68Ga-PSMA PET/CT and 18F-FDG PET/CT in the diagnosis of prostatic ductal cancer.

PURPOSES: To explore the characteristics of PSMA PET/CT and FDG PET/CT images in prostatic ductal adenocarcinoma (DA) patients. METHODS: We retrospectively enrolled prostatic DA patients with PET/CT scans at Tongji Hospital from 2018 to 2022. Patients with prostatic acinar adenocarcinoma (AA) and benign pathology (BP) were enrolled by 1:1 matching. Differences in the uptake of primary and metastatic foci on PET among the groups were analyzed. RESULTS: A total of 42 patients were enrolled: 14 in each group. In primary foci, the mean PSMA uptake in the DA group was lower than that in the AA group (14.2 ± 9.6 vs. 27.1 ± 14.3, P = 0.009) and greater than that in the BP group (14.2 ± 9.6 vs. 4.7 ± 1.3, P = 0.003). The AUCs of the DA-AA ROC curve and DA-BP ROC curve were 0.781 and 0.872, respectively. The median PSMA uptake of metastatic lymph nodes in the DA group was lower than that in the AA group (5.6 vs. 14.2, P = 0.033), with no significant difference in metastatic bone lesions (9.5 vs 19.1, P = 0.485). No significant difference was found in the FDG uptake of primary and metastatic foci between the DA and AA groups (P > 0.05). CONCLUSION: Prostatic DA has greater PSMA uptake than BP diseases, but lower uptake in both primary foci and metastatic lymph nodes than AA on PSMA PET/CT, aiding in the differential diagnosis of DA, AA and BP diseases. Clinicians should combine traditional imaging with PSMA PET/CT to avoid underestimating the clinical stage of DA patients.

Comparing the diagnostic performance of [18F]FDG PET/CT and [18F]FDG PET/MRI for detecting cardiac sarcoidosis: A meta-analysis.

PURPOSE: This meta-analysis aimed to evaluate the comparative diagnostic efficacy of [18F]FDG PET/CT and [18F]FDG PET/MRI in detecting cardiac sarcoidosis. METHODS: An extensive search was conducted in the PubMed and Embase databases to identify available publications up to November 2023. Studies were included if they evaluated the diagnostic efficacy of [18F]FDG PET/CT and [18F]FDG PET/MRI in patients with cardiac sarcoidosis. Sensitivity and specificity were evaluated using the DerSimonian and Laird method, with subsequent transformation via the Freeman-Tukey double inverse sine transformation. Publication bias was assessed using funnel plots and Egger's test. RESULTS: 16 articles involving 1361 patients were included in the meta-analysis. The overall sensitivity of [18F]FDG PET/CT in detecting cardiac sarcoidosis was 0.77(95%CI: 0.62-0.89), while the overall sensitivity of [18F]FDG PET/MRI was 0.94(95%CI: 0.84-1.00). The result indicated that [18F]FDG PET/MRI appears to a higher sensitivity in comparison to [18F]FDG PET/CT(P = 0.02). In contrast, the overall specificity of [18F]FDG PET/CT in detecting cardiac sarcoidosis was 0.90(95%CI: 0.85-0.94), while the overall specificity of [18F]FDG PET/MRI was 0.79(95%CI: 0.53-0.96), with no significant difference in specificity (P = 0.32). CONCLUSIONS: Our meta-analysis indicates that [18F]FDG PET/MRI demonstrates superior sensitivity and comparable specificity to [18F]FDG PET/CT in detecting cardiac sarcoidosis. However, the small number of PET/MRI studies limited the evidence of current results. To validate these results, larger, prospective studies employing a head-to-head design are needed.

A 18F-FDG PET/CT based radiomics nomogram for predicting disease-free survival in stage II/III colorectal adenocarcinoma.

