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Purpose This study examined the usefulness of the maximum standardized uptake value (SUVmax) of myocardial [123I]-metaiodobenzylguanidine ([123I]-MIBG) to characterize myocardial function by comparing it with echocardiographic parameters in patients with pheochromocytoma. Materials and methods This study included 18 patients with pheochromocytoma who underwent both planar and [123I]-MIBG single-photon emission computed tomography/computed tomography scans and echocardiography before surgery. Myocardial [123I]-MIBG visibility and SUVmax were compared with echocardiographic parameters related to systolic and diastolic functions. The Mann–Whitney U test, Fisher exact test, or Spearman rank correlation assessed differences or relationships between two quantitative variables. Results On visual analysis, 6 patients showed normal myocardial [123I]-MIBG uptake, whereas 12 patients showed decreased myocardial [123I]-MIBG uptake. No patients showed systolic dysfunction. A significant difference was observed in the incidence of diastolic dysfunction between the groups with normal and decreased uptake (p = 0.009), and left ventricular (LV) diastolic dysfunction was observed in 9 (75%) of 12 patients with decreased myocardial uptake. The myocardial SUVmax was significantly lower in 9 patients with LV diastolic dysfunction than in 9 patients with normal cardiac function (1.67 ± 0.37 vs. 3.03 ± 1.38, p = 0.047). Myocardial SUVmax was positively correlated with septal e′ (early diastolic velocity of septal mitral annulus) (ρ = 0.51, p = 0.031) and negatively correlated with the septal E/e′ ratio (early mitral E-velocity to early diastolic velocity of septal mitral annulus; ρ = − 0.64, p = 0.004), respectively. Conclusions LV diastolic dysfunction was inversely related to myocardial [123I]-MIBG uptake. Myocardial [123I]-MIBG SUVmax may be useful for characterizing cardiac function in patients with pheochromocytoma. Second abstract. The semiquantitative analysis using the myocardial SUVmax in 123I-MIBG SPECT/CT was found to be potentially useful for characterizing cardiac function in patients with pheochromocytoma.

Since the inline positron emission tomography (PET)/magnetic resonance imaging (MRI) system appeared in clinical, more than a decade has passed. In this article, we have reviewed recently-published articles about PET/MRI. There have been articles about staging in rectal and breast cancers by PET/MRI using fluorodeoxyglucose (FDG) with higher diagnostic performance in oncology. Assessing possible metastatic bone lesions is considered a proper target by FDG PET/MRI. Other than FDG, PET/MRI with prostate specific membrane antigen (PSMA)-targeted tracers or fibroblast activation protein inhibitor have been reported. Especially, PSMA PET/MRI has been reported to be a promising tool for determining appropriate sites in biopsy. Independent of tracers, the clinical application of artificial intelligence (AI) for images obtained by PET/MRI is one of the current topics in this field, suggesting clinical usefulness for differentiating breast lesions or grading prostate cancer. In addition, AI has been reported to be helpful for noise reduction for reconstructing images, which would be promising for reducing radiation exposure. Furthermore, PET/MRI has a clinical role in neuroscience, including localization of the epileptogenic zone. PET/MRI with new PET tracers could be useful for differentiation among neurological disorders. Clinical applications of integrated PET/MRI in various fields are expected to be reported in the future.

PURPOSE To examine the usefulness of machine learning to predict prognosis in cervical cancer using clinical and radiomic features of 2-deoxy-2-[18F]fluoro-D-glucose (18F-FDG) positron emission tomography/computed tomography (CT) (18F-FDG-PET/CT). METHODS This retrospective study included 50 cervical cancer patients who underwent 18F-FDG-PET/CT before treatment. Four clinical (age, histology, stage, and treatment) and 41 18F-FDG-PET-based radiomic features were ranked and a subset of useful features for association with disease progression was selected based on decrease of the Gini impurity. Six machine learning algorithms (random forest, neural network, k-nearest neighbors, naive Bayes, logistic regression, and support vector machine) were compared using the areas under the receiver operating characteristic curve (AUC). Progression-free survival (PFS) was assessed using Cox regression analysis. RESULTS The five top predictors of disease progression were: stage, surface area, metabolic tumor volume, gray-level run length non-uniformity (GLRLM_RLNU), and gray-level non-uniformity for run (GLRLM_GLNU). The naive Bayes model was the best-performing classifier for predicting disease progression (AUC = 0.872, accuracy = 0.780, F1 score = 0.781, precision = 0.788, and recall = 0.780). In the naive Bayes model, 5-year PFS was significantly higher in predicted non-progression than predicted progression (80.1% vs. 9.1%, p

This study examined the usefulness of the maximum standardized uptake value (SUVmax) of myocardial [This study included 18 patients with pheochromocytoma who underwent both planar and [On visual analysis, 6 patients showed normal myocardial [LV diastolic dysfunction was inversely related to myocardial [

The prognostic value of treatment response in patients with non-small cell lung cancer (NSCLC) treated with immune-checkpoint inhibitors (ICIs) shown by 18F-fludeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) results obtained with multiple types of PET scanners using standardized uptake value (SUV) harmonization was evaluated. Fifty-eight patients treated with ICIs who underwent 18F-FDG PET/CT examinations with nine types of PET scanners at six hospitals were enrolled. SUV harmonization of multiple PET scanner results was performed using the dedicated software packages “RAVAT” and “RC Tool for Harmonization”. Tumor response was assessed by change in sum of harmonized SUVmax, according to the European Organization for Research and Treatment of Cancer (EORTC5) or the SUV of up to five lesions normalized to lean body mass, according to the PET Response Criteria in Solid Tumors (PERCIST5) and immunotherapy-modified PERCIST (imPERCIST5) criteria. The correlation between tumor response according to those three definitions and overall survival (OS) was evaluated and compared to known prognostic factors. One-year OS in responders and non-responders for harmonized EROTC5 was 86 and 32%, for harmonized PERCIST5 was 86 and 32%, and for harmonized imPERCIST5 was 80 and 30%, respectively (each p = 0.001). Univariate analysis showed that all response criteria remained as prognostic factors. However, there was an overlap for the categories stable metabolic disease (SMD) and progression metabolic disease (PMD) in survival curves using the PET treatment response criteria. In patients with NSCLC treated with ICIs, tumor response based on the harmonized response criteria was associated with OS. PET response criteria using harmonized metabolic parameters may be difficult to routinely employ in daily practice due to overlapping SMD and PMD, although may have a supporting role for determining prognosis.

