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Solid pseudopapillary tumor (SPT) of the pancreas is a neoplasm with low malignant potential. It is often challenging to diagnose SPT due to its nonspecific clinical and radiological features, and [18F]FDOPA is effective in diagnosing SPT, particularly in differentiating SPT from benign conditions such as splenosis. A 55-year-old woman underwent distal pancreatectomy and splenectomy for histologically confirmed SPT. She was also initially diagnosed with splenosis. During follow-up, sizes of multiple nodular lesions were increased, raising the possibility of peritoneal seeding of SPT. For diagnosis, a spleen scan and SPECT/CT were performed using 99mTc-labeled damaged red blood cells, which showed no uptake in the peritoneal nodules. Subsequent [18F]FDOPA PET/CT revealed [18F]FDOPA-avidity of the nodules. The patient underwent tumor resection surgery, and the nodules were pathologically confirmed as SPT. [ABSTRACT FROM AUTHOR]

Purpose: Deep learning (DL) has been widely used in various medical imaging analyses. Because of the difficulty in processing volume data, it is difficult to train a DL model as an end-to-end approach using PET volume as an input for various purposes including diagnostic classification. We suggest an approach employing two maximum intensity projection (MIP) images generated by whole-body FDG PET volume to employ pre-trained models based on 2-D images. Methods: As a retrospective, proof-of-concept study, 562 [18F]FDG PET/CT images and clinicopathological factors of lung cancer patients were collected. MIP images of anterior and lateral views were used as inputs, and image features were extracted by a pre-trained convolutional neural network (CNN) model, ResNet-50. The relationship between the images was depicted on a parametric 2-D axes map using t-distributed stochastic neighborhood embedding (t-SNE), with clinicopathological factors. Results: A DL-based feature map extracted by two MIP images was embedded by t-SNE. According to the visualization of the t-SNE map, PET images were clustered by clinicopathological features. The representative difference between the clusters of PET patterns according to the posture of a patient was visually identified. This map showed a pattern of clustering according to various clinicopathological factors including sex as well as tumor staging. Conclusion: A 2-D image-based pre-trained model could extract image patterns of whole-body FDG PET volume by using anterior and lateral views of MIP images bypassing the direct use of 3-D PET volume that requires large datasets and resources. We suggest that this approach could be implemented as a backbone model for various applications for whole-body PET image analyses. [ABSTRACT FROM AUTHOR]

Purpose: 68 Ga-DOTA-TOC uptake in the pancreas uncinate process is often found due to physiologic expression of somatostatin receptors (SSTR). We investigated the association of physiologic 68 Ga-DOTA-TOC uptake in the pancreas uncinate process with blood glucose level. Methods: 68 Ga-DOTA-TOC PET scans acquired from 44 patients (male:female = 20:24, age = 50.8 ± 14.8y [mean ± SD]) were retrospectively analyzed. The blood glucose level (BGL) was examined before 68 Ga-DOTA-TOC injection. Patients diagnosed with diabetes mellitus and patients with BGL over 200 mg/dl were excluded. 68 Ga-DOTA-TOC uptake was measured by the maximum standardized uptake values (SUVmax). Additionally, SSTR-positive volume (SV) in the pancreas uncinate process was measured with two different thresholds: by SUV cutoff of 2.5 (SV2.5) and 40% of SUVmax (SV40%). These measurements on 68 Ga-DOTA-TOC PET were correlated with BGL. Results: The mean of SUVmax of the pancreas uncinate process was 6.51 ± 2.04. SV2.5 was 17.81 ± 7.14 cm3, and SV40% was 18.20 ± 8.83 cm3. A significant negative correlation was found between SUVmax of the pancreas uncinate process and BGL (r = -0.37, p = 0.01). The ratio between SUVmax of the pancreas uncinate process and SUVmean of the pancreas body also showed a significance negative correlation with BGL (r = -0.40, p = 0.01). SV2.5 (r = 0.27, p = 0.07) and SV40% (r = -0.151, p = 0.32) were not significantly correlated with BGL. Conclusion: Physiologic 68 Ga-DOTA-TOC uptake in the pancreas uncinate process was negatively correlated with BGL. Our results suggested that glycemia could affect physiologic uptake of 68 Ga-DOTA-TOC. [ABSTRACT FROM AUTHOR]

The Korean Society of Nuclear Medicine (KSNM) is celebrating its 60th anniversary in honor of the nuclear medicine professionals who have dedicated their efforts towards research, academics, and the more comprehensive clinical applications and uses of nuclear imaging modalities. Nuclear cardiology in Korea was at its prime time in the 1990s, but its growth was interrupted by a long pause. Despite the academic and practical challenges, nuclear cardiology in Korea now meets the second leap, attributed to the growth in molecular imaging tailored for many non-coronary diseases and the genuine values of nuclear myocardial perfusion imaging. In this review, we describe the trends, achievements, challenges, and perspectives of nuclear cardiology throughout the 60-year history of the KSNM. [ABSTRACT FROM AUTHOR]