OBJECTIVES: This study aimed to establish a clinical nomogram model based on a radiomics signatures derived from 18F-fluorodeoxyglucose positron-emission tomography (18F-FDG PET/CT) and clinical parameters to predict disease-free survival (DFS) in patients with stage II/III colorectal adenocarcinoma. Understanding and predicting DFS in these patients is key to optimizing treatment strategies. METHODS: A retrospective analysis included 332 cases from July 2011 to July 2021 at The Sixth Affiliated Hospital, Sun Yat-sen University, with PET/CT assessing radiomics features and clinicopathological features. Univariate Cox regression, the least absolute shrinkage and selection operator (LASSO) Cox, and multivariable Cox regression identified recurrence-related radiomics features. We used a weighted radiomics score (Rad-score) and independent risk factors to construct a nomogram. Evaluation involved time-dependent receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). RESULTS: The nomogram, incorporating Rad-score, pN, and pT demonstrated robust predictive ability for DFS in stage II/III colorectal adenocarcinoma. Training cohort areas under the curve (AUCs) were 0.78, 0.80, and 0.86 at 1, 2, and 3 years, respectively, and validation cohort AUCs were 0.79, 0.75, and 0.73. DCA and calibration curves affirmed the nomogram's clinical relevance. CONCLUSION: The 18F-FDG PET/CT based radiomics nomogram, including Rad-score, pN, and pT, effectively predicted tumor recurrence in stage II/III colorectal adenocarcinoma, significantly enhancing prognostic stratification. Our findings highlight the potential of this nomogram as a guide for clinical decision making to improve patient outcomes.

Stroke-Like Migraine Attacks After Radiation Therapy (SMART) Syndrome: A Case Report.

Stroke-like migraine attacks after radiation therapy (SMART) syndrome is a rare and delayed complication of brain irradiation involving impaired cerebrovascular autoregulation, and diagnosis is based on distinct clinic-radiographic findings and exclusion of differentials. We report a 38-year-old man, who received cranial irradiation 28 years before and developed episodes of headache and visual aura, followed by left hemianopia, aphasia, behavioral disturbances, and focal seizures. An MRI of the brain revealed gyral swelling with restricted diffusion and mild contrast enhancement over the right temporoparietal and occipital region, and fludeoxyglucose-FDG PET scan showed hyperperfusion in the corresponding brain region. He improved completely with pulse steroids and antiseizure medications. The recognition of this syndrome is important as we can reassure patients and their families and help avoid unnecessary and invasive diagnostic tests.

International Benchmark for Total Metabolic Tumor Volume Measurement in Baseline 18F-FDG PET/CT of Lymphoma Patients: A Milestone Toward Clinical Implementation.

Total metabolic tumor volume (TMTV) is prognostic in lymphoma. However, cutoff values for risk stratification vary markedly, according to the tumor delineation method used. We aimed to create a standardized TMTV benchmark dataset allowing TMTV to be tested and applied as a reproducible biomarker. Methods: Sixty baseline 18F-FDG PET/CT scans were identified with a range of disease distributions (20 follicular, 20 Hodgkin, and 20 diffuse large B-cell lymphoma). TMTV was measured by 12 nuclear medicine experts, each analyzing 20 cases split across subtypes, with each case processed by 3-4 readers. LIFEx or ACCURATE software was chosen according to reader preference. Analysis was performed stepwise: TMTV1 with automated preselection of lesions using an SUV of at least 4 and a volume of at least 3 cm3 with single-click removal of physiologic uptake; TMTV2 with additional removal of reactive bone marrow and spleen with single clicks; TMTV3 with manual editing to remove other physiologic uptake, if required; and TMTV4 with optional addition of lesions using mouse clicks with an SUV of at least 4 (no volume threshold). Results: The final TMTV (TMTV4) ranged from 8 to 2,288 cm3, showing excellent agreement among all readers in 87% of cases (52/60) with a difference of less than 10% or less than 10 cm3 In 70% of the cases, TMTV4 equaled TMTV1, requiring no additional reader interaction. Differences in the TMTV4 were exclusively related to reader interpretation of lesion inclusion or physiologic high-uptake region removal, not to the choice of software. For 5 cases, large TMTV differences (>25%) were due to disagreement about inclusion of diffuse splenic uptake. Conclusion: The proposed segmentation method enabled highly reproducible TMTV measurements, with minimal reader interaction in 70% of the patients. The inclusion or exclusion of diffuse splenic uptake requires definition of specific criteria according to lymphoma subtype. The publicly available proposed benchmark allows comparison of study results and could serve as a reference to test improvements using other segmentation approaches.