Objective In malignant melanoma patients treated with immune checkpoint inhibitor (ICI) therapy, three different FDG-PET criteria, European Organization for Research and Treatment of Cancer (EORTC), PET Response Criteria in Solid Tumors (PERCIST), immunotherapy-modified PERCIST (imPERCIST), were compared regarding response evaluation and prognosis prediction using standardized uptake value (SUV) harmonization of results obtained with various PET/CT scanners installed at different centers. Materials and methods Malignant melanoma patients (n = 27) underwent FDG-PET/CT examinations before and again 3 to 9 months after therapy initiation (nivolumab, n = 21; pembrolizumab, n = 6) with different PET scanners at five hospitals. EORTC, PERCIST, and imPERCIST criteria were used to evaluate therapeutic response, then concordance of the results was assessed using Cohen’s κ coefficient. Log-rank and Cox methods were employed to determine progression-free (PFS) and overall (OS) survival. Results Complete metabolic response (CMR)/partial metabolic response (PMR)/stable metabolic disease (SMD)/progressive metabolic disease (PMD) with harmonized EORTC, PERCIST, and imPERCIST was seen in 3/5/4/15, 4/5/3/15, and 4/5/5/13 patients, respectively. Nearly perfect concordance between each pair of criteria was noted (κ = 0.939–0.972). Twenty patients showed progression and 14 died from malignant melanoma after a median 19.2 months. Responders (CMR/PMR) showed significantly longer PFS and OS than non-responders (SMD/PMD) (harmonized EORTC: p p = 0.011; harmonized PERCIST: p p = 0.0012; harmonized imPERCIST: p p = 0.0012, respectively). Conclusions All harmonized FDG-PET criteria (EORTC, PERCIST, imPERCIST) showed accuracy for response evaluation of ICI therapy and prediction of malignant melanoma patient prognosis. Additional studies to determine their value in larger study populations will be necessary.

I-131 radioiodine false-positive findings in postoperative patients with differentiated thyroid cancer (DTC) should be recognized to avoid unnecessary therapies.A 50-year-old man underwent I-131 therapy 3 times, including the initial ablative therapy after total thyroidectomy for papillary thyroid cancer. The initial I-131 posttherapeutic whole-body scintigraphy showed 2 cervical and one superior mediastinal focal I-131 positive uptake lesions. The serum thyroglobulin level was negative every time when the radioiodine therapy was performed. Although the 2 cervical positive uptake lesions disappeared after the second therapy, the superior mediastinal I-131 positive uptake persisted even after the third therapy, and this lesion was suspicion of I-131 therapy-resistant node metastasis.The lesion was resected, and the pathological diagnosis with immune-histochemical analysis was a thymic cyst with thymic epithelial cells having a weak expression of the sodium-iodide symporter (NIS).The false-positive result may be attributed to the NIS expression in the thymic cyst epithelial cells. It is necessary to include a thymic cyst in the differential diagnosis, when I-131 uptake is noted in the superior mediastinal region on I-131 posttherapeutic scans of patients with postoperative DTC. Although the I-131 positive uptake in a thymic cyst may be influenced by the I-131 administered dose and scan timing after I-131 administration, the NIS expression may be essential to the false-positive uptake in a thymic cyst.

Objective: To examine whether the machine-learning approach using 18-fludeoxyglucose positron emission tomography (18F-FDG-PET)-based radiomic and deep-learning features is useful for predicting the pathological risk subtypes of thymic epithelial tumors (TETs). Methods: This retrospective study included 79 TET [27 low-risk thymomas (types A, AB and B1), 31 high-risk thymomas (types B2 and B3) and 21 thymic carcinomas] patients who underwent pre-therapeutic 18F-FDG-PET/CT. High-risk TETs (high-risk thymomas and thymic carcinomas) were 52 patients. The 107 PET-based radiomic features, including SUV-related parameters [maximum SUV (SUVmax), metabolic tumor volume (MTV), and total lesion glycolysis (TLG)] and 1024 deep-learning features extracted from the convolutional neural network were used to predict the pathological risk subtypes of TETs using six different machine-learning algorithms. The area under the curves (AUCs) were calculated to compare the predictive performances. Results: SUV-related parameters yielded the following AUCs for predicting thymic carcinomas: SUVmax 0.713, MTV 0.442, and TLG 0.479 or high-risk TETs: SUVmax 0.673, MTV 0.533, and TLG 0.539. The best-performing algorithm was the logistic regression model for predicting thymic carcinomas (AUC 0.900, accuracy 81.0%), and the random forest (RF) model for high-risk TETs (AUC 0.744, accuracy 72.2%). The AUC was significantly higher in the logistic regression model than three SUV-related parameters for predicting thymic carcinomas, and in the RF model than MTV and TLG for predicting high-risk TETs (each; p < 0.05). Conclusion: 18F-FDG-PET-based radiomic analysis using a machine-learning approach may be useful for predicting the pathological risk subtypes of TETs. Advances in knowledge: Machine-learning approach using 18F-FDG-PET-based radiomic features has the potential to predict the pathological risk subtypes of TETs.

This study assessed the possibility of semi-automatic harmonization of standardized uptake values (SUVs) in multicenter studies. Phantom data were acquired using 16 PET/CT scanners (including 3 PET/CT scanners with a silicon photomultiplier detector). PET images obtained using 30-min/bed scans for optimum harmonization filter calculations and using 90–180-s/bed scans for SUV validation under clinical conditions were obtained. Time of flight and a reconstruction method with point-spread function correction were allowed. The optimal full width at half maximum of the 3D-Gaussian filter that minimizes the root mean square error with the median value of the JSNM harmonization range was calculated semi-automatically. The SUVmax and the SUVpeak of the hot spheres were measured, and the inter-scanner coefficient of variation (COV) was calculated before and after harmonization. The harmonization filter was applied to 11 of the 15 PET/CT scanners in which the SUV calibration accuracy had been verified, but not in the remaining 4 scanners. Under noiseless conditions before harmonization, the inter-scanner COVs of the SUVmax and the SUVpeak were as high as 21.57% and 12.20%, respectively, decreasing to 8.79% and 5.73% after harmonization, respectively. Harmonization brought the SUVmax of all the hot spheres to within the harmonization range. Even under clinical conditions affected by image noise, the inter-scanner COVs for the SUVmax and SUVpeak were as high as 8.83% and 5.18% after harmonization, respectively. By applying an optimal harmonization filter that is calculated semi-automatically, the harmonization of SUVs according to the JSNM strategy is possible in multicenter studies, thereby reducing inter-scanner COVs.