Cardiac amyloidosis (CA) is a type of systemic amyloidosis, in which abnormal amyloid fibril is deposited in extracellular space of myocardium. Most common subtypes of CA are amyloidosis of immunoglobulin light chain (AL) and amyloidosis of transthyretin (ATTR). With increase in incidence of CA and development of new drugs, the needs of early and accurate diagnosis of CA are increasing. In CA, bone scan and SPECT/CT have long been used for diagnosis. Currently, bone scan is included in almost all practice guidelines as one of key diagnostic examinations for ATTR CA. In some specific scenarios, bone scan can be used as even a substitute for endomyocardial biopsy. Recently, amyloid-targeting PET that is used for Alzheimer dementia has also been attempted as an imaging method for CA. Although the study results are still insufficient, amyloid-targeting has shown promising potential as an imaging method for CA, particularly in AL. Here, imaging method and clinical application and implication of bone scan, SPECT/CT, and amyloid-targeting PET/CT in CA are reviewed. [ABSTRACT FROM AUTHOR]

Purpose: The precise quantification of dopamine transporter (DAT) density on N-(3-[18F]Fluoropropyl)-2β-carbomethoxy-3β-(4-iodophenyl) nortropane positron emission tomography ([18F]FP-CIT PET) imaging is crucial to measure the degree of striatal DAT loss in patients with parkinsonism. The quantitative analysis requires a spatial normalization process based on a template brain. Since the spatial normalization method based on a delayed-phase PET has limited performance, we suggest an early-phase PET-based method and compared its accuracy, referring to the MRI-based approach as a gold standard. Methods: A total of 39 referred patients from the movement disorder clinic who underwent dual-phase [18F]FP-CIT PET and took MRI within 1 year were retrospectively analyzed. The three spatial normalization methods were applied for quantification of [18F]FP-CIT PET-MRI-based anatomical normalization, PET template-based method based on delayed PET, and that based on early PET. The striatal binding ratios (BRs) were compared, and voxelwise paired t tests were implemented between different methods. Results: The early image-based normalization showed concordant patterns of putaminal [18F]FP-CIT binding with an MRI-based method. The BRs of the putamen from the MRI-based approach showed higher agreement with early image- than delayed image-based method as presented by Bland-Altman plots and intraclass correlation coefficients (early image-based, 0.980; delayed image-based, 0.895). The voxelwise test exhibited a smaller volume of significantly different counts in putamen between brains processed by early image and MRI compared to that between delayed image and MRI. Conclusion: The early-phase [18F]FP-CIT PET can be utilized for spatial normalization of delayed PET image when the MRI image is unavailable and presents better performance than the delayed template-based method in quantitation of putaminal binding ratio. [ABSTRACT FROM AUTHOR]

Purpose: EGFR-mutation (EGFR-mt) is a major oncogenic driver mutation in lung adenocarcinoma (ADC) and is more often observed in Asian population. In lung ADC, some radiomics parameters of FDG PET have been reported to be associated with EGFR-mt. Here, the associations between EGFR-mt and PET parameters, particularly asphericity (ASP), were evaluated in Asian population. Methods: Lung ADC patients who underwent curative surgical resection as the first treatment were retrospectively enrolled. EGFR mutation was defined as exon 19 deletion and exon 21 point mutation and was evaluated using surgical specimens. On FDG PET, image parameters of maximal standardized uptake value (SUVmax), metabolic tumor volume (MTV), total lesion glycolysis (TLG), and ASP were obtained. The parameters were compared between EGFR-mt and wild type (EGFR-wt) groups, and the relationships between these PET parameters and EGFR-mt were evaluated. Results: A total of 64 patients (median age 66 years, M:F = 34:30) were included in the analysis, and 29 (45%) patients showed EGFR-mt. In EGFR-mt group, all the image parameters of SUVmax, MTV, TLG, and ASP were significantly lower than in EGFR-wt group (all adjusted P < 0.050). In univariable logistic regression, SUVmax (P = 0.003) and ASP (P = 0.010) were significant determinants for EGFR-mt, whereas MTV was not (P = 0.690). Multivariate analysis revealed that SUVmax and ASP are independent determinants for EGFR-mt, regardless of inclusion of MTV in the analysis (P < 0.05). Conclusion: In Asian NSCLC/ADC patients, SUVmax, MTV, and ASP on FDG PET are significantly related to EGFR mutation status. Particularly, low SUVmax and ASP are independent determinants for EGFR-mt. [ABSTRACT FROM AUTHOR]