An end-to-end deep learning pipeline to derive blood input with partial volume corrections for automated parametric brain PET mapping.

Dynamic 2-[18F] fluoro-2-deoxy-D-glucose positron emission tomography (dFDG-PET) for human brain imaging has considerable clinical potential, yet its utilization remains limited. A key challenge in the quantitative analysis of dFDG-PET is characterizing a patient-specific blood input function, traditionally reliant on invasive arterial blood sampling. This research introduces a novel approach employing non-invasive deep learning model-based computations from the internal carotid arteries (ICA) with partial volume (PV) corrections, thereby eliminating the need for invasive arterial sampling. We present an end-to-end pipeline incorporating a 3D U-Net based ICA-net for ICA segmentation, alongside a Recurrent Neural Network (RNN) based MCIF-net for the derivation of a model-corrected blood input function (MCIF) with PV corrections. The developed 3D U-Net and RNN was trained and validated using a 5-fold cross-validation approach on 50 human brain FDG PET datasets. The ICA-net achieved an average Dice score of 82.18% and an Intersection over Union of 68.54% across all tested scans. Furthermore, the MCIF-net exhibited a minimal root mean squared error of 0.0052. The application of this pipeline to ground truth data for dFDG-PET brain scans resulted in the precise localization of seizure onset regions, which contributed to a successful clinical outcome, with the patient achieving a seizure-free state after treatment. These results underscore the efficacy of the ICA-net and MCIF-net deep learning pipeline in learning the ICA structure's distribution and automating MCIF computation with PV corrections. This advancement marks a significant leap in non-invasive neuroimaging.

sICAM-1 concentrations are associated with inflammation in contralateral carotid plaque in patients with ischemic stroke.

BACKGROUND: Atherosclerotic plaques in the internal carotid artery are responsible for more than 15% of ischemic strokes. Carotid 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET) detects plaque inflammation. Plasma ICAM-1 and LRP1 concentrations have been associated with inflammation in ipsilateral carotid plaque. The aim of the present study was to test the association between the soluble (s) form of these biomarkers and contralateral carotid plaques. METHODS: Prospective study conducted in 53 patients with a recent ischemic stroke and at least one atherosclerotic plaque in both carotid arteries. All of the patients underwent an early carotid 18F-FDG PET, and a blood sample was obtained at 7±1 days. Several plasma inflammatory markers were evaluated by Multiplex and sLRP1 levels were measured by commercial ELISA. Bivariate and multivariable linear regression was used to assess the association between inflammatory markers and the clinical variables, including contralateral maximum standardized uptake value (SUVmax) and mean SUVmax (mean of contralateral and ipsilateral SUVmax) of 18F-FDG uptake. Hazard ratio (HR) was estimated with Cox models adjusted for potential confounding factors to evaluate recurrence. RESULTS: Multivariable linear regression analysis showed an independent association between sICAM-1 and sVCAM-1 and mean SUVmax (CI=-0.064-0.325, p=0.004; CI=0.079-0.554, p=0.010). In addition, in bivariate regression analysis, sICAM-1 was associated with contralateral SUVmax (CI=0.049-0.382, p=0.012). Cox regression showed that mean SUVmax was associated with stroke recurrence (HR=5.604, p=0.044). CONCLUSIONS: sICAM-1 was independently associated with mean carotid plaque inflammation and with inflammation in contralateral plaque. sICAM-1 could be an indicator of plaque inflammation even in asymptomatic plaques.

Predictive Value of PERCIST for Locally Advanced Non-Small Cell Lung Cancer Treated with Preoperative Induction Therapy - A Multicenter Study in Japan.