To examine the prognostic significance of pretreatment 2-deoxy-2-[18F]fluoro-d-glucose ([18F]-FDG) positron emission tomography (PET)-based radiomic features using a machine learning approach in patients with endometrial cancers. Included in this retrospective study were 53 patients with endometrial cancers who underwent [18F]-FDG PET/X-ray computed tomography (CT) before treatment. Since two different PET scanners were used, post-reconstruction harmonization was performed for all PET parameters using the ComBat harmonization method. Four clinical (age, histological type, stage, and treatment method) and 40 [18F]-FDG PET-based radiomic features were ranked, and a subset of useful features was selected based on the decrease in the Gini impurity in terms of associations with disease progression. The machine learning algorithms (random forest, neural network, k-nearest neighbors (kNN), naive Bayes, logistic regression, and support vector machine) were compared using the areas under the receiver operating characteristic curve (AUC) and validated by the random sampling method. Progression-free survival (PFS) and overall survival (OS) were assessed by the Cox regression analysis. The five best predictors of disease progression were coarseness, gray-level run length nonuniformity, stage, treatment method, and gray-level zone length nonuniformity. The kNN model obtained the best performance classifier for predicting the disease progression (AUC =0.890, accuracy =0.849, F1 score =0.848, precision =0.857, and recall =0.849). Coarseness which was the first ranked radiomic feature was selected for survival analyses, and only coarseness remained as a significant and independent factor for both PFS (hazard ratios (HR), 0.65; 95 % confidence interval [CI], 0.49–0.86; p=0.003) and OS (HR, 0.52; 95 % CI, 0.36–0.76; p

To examine whether the machine-learning approach using 18-fludeoxyglucose positron emission tomography (This retrospective study included 79 TET [27 low-risk thymomas (types A, AB and B1), 31 high-risk thymomas (types B2 and B3) and 21 thymic carcinomas] patients who underwent pre-therapeuticSUV-related parameters yielded the following AUCs for predicting thymic carcinomas: SUVmax 0.713, MTV 0.442, and TLG 0.479 or high-risk TETs: SUVmax 0.673, MTV 0.533, and TLG 0.539. The best-performing algorithm was the logistic regression model for predicting thymic carcinomas (AUC 0.900, accuracy 81.0%), and the random forest (RF) model for high-risk TETs (AUC 0.744, accuracy 72.2%). The AUC was significantly higher in the logistic regression model than three SUV-related parameters for predicting thymic carcinomas, and in the RF model than MTV and TLG for predicting high-risk TETs (each;Machine-learning approach using

This article was update to correct the spelling of Takashi Yoshiura's name; it is correct as displayed here.

OBJECTIVES The aim of the study was to evaluate PET response criteria in solid tumors (PERCIST) to indicate therapeutic response to definitive chemoradiotherapy, as well as prediction of recurrence and death in patients with esophageal cancer. METHODS Before and after recieving definitive chemoradiotherapy, 181 patients with esophageal cancer underwent fluorodeoxyglucose-PET/computed tomography (FDG-PET/CT). PERCIST, reduction rates of tumor uptake and volume of whole lesions, tumor node metastasis (TNM) staging regarding progression-free survival (PFS), and overall survival (OS) were analyzed using log-rank and Cox methods. RESULTS Complete metabolic response (CMR), partial metabolic response (PMR), stable metabolic disease (SMD), and progressive metabolic disease (PMD) shown by PERCIST were seen in 42 (23.2%), 113 (62.4%), 14 (7.7%), and 12 (6.6%) patients, respectively. Progression developed in 137 (75.7%) patients and 101 (56.1%) patients died (median follow-up 16.9, range 3.2-124.9 months). Those who achieved CMR showed significantly longer PFS and OS as compared with patients who did not (PMR, SMD, and PMD) (both P

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Granulocyte colony-stimulating factor (G-CSF)-producing tumors are malignant tumors associated with a poor prognosis, and G-CSF-producing liposarcoma is particularly rare. We report a case of G-CSF-producing dedifferentiated liposarcoma. 18F-FDG PET/CT showed abnormal 18F-FDG uptake throughout the bone marrow and in the primary site. When a diffuse bone marrow 18F-FDG uptake was observed on 18F-FDG PET/CT, G-CSF-producing dedifferentiated liposarcoma should be included in the differential diagnosis.

To examine whether the texture analysis of dual-time-point (DTP) F-18-fluorodeoxyglucose (18F-FDG)-PET/CT imaging can differentiate between 18F-FDG-avid benign and malignant pulmonary lesions. We compared standardized uptake value (SUV)-related (SUVmax [g/ml] and SUVmean [g/ml]), volumetric (metabolic tumor volume [MTV] [cm3] and total lesion glycolysis [TLG] [g]), and texture (entropy, homogeneity, dissimilarity, intensity variability [IV], size-zone variability [SZV], and zone percentage [ZP]) (MTV ≥ 5.0 cm3 and SUV ≥ 2.5 g/ml) parameters between 13 benign and 46 malignant lesions using the Mann–Whitney U test. Diagnostic performance was evaluated by receiver operating characteristic (ROC) analysis. Stepwise logistic regression analysis was performed to identify and use the independent variables that correctly differentiate between benign and malignant lesions. Malignant pulmonary lesions showed significantly higher SUVmax, SUVmean, MTV, TLG, entropy, dissimilarity, IV, and SZV and significantly lower homogeneity and ZP than benign pulmonary lesions (all p < 0.05) in both early and delayed images. Their areas under the ROC curves (AUCs) ranged between 0.69 and 0.94, and diagnostic accuracies between 64.4% and 93.2%. Entropy-early (p = 0.014), SUVmean-delay (p = 0.039), and dissimilarity-delay (p = 0.027) were independent parameters, and combined use of them yielded the highest AUC (0.98) with 100% sensitivity (46/46), 84.6% specificity (11/13), and 96.7% (57/59) accuracy for distinguishing between benign and malignant lesions. The individual early and delayed SUV-related, volumetric, and texture parameters showed a wide range of accuracy. Combined use of independent parameters extracted from DTP imaging might yield a high diagnostic accuracy with balanced sensitivity and specificity to differentiate between benign and malignant 18F-FDG-avid pulmonary lesions. • Malignant pulmonary lesions showed significantly higher SUV-related (SUVmax and SUVmean) and volumetric (MTV and TLG) parameters than benign pulmonary lesions in both early and delayed images. • Malignant pulmonary lesions showed significantly more heterogeneous 18 F-FDG uptake than benign pulmonary lesions in both early and delayed images. • Combined use of independent parameters extracted from DTP imaging might yield a high diagnostic accuracy to differentiate between benign and malignant 18 F-FDG-avid pulmonary lesions.