Purpose: Although quantification of amyloid positron emission tomography (PET) is important for evaluating patients with cognitive impairment, its routine clinical use is hampered by complicated preprocessing steps and required MRI. Here, we suggested a one-step quantification based on deep learning using native-space amyloid PET images of different radiotracers acquired from multiple centers. Methods: Amyloid PET data of the Alzheimer Disease Neuroimaging Initiative (ADNI) were used for this study. A training/validation consists of 850 florbetapir PET images. Three hundred sixty-six florbetapir and 89 florbetaben PET images were used as test sets to evaluate the model. Native-space amyloid PET images were used as inputs, and the outputs were standardized uptake value ratios (SUVRs) calculated by the conventional MR-based method. Results: The mean absolute errors (MAEs) of the composite SUVR were 0.040, 0.060, and 0.050 of training/validation and test sets for florbetapir PET and a test set for florbetaben PET, respectively. The agreement of amyloid positivity measured by Cohen's kappa for test sets of florbetapir and florbetaben PET were 0.87 and 0.89, respectively. Conclusion: We suggest a one-step quantification method for amyloid PET via a deep learning model. The model is highly reliable to quantify the amyloid PET regardless of multicenter images and various radiotracers. [ABSTRACT FROM AUTHOR]

Radiomics is a medical imaging analysis approach based on computer-vision. Metabolic radiomics in particular analyses the spatial distribution patterns of molecular metabolism on PET images. Measuring intratumoral heterogeneity via image is one of the main targets of radiomics research, and it aims to build a image-based model for better patient management. The workflow of radiomics using texture analysis follows these steps: 1) imaging (image acquisition and reconstruction); 2) preprocessing (segmentation & quantization); 3) quantification (texture matrix design & texture feature extraction); and 4) analysis (statistics and/or machine learning). The parameters or conditions at each of these steps are effect on the results. In statistical testing or modeling, problems such as multiple comparisons, dependence on other variables, and high dimensionality of small sample size data should be considered. Standardization of methodology and harmonization of image quality are one of the most important challenges with radiomics methodology. Even though there are current issues in radiomics methodology, it is expected that radiomics will be clinically useful in personalized medicine for oncology. [ABSTRACT FROM AUTHOR]

Purpose: Although 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET) is a standard imaging modality for response evaluation in FDG-avid lymphoma, there is a controversy using FDG PET in indolent lymphoma. The purpose of this study was to investigate the effectiveness of quantitative indexes on FDG PET in response evaluation of the indolent lymphoma.Methods: Fifty-seven indolent lymphoma patients who completed chemotherapy were retrospectively enrolled. FDG PET/computed tomography (CT) scans were performed at baseline, interim, and end of treatment (EOT). Response was determined by Lugano classification, and progression-free survival (PFS) by follow-up data. Maximum standardized uptake value (SUVmax), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) were measured in the single hottest lesion (target A) or five hottest lesions (target B). Their efficacies regarding response evaluation and PFS prediction were evaluated.Results: On EOT PET, SUVmax, and MTV of both targets were well associated with visual analysis. Changes between initial and EOT PET were not significantly different between CR and non-CR groups. On interim PET, SUVmax, and %ΔSUVmax in both targets were significantly different between CR and non-CR groups. For prediction of PFS, most tested indexes were significant on EOT and interim PET, with SUVmax being the most significant prognostic factor.Conclusion: Quantitative indexes of FDG PET are well associated with Lugano classification in indolent lymphoma. SUVmax measured in the single hottest lesion can be effective in response evaluation and prognosis prediction on interim and EOT PET. [ABSTRACT FROM AUTHOR]

Purpose: In malignant melanoma, recurrence is often observed in distant areas from the primary site. While FDG PET is a sensitive imaging for detecting malignant lesions, the role of FDG PET in posttreatment surveillance period has not been investigated sufficiently. The aim of this study was to evaluate the value of PET during posttreatment surveillance in melanoma.Methods: A total of 76 melanoma patients who underwent FDG PET during surveillance period after completion of the first treatment were retrospectively enrolled. PET scans were grouped according to the purpose and clinical situations, routine surveillance, or evaluating clinical suspicion. Final diagnosis of recurrence was determined by complete clinical evaluation or long-term follow-up. In each situation, the diagnostic role of FDG PET was assessed.Results: A total of 143 scans of 76 patients were analyzed: 51 for clinical suspicion and 92 for routine surveillance. In the clinical suspicion group, PET correctly diagnosed non-recurrence in 10 cases (20%). In routine surveillance group, 16 cases (17%) presented recurrence, all of which was correctly diagnosed on PET. NPV and PPV were 100% and 76%, respectively. In subgroup analysis, sensitivity and NPV were higher in the low-risk group (stages I-IIA) than in the high-risk group (stages IIB-IV), while specificity and PPV were higher in the high-risk group.Conclusion: In conclusion, FDG PET is an effective diagnostic tool in posttreatment surveillance of melanoma. Even in cases without clinical suspicion, melanoma recurs in a considerable proportion of patients, which can be sensitively diagnosed on PET. [ABSTRACT FROM AUTHOR]