Background: Induction therapy followed by surgery is recommended as an alternative treatment strategy for locally advanced non-small cell lung cancer (NSCLC). Patients who achieve pathologic response after induction therapy have better outcomes than non-responders; therefore, therapeutic response must be evaluated. Recently, new approaches for monitoring therapeutic responses, which are based on 18F-Fluorodeoxyglucose positron emission tomography (FDG-PET), have been developed. In this study, we evaluated the predictive value of Positron Emission Tomography Response Criteria in Solid Tumors (PERCIST), which uses standardized uptake values corrected for lean body mass (SUL) and total lesion glycolysis (TLG). Methods: A total of 130 patients in the Setouchi Lung Cancer Group who underwent FDG-PET imaging before and after induction therapy prior to a planned surgical resection for NSCLC between 2007 and 2016 were studied retrospectively. The pathologic responses of the primary lung tumors and metastatic lymph nodes were compared with their responses based on evaluation using PERCIST. Results: Postoperative pathologic studies revealed pathologic complete response (pCR) in 42 (32.3%) patients. PERCIST was significantly correlated with pathologic response (p < 0.001). The sensitivity, specificity, and accuracy of PERCIST for predicting pCR were 16.7% (7/42), 88.6% (78/88), and 65.4% (85/130), respectively. Patients with pCR had significantly higher reduction rates in SULpeak for both primary lung tumors and metastatic lymph nodes and TLG for primary tumors than non-responders. In a multivariate Cox regression analysis, tumor site in upper lobes, reduction rate of TLG in primary tumor, and pathologic N0 were independent predictors of favorable recurrence-free survival (RFS). Conclusion: Our study suggested that PERCIST, especially the rate of TLG reduction rate, are useful to predict the pathological response and prognosis after induction therapy. Although improvement is necessary, PERCIST can be a promising method of the post-induction status in lung cancer. Further research is needed to confirm our findings.

The clinical and predictive value of 18F-FDG PET/CT metabolic patterns in a clinical Chinese cohort with autoimmune encephalitis.

AIMS: To investigate the diagnostic and predictive role of 18F-FDG PET/CT in patients with autoimmune encephalitis (AE) as a whole group. METHODS: Thrty-five patients (20 females and 15 males) with AE were recruited. A voxel-to-voxel semi-quantitative analysis based on SPM12 was used to analyze 18F-FDG PET/CT imaging data compared to healthy controls. Further comparison was made in different prognostic groups categorized by modified Rankin Scale (mRS). RESULTS: In total, 24 patients (68.6%) were tested positive neuronal antibodies in serum and/or CSF. Psychiatric symptoms and seizure attacks were major clinical symptoms. In the acute stage, 13 patients (37.1%) demonstrated abnormal brain MRI results, while 33 (94.3%) presented abnormal metabolism patterns. 18F-FDG PET/CT was more sensitive than MRI (p < 0.05). Patients with AE mainly presented mixed metabolism patterns compared to the matched controls, demonstrating hypermetabolism mainly in the cerebellum, BG, MTL, brainstem, insula, middle frontal gyrus, and relatively hypometabolism in the frontal cortex, occipital cortex, temporal gyrus, right parietal gyrus, left cingulate gyrus (p < 0.05, FWE corrected). After a median follow-up of 26 months, the multivariable analysis identified a decreased level of consciousness as an independent risk factor associated with poor outcome of AE (HR = 3.591, p = 0.016). Meanwhile, decreased metabolism of right superior frontal gyrus along with increased metabolism of the middle and upper brainstem was more evident in patients with poor outcome (p < 0.001, uncorrected). CONCLUSION: 18F-FDG PET/CT was more sensitive than MRI to detect neuroimaging abnormalities of AE. A mixed metabolic pattern, characterized by large areas of cortical hypometabolism with focal hypermetabolism was a general metabolic pattern. Decreased metabolism of right superior frontal gyrus with increased metabolism of the middle and upper brainstem may predict poor long-term prognosis of AE.

Misdiagnosis of a Drain-site Hernia Containing Fallopian Tube Fimbria on 18F-FDG PET/CT.

In a 55-year-old woman with sigmoid colon cancer, a subcutaneous mass in the left lower abdomen was incidentally found and gradually enlarged. For further diagnosis and staging, an 18F-fluorodeoxyglucose (FDG) positron emission tomography/computed tomography scan was performed, which revealed a subcutaneous mass in the left lower abdomen with mild uptake of 18F-FDG, suggesting the possibility of metastasis. However, post-surgery and pathological confirmation, this mass was diagnosed as a drain-site hernia containing fallopian tube fimbria, which is extremely rare but should be considered in the differential diagnosis of subcutaneous mass in the lower abdomen.

Jejunal Undifferentiated Spindle Cell Sarcoma with Intussusception Revealed by 18F-FDG PET/CT.