Objective This study aimed to determine whether extracellular volume (ECV) fraction with routine equilibrium contrast-enhanced computed tomography (CT) can predict outcomes in patients with stage IV pancreatic ductal adenocarcinoma (PDAC) treated with chemotherapy. Methods This is a retrospective cohort study of 128 patients with stage IV PDAC who underwent multiphasic pancreatic CT before systemic chemotherapy. Contrast enhancement and ECV fraction of the primary lesion were calculated using region-of-interest measurement within the PDAC and aorta on unenhanced and equilibrium phase-enhanced CT. The effects of clinical prognostic factors and ECV fractions on progression-free survival (PFS) and overall survival (OS) were assessed by univariate and multivariate analyses using Cox proportional hazards models. Results The number of metastatic organs and tumor ECV fraction were significant for PFS (P = 0.005 and 0.001, respectively) and OS (P = 0.012 and 0.007, respectively). On the multivariate analysis, multiple metastatic organs (PFS, P = 0.046; OS, P = 0.047) and lower tumor ECV fraction (PFS, P = 0.010; OS, P = 0.026) were identified as independent predictors of poor PFS and OS. Conclusion Extracellular volume fraction with routine equilibrium contrast-enhanced CT may potentially predict survival in patients with stage IV PDAC treated with chemotherapy.

To examine the usefulness of machine learning to predict prognosis in cervical cancer using clinical and radiomic features of 2-deoxy-2-[This retrospective study included 50 cervical cancer patients who underwentThe five top predictors of disease progression were: stage, surface area, metabolic tumor volume, gray-level run length non-uniformity (GLRLM_RLNU), and gray-level non-uniformity for run (GLRLM_GLNU). The naive Bayes model was the best-performing classifier for predicting disease progression (AUC = 0.872, accuracy = 0.780, F1 score = 0.781, precision = 0.788, and recall = 0.780). In the naive Bayes model, 5-year PFS was significantly higher in predicted non-progression than predicted progression (80.1% vs. 9.1%, p 0.001) and was only the independent factor for PFS in multivariate analysis (HR, 6.89; 95% CI, 1.92-24.69; p = 0.003).A machine learning approach based on clinical and pretreatment

To examine the prognostic significance of pretreatment 2-deoxy-2-[Included in this retrospective study were 53 patients with endometrial cancers who underwent [The five best predictors of disease progression were coarseness, gray-level run length nonuniformity, stage, treatment method, and gray-level zone length nonuniformity. The kNN model obtained the best performance classifier for predicting the disease progression (AUC =0.890, accuracy =0.849, F1 score =0.848, precision =0.857, and recall =0.849). Coarseness which was the first ranked radiomic feature was selected for survival analyses, and only coarseness remained as a significant and independent factor for both PFS (hazard ratios (HR), 0.65; 95 % confidence interval [CI], 0.49-0.86; p=0.003) and OS (HR, 0.52; 95 % CI, 0.36-0.76; p0.001) at multivariate Cox regression analysis.[

To assess the utility of a machine-learning approach for predicting liver function based on technetium-99 m-galactosyl serum albumin (One hundred twenty-eight patients underwent aFour indices (LHL15, HH15, heart SUVmax and SUVmax ratio) yielded high areas under the ROC curves (AUCs) for predicting high liver damage (range: 0.89-0.93). In a machine learning classification, the RF with selected features (heart SUVmax, SUVmax ratio, LHL15, HH15, and background liver disease) and PCA model yielded the best performance for predicting high liver damage (AUC = 0.956, sensitivity = 96.3%, specificity = 90.0%, accuracy = 91.4%).A machine-learning approach based on clinical and quantitative

Background: Cardiac sarcoidosis (CS) has a poor prognosis because of frequent complication of atrioventricular block, ventricular tachycardia and congestive heart failure. Qualitative or quantitative 18F-FDG PET/CT has been used for diagnosing or assessing the disease activity of CS. However, the association between 18F-FDG myocardial uptake and clinical presentations in CS has not yet been clarified, and it is unknown if Patlak Ki images (Ki images) extracted from dynamic 18F-FDG-PET/CT are useful for evaluating the disease activity or clinical events in CS patients. In this context, this study was performed to investigate the usefulness of SUV and Patlak Ki images extracted from dynamic 18F-FDG-PET/CT for evaluating the risk of severe clinical events (SCEs) in CS. Methods: The SUV and Ki myocardial images were generated from 30 dynamic 18F-FDG-PET/CT scans of 21 CS patients including those with cardiac dysfunction and arrhythmic events. SUV parameters and Ki parameters (Ki max, Ki mean, Ki volume) were measured for positive myocardial lesions. The Mann–Whitney U-test or Fisher’s exact test was used appropriately to assess differences between quantitative variables or compare categorical data. The association between each quantitative parameter and presence of SCEs was analyzed by logistic regression analysis.Results: The SUV and Ki mages both were rated as positive in 19 scans and negative in 11 scans with the same incidence of SCEs which were significantly higher in positive than negative scans [cardiac dysfunction: 78.9% (15/19) vs. 27.2% (3/11), p=0.009; arrhythmic events: 65.5% (10/19) vs. 0% (0/11), p=0.004]. In 19 positive scans, neither SUV nor Ki parameters were significantly different between scans of patients with cardiac dysfunction (n=15) and those without (n=4) (p>0.05, each), whereas the three Ki parameters were significantly higher in scans for patients with arrhythmic events (n=10) than in those without (n=9) (pp=0.047).Conclusion: Patlak Ki images may add value to SUV images for evaluating the risk of SCEs in CS patients.

The association between 18F-fluorodeoxyglucose (18F-FDG) myocardial uptake and clinical presentations in cardiac sarcoidosis (CS) has not yet been clarified. The Patlak slope, Ki, which represents the rate of 18F-FDG uptake is a quantitative index of 18F-FDG metabolism. This study aims to investigate the usefulness of standardized uptake value (SUV) and Patlak Ki images (Ki images) extracted from dynamic 18F-FDG-PET/CT for evaluating the risk of clinical events (CEs) in CS. The SUV and Ki myocardial images were generated from 30 dynamic 18F-FDG-PET/CT scans of 21 CS patients. The SUV and Ki images both were rated as positive in 19 scans and negative in 11 scans with the same incidence of CEs which were significantly higher in positive than negative scans [cardiac dysfunction: 78.9% (15/19) vs. 27.2% (3/11); arrhythmic events: 65.5% (10/19) vs. 0% (0/11)]. In 19 positive scans, the three Ki parameters (Ki max, Ki mean and Ki volume) were significantly higher in scans for patients with arrhythmic events than in those without. Logistic regression analysis showed that the Ki volume alone was significantly associated with the risk of arrhythmic events. Our study suggests that Ki images may add value to SUV images for evaluating the risk of CEs in CS patients.