Purpose: 68Ga-labeled 1,4,7,10-tetraazacyclododecane-N,N′,N″,N‴-tetraacetic acid-D-Phe1-Tyr3-octreotide (68Ga-DOTATOC) is taken up by activated macrophages, which accumulate in active inflammatory lesions. The purpose of this study was to investigate the feasibility of 68Ga-DOTATOC PET/CT for assessment of vulnerable plaque, by evaluating correlation between aortic uptake of 68Ga-DOTATOC and cardiovascular risk factors.Methods: Fifty patients with neuroendocrine tumors who underwent 68Ga-DOTATOC PET/CT were retrospectively enrolled. The uptakes in the thoracic aorta were measured by two methods: multi-sample region-of-interest (ROI) method and single volume-of-interest (VOI) method. TBRmax-avg, TBRmean-avg, TBRmax-VOI, and TBRmean-VOI were defined by maximum and mean target-to-background ratio (TBR) from the multi-sample ROI method and the single VOI method, respectively.Results: Framingham risk score (FRS) exhibited significant correlations with TBRmax-avg and TBRmean-avg, as well as TBRmax-VOI (r = 0.3389-0.4593, P < 0.05 for all). TBRmax-avg and TBRmax-VOI were significantly higher in high FRS group than in low FRS group (1.48 ± 0.21 vs. 1.70 ± 0.17, P < 0.001 for TBRmax-avg and 1.90 ± 0.33 vs. 2.25 ± 0.36, P = 0.002 for TBRmax-VOI). TBR exhibited high correlations between the two measuring methods (r = 0.9684, P < 0.001 for TBRmean-avg and TBRmean-VOI and r = 0.8681, P < 0.001 for TBRmax-avg and TBRmax-VOI).Conclusions: 68Ga-DOTATOC uptake in the thoracic aorta exhibited a significant correlation with cardiovascular risk factors, which suggests the feasibility of 68Ga-DOTATOC PET for vulnerable plaque imaging, with a simple measurement of the single VOI method that is comparable to the multi-sample ROI-based approach. [ABSTRACT FROM AUTHOR]

Purpose: Lymph node (LN) characterization is crucial in determining the stage and treatment decisions in patient with lung cancer. Although 18F-fluorodeoxyglucose positron emission tomography/computed tomography ( 18F-FDG PET/CT) has a higher diagnostic accuracy in LN characterization than anatomical imaging, differentiating between metastatic and inflammatory LNs is still challenging because both could show high 18F-FDG uptake. The purpose of this study was to assess if the heterogeneity of the 18F-FDG uptake could help in differentiating between inflammatory and metastatic LNs in lung cancer, and to compare with other parameters. Methods: A total of 44 patients with adenocarcinoma of the lung, who underwent preoperative 18F-FDG PET/CT without having any previous treatments and were revealed to have 18F-FDG-avid LNs, were enrolled. There were 52 pathology-proven metastatic lymph nodes in 26 subjects. The pathology-proven metastatic LNs were compared with 42 pathology-proven inflammatory/benign LNs in 18 subjects. The coefficient of variation (CV) was used to assess the heterogeneity of 18F-FDG uptake by dividing the standard deviation of standardized uptake value (SUV) by mean SUV. The volume of interest was manually drawn based on the combined CT images of 18F-FDG PET/CT (no threshold is used). Comparisons were made with the maximum standardized uptake values (SUVmax), visual assessment of 18F-FDG uptake, longest diameter, and maximum Hounsfield units (HUmax). Results: Metastatic lymph nodes tended to have higher CVs than the inflammatory LNs. The mean CV of metastatic LNs (0.30 ± 0.08; range: 0.08–0.55) was higher than that of inflammatory LNs (0.17 + 0.06; range, 0.07–0.32; P < 0.0001). On receiver operating characteristic (ROC) curve analysis, the area under curve was 0.901, and using 0.20 as cut-off value, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy were 88.5 %, 76.2 %, 82.2 %, 84.3, and 83.0 % respectively. Accuracy of CV was slightly higher than SUVmax and diameter, but significantly higher than visual assessment and HUmax. Conclusions: In patients with adenocarcinoma of the lung having no prior treatments, metastatic LNs showed more heterogeneous 18F-FDG uptake than inflammatory LNs. Measuring the CV of the SUV derived from a manual volume of interest (VOI) can be helpful in determining metastatic LN of adenocarcinoma of the lung. Including diagnostic criteria of CV into the diagnostic approach can increase the accuracy of mediastinal node status. [ABSTRACT FROM AUTHOR]