Spindle cell sarcoma is a malignant tumor with low incidence. They can occur in the soft tissue, bone, or viscera. The characteristics of morphology, density, and metabolism of spindle cell sarcoma are related to the location of the lesion. A 61-year-old woman presented with vomiting after eating for 2 weeks. Signs of peritoneal irritation were involved, but no response for symptomatic treatment included antiemetic and antispasmodic therapy. Abdominal computed tomography (CT) indicated a mass in the intestinal tract in the pelvic cavity. Then, 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography/CT was performed, which interestingly detected a jejunal malignancy mass in the left upper abdomen with annular high uptake of 18F-FDG, which was complicated by intussusception and intestinal obstruction. Finally, the jejunal mass was pathologically clarified as an undifferentiated spindle cell sarcoma.

Isolated Diffuse Bone Marrow Metastases From Signet-ring Cell Gastric Carcinoma.

A 71-year-old female patient with a known history of signet-ring cell carcinoma presented with diffuse bone pain and anemic symptoms. An 18F-fluorodeoxyglucose (FDG) positron emission tomography/computed tomography study revealed diffuse heterogeneous hypermetabolic sclerotic lesions in the axial and proximal appendicular skeleton. No other 18F-FDG-avid lesions were detected. Subsequent bone marrow biopsy confirmed the diagnosis of metastatic carcinoma originating from the gastric primary site. Palliative treatment was initiated; however, the patient's condition deteriorated, and she succumbed to the disease two months later.

18F-FDG PET/CT Radiomics-Based Multimodality Fusion Model for Preoperative Individualized Noninvasive Prediction of Peritoneal Metastasis in Advanced Gastric Cancer.

PURPOSE: This study was designed to develop and validate a machine learning-based, multimodality fusion (MMF) model using 18F-fluorodeoxyglucose (FDG) PET/CT radiomics and kernelled support tensor machine (KSTM), integrated with clinical factors and nuclear medicine experts' diagnoses to individually predict peritoneal metastasis (PM) in advanced gastric cancer (AGC). METHODS: A total of 167 patients receiving preoperative PET/CT and subsequent surgery were included between November 2006 and September 2020 and were divided into a training and testing cohort. The PM status was confirmed via laparoscopic exploration and postoperative pathology. The PET/CT signatures were constructed by classic radiomic, handcrafted-feature-based model and KSTM self-learning-based model. The clinical nomogram was constructed by independent risk factors for PM. Lastly, the PET/CT signatures, clinical nomogram, and experts' diagnoses were fused using evidential reasoning to establish the MMF model. RESULTS: The MMF model showed excellent performance in both cohorts (area under the curve [AUC] 94.16% and 90.84% in training and testing), and demonstrated better prediction accuracy than clinical nomogram or experts' diagnoses (net reclassification improvement p < 0.05). The MMF model also had satisfactory generalization ability, even in mucinous adenocarcinoma and signet ring cell carcinoma which have poor uptake of 18F-FDG (AUC 97.98% and 89.71% in training and testing). CONCLUSIONS: The 18F-FDG PET/CT radiomics-based MMF model may have significant clinical implications in predicting PM in AGC, revealing that it is necessary to combine the information from different modalities for comprehensive prediction of PM.

Respective contribution of baseline clinical data, tumour metabolism and tumour blood-flow in predicting pCR after neoadjuvant chemotherapy in HER2 and Triple Negative breast cancer.