To evaluate the maximum standardized uptake value (SUVmax) byTen patients underwent NP-59 SPECT/CT to evaluate the following unilateral adrenocortical hyperfuncting masses: three with Cushing's syndrome (CS), three with subclinical CS, and four with primary aldosteronism (PA). Visual and quantitative or semiquantitative analyses (noncontrast CT HU [Hounsfield units], lesion SUVmax, contralateral SUVmax, and SUVmax ratio [lesion SUVmax/contralateral adrenal SUVmax]) were performed. The Mann-Whitney U test or Chi-squared test was used appropriately to assess differences between quantitative variables or compare categorical data. Diagnostic performance was evaluated by receiver operating characteristic (ROC) curve analysis.All adrenal tumors were diagnosed as cortical adenomas. On visual analysis, unilateral uptake was noted in three patients with CS and one patient with subclinical CS, whereas bilateral uptake was noted in four patients with PA and two patients with subclinical CS (p = 0.046). No significant difference was observed in CT HU (p = 0.055). The lesion SUVmax and SUVmax ratio were significantly higher and the contralateral SUVmax was significantly lower in six patients with CS than in four patients with PA (each, p 0.05). The area under the ROC curve and accuracy for differentiating between CS and PA were, respectively, 0.92 and 90.0 % for the lesion SUVmax, 1.00 and 100 % for the contralateral SUVmax, and 0.92 and 90.0 % for the SUVmax ratio.Quantitative or semiquantitative analysis using the adrenal SUVmax in adrenocortical NP-59 SPECT/CT has potential for characterizing unilateral hyperfunctioning adrenocortical masses.

To examine whether the heterogeneous texture parameters in primary tumor can predict prognosis of patients with non-small cell lung cancer (NSCLC) received surgery after 2-deoxy-2-[18F]fluoro-D-glucose ([18F]FDG) positron emission tomography (PET)/X-ray computed tomography (CT). This retrospective study included 55 patients with NSCLC who underwent [18F]FDG-PET/CT before surgery from January 2011 and December 2015. SUV-related (SUVmax and SUVmean), volumetric (metabolic tumor volume [SUV ≥ 2.5], and total lesion glycolysis) and texture parameters (local parameters; entropy, homogeneity, and dissimilarity and regional parameters; intensity variability [IV], size-zone variability [SZV], and zone percentage [ZP]) were obtained. Tumor size, TNM stage, SUV-related, volumetric, and texture parameters were compared between the patients with progression and without progression using Mann-Whitney’s U or χ2 test and progression-free survival (PFS) and prognostic significance were assessed by Kaplan-Meier method and Cox regression analysis, respectively. Nineteen patients eventually showed progression, and 36 patients were alive without progression during clinical follow-up (median follow-up PFS; 23 months [range, 1–71]). The patients with progression showed significantly larger tumor size (p

Advanced imaging techniques may enable early diagnosis and monitoring of therapy in various rheumatic diseases. To prevent irreversible tissue damage, inflammatory rheumatic disease must be diagnosed and treated in preclinical stages, requiring highly sensitive detection techniques. PET provides highly sensitive, quantitative imaging at a molecular level, revealing the important pathophysiological processes underlying inflammation. This section provides an overview of the current utility of FDG-PET/CT in patients with active rheumatic diseases such as rheumatoid arthritis (RA), polymyalgia rheumatica (PMR), spondyloarthritis (SpA), relapsing polychondritis (RPC), adult-onset Still’s disease (AOSD), large vessel vasculitis (LVV), immunoglobulin G4-related disease (IgG4-RD), polymyositis/dermatomyositis (PM/DM), and Granulomatosis with polyangitis (GPA). We also discuss the role of FDG-PET/CT in the diagnosis and monitoring of these diseases.

The purpose of this study was to evaluate therapeutic response to neoadjuvant chemotherapy (NAC) and predict breast cancer recurrence using Positron Emission Tomography Response Criteria in Solid Tumors (PERCIST). Fifty-nine breast cancer patients underwent fluorodeoxyglucose-positron emission tomography/computed tomography (FDG-PET/CT) before and after NAC prior to planned surgical resection. Pathological complete response (pCR) of the primary tumor was evaluated using PERCIST, while effects of clinicopathological factors on progression-free survival (PFS) were examined using log-rank and Cox methods. Fifty-six patients and 54 primary tumors were evaluated. Complete metabolic response (CMR), partial metabolic response, stable metabolic disease, and progressive metabolic disease were seen in 45, 7, 3, and 1 patients, respectively, and 43, 7, 3, and 1 primary tumors, respectively. Eighteen (33.3%) of the 54 primary tumors showed pCR. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy of PERCIST to predict pCR were 100% (18/18), 30.6% (11/36), 41.9% (18/43), 100% (11/11), and 53.7% (29/54), respectively. An optimal percent decrease in peak standardized uptake value for a primary tumor corrected for lean body mass (SULpeak) of 84.3% was found to have a sensitivity of 77.8% (14/18), specificity of 77.8% (28/36), PPV of 63.6% (14/22), NPV of 87.5% (28/32), and accuracy of 77.8% (42/54). Seven (12.5%) of the 56 patients developed recurrent disease (median follow-up 28.1 months, range 11.4–96.4 months). CMR (p = 0.031), pCR (p = 0.024), and early TNM stage (p = 0.033) were significantly associated with longer PFS. PERCIST is useful for predicting pathological response and prognosis following NAC in breast cancer patients. However, FDG-PET/CT showed a tendency toward underestimation of the residual tumor, and relatively low specificity and PPV of PERCIST showed that a combination of other imaging modalities would still be needed to predict pCR.

According to recent studies, lung uptake of iodine-123-metaiodobenzylguanidine (123I-MIBG) is impaired in many lung diseases and low lung uptake of 123I-MIBG suggests endothelial dysfunction of the pulmonary artery. 123I-MIBG scintigraphy in patients with pulmonary hypertension (PH) has not yet been clinically evaluated. We hypothesized that the lung uptake of 123I-MIBG is reduced in patients with PH and differs among PH subtypes. The purpose of the present study was to analyze the lung uptake of 123I-MIBG in patients with PH and compare it with the data obtained by echocardiography or right heart catheterization. 123I-MIBG scintigraphy was performed in 286 consecutive patients from 2003 to 2014. We enrolled 21 patients with PH and 8 control patients. The 21 patients with PH were categorized into those with pulmonary artery hypertension (PAH, n = 12) and those with chronic thromboembolic pulmonary hypertension (CTEPH, n = 9). The mean pulmonary artery pressure was not significantly different between patients with CTEPH and PAH (37.7 ± 6.8 versus 32.3 ± 5.3 mmHg respectively; P = 0.054). There were no significant differences in any other hemodynamic parameters between the two groups. The lung uptake of 123I-MIBG in PAH patients (early image: 1.54 ± 0.18, delayed image: 1.41 ± 0.16) was significantly lower than that of CTEPH patients (early image: 2.17 ± 0.25, P < 0.0001; delayed image: 1.99 ± 0.20, P = 0.0001, adjusted for age and World Health Organization classification) and controls (early image: 2.32 ± 0.27, P = 0.0007; delayed image: 1.92 ± 0.19, P = 0.0007). In conclusion, we found for the first time that the lung uptake of 123I-MIBG in patients with PAH is lower than that in patients with CTEPH and controls.

