for enhancing gliomas. Amino acid PET has been suggested as the new standard. Imaging combinations may improve standard MRI and amino acid PET. The aim of the study was to determine the accuracy of imaging combinations to detect glioma infiltration. Methods We included 20 consecutive adults with newly diagnosed non-enhancing glioma (7 diffuse astrocytomas, isocitrate dehydrogenase [IDH] mutant; 1 oligodendroglioma, IDH mutant and 1p/19q codeleted; 1 glioblastoma IDH wildtype) or enhancing glioma (glioblastoma, 9 IDH wildtype and 2 IDH mutant). Standardized preoperative imaging (T1-, T2-, FLAIR-weighted, and T1G MRI, perfusion and diffusion MRI, MR spectroscopy and O-(2-[18F]-fluoroethyl)-L-tyrosine ([18F]FET) PET) was co-localized with multiregion stereotactic biopsies preceding resection. Tumor presence in the biopsies was assessed by 2 neuropathologists. Diagnostic accuracy was determined using receiver operating characteristic analysis. Results A total of 174 biopsies were obtained (63 from 9 non-enhancing and 111 from 11 enhancing gliomas), of which 129 contained tumor (50 from non-enhancing and 79 from enhancing gliomas). In enhancing gliomas, the combination of apparent diffusion coefficient (ADC) with [18F]FET PET (area under the curve [AUC], 95% CI: 0.89, 0.79‒0.99) detected tumor better than T1G MRI (0.56, 0.39‒0.72; P < 0.001) and [18F]FET PET (0.76, 0.66‒0.86; P = 0.001). In non-enhancing gliomas, no imaging combination detected tumor significantly better than standard MRI. FLAIR-weighted MRI had an AUC of 0.81 (0.65–0.98) compared with 0.69 (0.56–0.81; P = 0.019) for [18F]FET PET. Conclusion Combining ADC and [18F]FET PET detects glioma infiltration better than standard MRI and [18F]FET PET in enhancing gliomas, potentially enabling better guidance of local therapy.

Biochemically recurrent prostate cancer (BCR) is the main indication to perform prostate-specific membrane antigen PET/CT. However, localizing BCR with prostate-specific membrane antigen PET/CT remains challenging in patients with low prostate-specific antigen (PSA) values. Here, we studied the impact of advanced PET image reconstruction methods on BCR localization and interobserver agreement with 18F-DCFPyL PET/CT scans in patients with BCR and low PSA values. Methods: Twenty-four patients with BCR and a PSA level of less than 2.0 ng/mL were included. PET images were reconstructed with 4-mm voxels and 2-mm voxels, both with and without point-spread function. All scans were interpreted by 4 nuclear medicine physicians. Additionally, PET examinations of 5 patients with primary prostate cancer and confirmed absence of lymph node metastases (after lymph node dissection) were included, to assess the risk of introducing false-positive findings when using advanced reconstruction. Calculation of BCR localization rates (scan positivity) was based on consensus among our readers (≥3 readers regarding a scan positive for BCR), as well as the individual scan interpretations of the readers. Results: In the consensus analysis, BCR localization rates were not higher using advanced reconstruction (62.5%-66.7%) than using 4-mm reconstruction (62.5%). On the basis of individual readings, however, more scans were positive using 2-mm reconstruction (74.0%; 95% confidence interval [CI], 65.0%-82.9%) (P = 0.027) and 2-mm reconstruction with point-spread function (75.0%; 95% CI, 66.2%-83.8%) (P = 0.014) than 4-mm reconstruction (65.6%; 95% CI, 56.0%-75.3%). A higher number of lesions was detected on the 2-mm scans (median, 2 lesions; interquartile range, 1-3) than the 4-mm scans (median, 1; interquartile range, 0-3; P = 0.008). The advanced reconstruction methods did not increase interobserver agreement (80.6%-84.7%), compared with the 4-mm scans (75.7%, P = 0.08-0.25). In the patients with primary prostate cancer, an equal number of false-positive lesions was observed among the different reconstruction methods (overall, n = 13). Conclusion: Applying advanced image reconstruction for 18F-DCFPyL PET/CT scans did not increase BCR localization in patients with BCR and low PSA values (reader consensus). Yet, the increased number of positive individual readings may imply that further development of image reconstruction methods holds potential to improve BCR localization. No improved interobserver agreement was observed with advanced reconstruction compared with standard 4-mm reconstruction.