This retrospective study was done to examine whether the heterogeneity in primary tumor F-18-fluorodeoxyglucose (18F-FDG) and 18F-3′-fluoro-3′-deoxythymidine (18F-FLT) distribution can predict prognosis of patients with colorectal cancer who received surgery. The enrolled 32 patients with colorectal cancer underwent both 18F-FDG- and 18F-FLT-PET/CT studies before surgery. Clinicopathological factors, stage, SUVmax, SUVmean, metabolic tumor volume (SUV ≥ 2.5), total lesion glycolysis, total lesion proliferation and seven texture heterogeneity parameters (coefficient of variation, local parameters: entropy, homogeneity, and dissimilarity; and regional parameters: intensity variability [IV], size-zone variability [SZV], and zone percentage [ZP]) were obtained. Progression free survival (PFS) was calculated by the Kaplan-Meier method. Prognostic significance was assessed by Cox proportional hazards analysis. Eight patients had eventually come to progression, and 24 patients were alive without progression during clinical follow-up [mean follow-up PFS; 55.9 months (range, 1-72)]. High stage (p = 0.004), high 18F-FDG-IV (p = 0.015), high 18F-FDG-SZV (p = 0.013) and high 18F-FLT-entropy (p = 0.015) were significant in predicting poor 5-year PFS. Other parameters did not predict the disease outcome. At bivariate analysis, disease event hazards ratios for 18F-FDG-IV and 18F-FDG-SZV remained significant when adjusted for stage and 18F-FLT-entropy (18F-FDG-IV; p = 0.004 [adjusted for stage], 0.007 [adjusted for 18F-FLT-entropy]; 18F-FDG-SZV; p = 0.028 [adjusted for stage], 0.040 [adjusted for 18F-FLT-entropy]). 18F-FDG PET heterogeneity parameters, IV and SZV, have a potential to be strong prognostic factors to predict PFS of patients with surgically resected colorectal cancer and are more useful than 18F-FLT-PET/CT heterogeneity parameters.

To retrospectively investigate the SUV-related and texture parameters individually and in combination for differentiating between F-18-fluorodeoxyglucose (FDG)-avid benign and metastatic adrenal tumors with PET/CT. Thirteen benign adrenal tumors (BATs) and 22 metastatic adrenal tumors (MATs) with a metabolic tumor volume (MTV) > 10.0 cm3 and SUV ≥ 2.5 were included. SUVmax, MTV, total lesion glycolysis, and four textural parameters [entropy, homogeneity, intensity variability (IV), and size-zone variability] were obtained. These parameters were compared between BATs and MATs using Mann–Whitney U test, and the diagnostic performance was evaluated by the area under the curve (AUC) values derived from the receiver operating characteristic analysis. The diagnostic value of combining SUV and texture parameters was examined using a scoring system. MATs showed significantly higher SUVmax (p = 0.004), entropy (p = 0.013), IV (p = 0.006), and lower homogeneity (p = 0.019) than BATs. The accuracies for diagnosing MATs were 82.9, 82.9, 85.7, and 71.4% for SUVmax, entropy, IV, and homogeneity, respectively. No significant differences in AUC were found among these parameters (p > 0.05 each). When each parameter was scored as 0 (negative for malignancy) and 1 (positive for malignancy) according to each threshold criterion and the four parameter summed scores 0, 1, and 2 were defined as benignity and 3 and 4 as malignancy, the sensitivity and specificity and accuracy to predict MATs were 100% (22/22), 84.6% (11/13), and 94.3% (33/35), respectively, with 0.97 of the AUC. The combined use of SUVmax and texture parameters has a potential to significantly increase the diagnostic performance to differentiate between large FDG-avid BATs and MATs.

To evaluate the feasibility of equilibrium contrast-enhanced dual-energy CT (DECT), as compared with single-energy CT (SECT) and to calculate extracellular volume (ECV) fraction to predict the survival outcomes of pancreatic ductal adenocarcinoma (PDAC) patients with distant metastases (stage IV) treated with chemotherapy. The study cohort included a total of 66 patients with stage IV PDAC who underwent DECT before systemic chemotherapy between July 2014 and March 2017. Unenhanced and 120-kVp equivalent images during the equilibrium phase were used to calculate tumor SECT-derived ECV fractions, and iodine density images were obtained from equilibrium-phase DECT for DECT-derived ECV fractions. Correlations between SECT- and DECT-derived ECV fractions were identified using the Pearson correlation coefficient and Bland–Altman analysis. The effects of clinical prognostic factors and tumor SECT- and DECT-derived ECV fractions on progression-free survival (PFS) and overall survival (OS) were assessed by univariate and multivariate analyses using Cox proportional hazards models. The correlation between SECT- and DECT-derived ECV fractions was strong (r = 0.965; p < 0.001). The Bland–Altman plot between SECT- and DECT-derived ECV fractions showed a small bias (− 3.4%). Increasing tumor SECT- and DECT-derived ECV fractions were associated with a positive effect on PFS (SECT, p = 0.002; DECT, p = 0.007) and OS (DECT, p = 0.014; DECT, p = 0.015). Only tumor DECT-derived ECV fraction was an independent predictor of PFS (p = 0.018) and OS (p = 0.022) in patients with stage IV PDAC treated with chemotherapy on multivariate analysis. The ECV fraction determined by equilibrium contrast-enhanced DECT can potentially predict the survival of patients with stage IV PDAC treated with chemotherapy. • Extracellular volume fraction of stage IV pancreatic ductal adenocarcinoma determined by dual-energy CT was strongly correlated to that with single-energy CT (r = 0.965, p < 0.001). • Tumor extracellular volume fraction was an independent predictor of progression-free survival (p = 0.018) and overall survival (p = 0.022). • Extracellular volume fraction determined by dual-energy CT could be a useful imaging biomarker to predict the survival of patients with stage IV pancreatic ductal adenocarcinoma treated with chemotherapy.

To examine whether the texture analysis of dual-time-point (DTP) F-18-fluorodeoxyglucose (We compared standardized uptake value (SUV)-related (SUVmax [g/ml] and SUVmean [g/ml]), volumetric (metabolic tumor volume [MTV] [cmMalignant pulmonary lesions showed significantly higher SUVmax, SUVmean, MTV, TLG, entropy, dissimilarity, IV, and SZV and significantly lower homogeneity and ZP than benign pulmonary lesions (all p0.05) in both early and delayed images. Their areas under the ROC curves (AUCs) ranged between 0.69 and 0.94, and diagnostic accuracies between 64.4% and 93.2%. Entropy-early (p = 0.014), SUVmean-delay (p = 0.039), and dissimilarity-delay (p = 0.027) were independent parameters, and combined use of them yielded the highest AUC (0.98) with 100% sensitivity (46/46), 84.6% specificity (11/13), and 96.7% (57/59) accuracy for distinguishing between benign and malignant lesions.The individual early and delayed SUV-related, volumetric, and texture parameters showed a wide range of accuracy. Combined use of independent parameters extracted from DTP imaging might yield a high diagnostic accuracy with balanced sensitivity and specificity to differentiate between benign and malignant• Malignant pulmonary lesions showed significantly higher SUV-related (SUVmax and SUVmean) and volumetric (MTV and TLG) parameters than benign pulmonary lesions in both early and delayed images. • Malignant pulmonary lesions showed significantly more heterogeneous

The purpose of this case series was to describe computed tomography (CT) and magnetic resonance imaging (MRI) features of undifferentiated carcinoma with osteoclast-like giant cells of the pancreas. Institutional ethics review board approval was obtained, and informed consent was waived for this case series. We reviewed CT and MRI of patients with pathologically confirmed undifferentiated carcinoma with osteoclast-like giant cells of the pancreas found in the medical records of our hospital between 2006 and 2016. Seven patients (3 males and 4 females; age, 59–82 years (mean, 71)) with confirmation by surgical resection (n = 3) or biopsy (n = 4) were identified. They underwent CT (n = 7) and MRI (n = 6). The tumors 26–83 mm in diameter (mean, 44 mm) were located in the head (n = 4) or body (n = 3) of the pancreas. They were demonstrated as lower attenuation areas relative to the adjacent pancreas on CT images obtained in both pancreatic and portal vein phases (n = 7) with a well-defined smooth margin (n = 5). They were demonstrated as hypointense areas relative to the pancreas on T2-weighted images (n = 4) and T2*-weighted images (n = 4) and diffusion-weighted images (n = 3). They contained hemosiderin deposits on histology (n = 7). Undifferentiated carcinoma with osteoclast-like giant cells of the pancreas might be present as low attenuation areas with a well-defined smooth margin on CT images obtained in pancreatic and portal vein phases, and hypointense areas on T2-, T2*-, and diffusion-weighted images caused by hemosiderin deposits.

Recent breakthrough results from immune checkpoint inhibitors (ICIs) have paved the way to a new era of cancer immunotherapy, and have thus led to a paradigm shift of cancer treatment. In particular, inhibition of the antiprogrammed death-1 (PD-1)/programmed death-ligand 1 (PD-L1) axis with ICI, including nivolumab and pembrolizumab, has been emerging as a novel treatment strategy for advanced gastric cancers. An accurate noninvasive assessment of the response to ICI is important for the management of patients with advanced or metastatic gastric cancer. To examine whether the European Organization for Research and Treatment of Cancer (EORTC) and PET Response Criteria in Solid Tumors (PERCIST) are valuable for predicting progression-free survival (PFS) in patients with advanced or metastatic gastric cancers treated with nivolumab. Six patients with advanced or metastatic gastric cancers who underwent 18F-FDG-PET/computed tomography (CT) scans before, and from 2 to 6 months after initiation of nivolumab therapy between September 2017 and August 2019, were evaluated retrospectively. The correlation between tumor progression and EORTC or PERCIST was assessed with the Fisher's exact test. The PFS was assessed with the Kaplan–Meier method. Two patients were alive without progression, and the remaining 4 patients exhibited tumor progression. Two patients without progression were classified as partial metabolic response (PMR) patients based on EORTC or PERCIST, while the other 4 patients with progression were classified as progressive metabolic disease (PMD) patients based on EORTC (P = .067), or stable metabolic disease (SMD) patients, or PMD patients based on PERCIST (P = .067). The mean and median PFS of all patients was 12.7 months (95% confidence interval [CI], 4.9–20.4 months) and 5 months (95%CI, 4.0–11.0 months). Two EORTC or PERCIST PMR patients showed significantly longer median PFS compared with 4 non-PMR patients (not reached vs 4.0 months, P = .044). Three PERCIST PMR or SMD patients also showed significantly longer median PFS compared with 3 PMD patients (not reached vs 4.0 months, P = .022). These results suggest that EORTC or PERCIST has the potential to predict PFS of patients with advanced or metastatic gastric cancers treated by nivolumab and further studies are needed to determine its value in larger study populations.

Purpose To evaluate the maximum standardized uptake value (SUVmax) by 131I-6β-iodomethyl-19-norcholesterol (NP-59) single-photon emission computed tomography (SPECT)/computed tomography (CT) for characterizing unilateral hyperfunctioning adrenocortical masses. Methods Ten patients underwent NP-59 SPECT/CT to evaluate the following unilateral adrenocortical hyperfuncting masses: three with Cushing’s syndrome (CS), three with subclinical CS, and four with primary aldosteronism (PA). Visual and quantitative or semiquantitative analyses (noncontrast CT HU [Hounsfield units], lesion SUVmax, contralateral SUVmax, and SUVmax ratio [lesion SUVmax/contralateral adrenal SUVmax]) were performed. The Mann–Whitney U test or Chi-squared test was used appropriately to assess differences between quantitative variables or compare categorical data. Diagnostic performance was evaluated by receiver operating characteristic (ROC) curve analysis. Results All adrenal tumors were diagnosed as cortical adenomas. On visual analysis, unilateral uptake was noted in three patients with CS and one patient with subclinical CS, whereas bilateral uptake was noted in four patients with PA and two patients with subclinical CS (p = 0.046). No significant difference was observed in CT HU (p = 0.055). The lesion SUVmax and SUVmax ratio were significantly higher and the contralateral SUVmax was significantly lower in six patients with CS than in four patients with PA (each, p Conclusions Quantitative or semiquantitative analysis using the adrenal SUVmax in adrenocortical NP-59 SPECT/CT has potential for characterizing unilateral hyperfunctioning adrenocortical masses.

The purpose of the study was to examine the diagnostic and prognostic values of 18F-fluorothymidine (FLT)-PET/CT for pancreatic cancer by comparing with 18F-fluorodeoxyglucose (FDG)-PET/CT. Fifteen patients with newly diagnosed pancreatic cancer underwent both FLT and FDG-PET/CT scans before treatment. The sensitivity, specificity, and accuracy in detecting nodal and distant metastases were compared between both scans using McNemar exact or χ 2 test. Progression-free survival (PFS) and overall survival (OS) were calculated by Kaplan–Meier method. Prognostic significance was assessed by Cox proportional hazards analysis. Both scans visualized all primary cancers. The sensitivity, specificity, and accuracy per patient basis for detecting nodal metastasis were equal and 63.6% (7/11), 100% (4/4), and 73.3% (11/15) for both scans, and for detecting distant metastasis were 100% (6/6), 88.9% (8/9), and 93.3% (14/15) for FDG-PET/CT, and 50.0% (3/6), 100% (9/9), and 80.0% (12/15) for FLT-PET/CT, respectively, without significant difference in each of them between both scans (p > 0.05). However, of 4 patients with multiple liver metastases, FDG-PET/CT was positive in all, but FLT-PET/CT was negative in three patients. At univariate analysis, only FLT-SUVmax correlated with PFS (hazard ratio, 1.306, p = 0.048), and FDG total lesion glycolysis (TLG), FLT-SUVmax, and FLT-total lesion proliferation (TLP) correlated with OS (p = 0.021, p = 0.005, and p = 0.022, respectively). At bivariate analysis, FLT-SUVmax was superior to FDG-TLG or FLT-TLP for prediction of OS [HR (adjusted for FDG-TLG), 1.491, p = 0.034, HR (adjusted for FLT-TLP), 1.542, p = 0.023]. FLT-PET/CT may have a potential equivalent to FDG-PET/CT for detecting primary and metastatic cancers except liver metastasis. FLT-SUVmax can provide the most significant prognostic information.

Positron emission tomography (PET) or PET/computed tomography (CT) using 18F-3'-fluoro-3'-deoxythymidine (18F-FLT) offers noninvasive assessment of cell proliferation in human cancers in vivo. The present review discusses the current status on clinical applications of 18F-FLT-PET (or PET/CT) in digestive and abdominal oncology by comparing with 18F-fluorodeoxyglucose (18F-FDG)-PET (or PET/CT). The results of this review show that although 18F-FLT uptake is lower in most cases of digestive and abdominal malignancies compared with 18F-FDG uptake, 18F-FLT-PET can be used to detect primary tumors. 18F-FLT-PET has shown greater specificity for N staging than 18F-FDG-PET which can show false-positive uptake in areas of inflammation. However, because of the high background uptake in the liver and bone marrow, it has a limited role of assessing liver and bone metastases. Instead, 18F-FLT-PET will be a powerful tool for monitoring response to treatment and provide prognostic information in digestive and abdominal oncology.

This retrospective study was done to examine whether the heterogeneity in primary tumour F-18-fluorodeoxyglucose (18F-FDG) distribution can predict tumour response and prognosis of patients with esophageal cancer treated by chemoradiotherapy (CRT). The enrolled 52 patients with esophageal cancer underwent 18F-FDG-PET/CT studies before CRT. SUVmax, SUVmean, metabolic tumour volume (MTV, SUV ≥ 2.5), total lesion glycolysis (TLG) and six heterogeneity parameters assessed by texture analysis were obtained. Patients were classified as responders or non-responders according to Response Evaluation Criteria in Solid Tumors. Progression-free survival (PFS) and overall survival (OS) were calculated by the Kaplan–Meier method. Prognostic significance was assessed by Cox proportional hazards analysis. Thirty four non-responders showed significantly higher MTV (p = 0.006), TLG (p = 0.007), intensity variability (IV; p = 0.003) and size-zone variability (SZV; p = 0.004) than 18 responders. The positive and negative predictive values for non-responders were 77 % and 69 % in MTV, 76 % and 100 % in TLG, 78 % and 67 % in IV and 78 % and 82 % in SZV, respectively. Although PFS and OS were significantly shorter in patients with high MTV (PFS, p = 0.018; OS, p = 0.014), TLG (PFS, p = 0.009; OS, p = 0.025), IV (PFS, p = 0.013; OS, p = 0.007) and SZV (PFS, p = 0.010; OS, p = 0.007) at univariate analysis, none of them was an independent factor, while lymph node status, stage and tumour response status were independent factors at multivariate analysis. Texture features IV and SZV, and volumetric parameters MTV and TLG can predict tumour response, but all of them have limited value in prediction of prognosis of patients with esophageal cancer treated by CRT.

Purpose To determine the diagnostic performance of apparent diffusion coefficient (ADC) histogram analysis in diffusion-weighted (DW) magnetic resonance imaging (MRI) for differentiating adrenal adenoma from pheochromocytoma. Materials and Methods We retrospectively evaluated 52 adrenal tumors (39 adenomas and 13 pheochromocytomas) in 47 patients (21 men, 26 women; mean age, 59.3 years; range, 16–86 years) who underwent DW 3.0T MRI. Histogram parameters of ADC (b-values of 0 and 200 [ADC200], 0 and 400 [ADC400], and 0 and 800 s/mm2 [ADC800])—mean, variance, coefficient of variation (CV), kurtosis, skewness, and entropy—were compared between adrenal adenomas and pheochromocytomas, using the Mann–Whitney U-test. Receiver operating characteristic (ROC) curves for the histogram parameters were generated to differentiate adrenal adenomas from pheochromocytomas. Sensitivity and specificity were calculated by using a threshold criterion that would maximize the average of sensitivity and specificity. Results Variance and CV of ADC800 were significantly higher in pheochromocytomas than in adrenal adenomas (P

As an orphan malignancy, only limited treatment options are available in adrenocortical carcinoma (ACC). Non-invasive risk assessment has not been described but may be of value to stratify patients for treatment. We aimed to evaluate the potential value of intra-individual tumor heterogeneity as assessed by (18)F-fluorodeoxyglucose ((18)F-FDG) positron emission tomography/computed tomography (PET/CT) for outcome prediction in treatment-naïve ACC patients. Ten patients with primary diagnosis of ACC were included in this study. Prior to any treatment initiation, baseline (18)F-FDG PET scans were performed. Tumor staging was performed using the European Network for the Study of Adrenal Tumors (ENS@T). Intratumoral heterogeneity of the primary tumor was assessed by manual segmentation using conventional PET parameters (standardized uptake values and tumor-to-liver ratios) and textural features. The impact of tumoral heterogeneity based on pre-therapeutic (18)F-FDG PET to predict progression-free (PFS) and overall survival (OS) was evaluated by receiver operating characteristic analysis. On average, tumor recurrence or progression was detected after median of 561 days (range 71-1434 days) after the pre-therapeutic baseline PET scan. 50 % of the patients died of ACC within the follow-up period (mean 983 ± 404 days). Pre-therapeutic tumor volume was associated with PFS (r = -0.67, p = 0.05) and Ki67 index with OS (r = -0.66, p = 0.04). ENS@T tumor stage was the only parameter to correlate with both PFS and OS (r = -0.82, p = 0.001, and r = -0.72, p = 0.01, respectively). In the subgroup of patients without distant metastases (ENS@T stages II and III), age and pre-therapeutic tumor volume correlated significantly with PFS (r = 0.96, p = 0.01 and r = -0.93, p = 0.02, respectively) and OS (r = 0.95, p = 0.02 and r = -0.90, p = 0.04, respectively). None of the investigated classic or textural PET parameters predicted PFS or OS. In this pilot study in treatment-naïve ACC patients, conventional (18)F-FDG PET-derived parameters and textural tumor heterogeneity features were not suitable to identify high-risk patients.