BACKGROUND: The aim of this study is to investigate the added value of combining tumour blood flow (BF) and metabolism parameters, including texture features, with clinical parameters to predict, at baseline, the pathological complete response (pCR) to neoadjuvant chemotherapy (NAC) in patients with newly diagnosed breast cancer (BC). METHODS: One hundred and twenty-eight BC patients underwent a 18F-FDG PET/CT before any treatment. Tumour BF and metabolism parameters were extracted from first-pass dynamic and delayed PET images, respectively. Standard and texture features were extracted from BF and metabolic images. Prediction of pCR was performed using logistic regression, random forest and support vector classification algorithms. Models were built using clinical (C), clinical and metabolic (C+M) and clinical, metabolic and tumour BF (C+M+BF) information combined. Algorithms were trained on 80% of the dataset and tested on the remaining 20%. Univariate and multivariate features selections were carried out on the training dataset. A total of 50 shuffle splits were performed. The analysis was carried out on the whole dataset (HER2 and Triple Negative (TN)), and separately in HER2 (N=76) and TN (N=52) tumours. RESULTS: In the whole dataset, the highest classification performances were observed for C+M models, significantly (p-value<0.01) higher than C models and better than C+M+BF models (mean balanced accuracy of 0.66, 0.61, and 0.64 respectively). For HER2 tumours, equal performances were noted for C and C+M models, with performances higher than C+M+BF models (mean balanced accuracy of 0.64, and 0.61 respectively). Regarding TN tumours, the best classification results were reported for C+M models, with better performances than C and C+M+BF models but not significantly (mean balanced accuracy of 0.65, 0.63, and 0.62 respectively). CONCLUSION: Baseline clinical data combined with global and texture tumour metabolism parameters assessed by 18F-FDG PET/CT provide a better prediction of pCR after NAC in patients with BC compared to clinical parameters alone for TN, and HER2 and TN tumours together. In contrast, adding BF parameters to the models did not improve prediction, regardless of the tumour subgroup analysed.

Comprehensive considerations for dermatologists: the application of FDG-PET in evaluating cutaneous lesions in pediatric Langerhans cell histiocytosis.

Langerhans cell histiocytosis (LCH) is a complex disorder characterized by the clonal proliferation of Langerhans cells, primarily affecting children and adolescents. This condition exhibits a wide spectrum of clinical presentations, necessitating a multidisciplinary approach for diagnosis, treatment, and follow-up. Cutaneous manifestations of LCH are significant, mimicking common dermatoses and posing diagnostic challenges. [18F]Fluorodeoxyglucose-Positron Emission Tomography (FDG-PET) has emerged as an important tool in the evaluation of pediatric LCH, offering insights into disease activity, extent, and therapeutic response. Moreover, FDG-PET provides a non-invasive means to distinguish between active LCH skin lesions and other dermatological conditions with similar clinical appearances, enhancing diagnostic accuracy and aiding in disease monitoring. This educational review summarizes the utility of nuclear imaging techniques, with a focus on PET scans, in the diagnosis and management of cutaneous pediatric LCH. A comprehensive literature search identified seven relevant articles, including retrospective studies and case reports. These studies highlight the efficacy of FDG-PET in localizing active LCH skin lesions, monitoring disease activity, and guiding treatment decisions. FDG-PET represents a valuable imaging modality for dermatologists, oncologists, and pediatricians managing pediatric LCH patients with cutaneous involvement. This non-invasive technique contributes to improved diagnostic accuracy and facilitates early intervention, ultimately enhancing patient care and outcomes.

FDG-PET/MRI in colorectal cancer care: an updated systematic review.

PURPOSE: Since its introduction in 2011, FDG-PET/MRI has been advocated as a useful adjunct in colorectal cancer care. However, gaps and limitations in current research remain. This systematic review aims to review the current literature to quantify the utility of FDG-PET/MRI in colorectal cancer care. METHODS: An up-to-date review was performed on the available literature between 2000 and 2023 on PubMed, EMBASE, Medline, databases. All studies reporting on the use of FDG-PET/MRI in colorectal cancer care were analyzed. The main outcome measures were accuracy in initial staging, restaging, and detection of metastatic disease in both rectal as well as colon cancers. The secondary outcome was comparing the performance of FDG-PET/MRI versus Standard of Care Imaging (SCI). Finally, the clinical significance of FDG-PET/MRI was measured in the change in management resulting from imaging findings. RESULTS: A total of 22 observational studies were included, accounting for 988 patients. When individually compared to current Standard of Care Imaging (SCI)-MRI pelvis for rectal cancer and thoraco-abdominal contrast CT, PET/MRI proved superior in terms of distant metastatic disease detection. This led to as much as 21.0% change in management. However, the technological limitations of PET/MRI were once again highlighted, suggesting SCI should retain its place as first-line imaging. CONCLUSION: FDG-PET/MRI appears to be a promising adjunct in staging and restaging of colorectal cancer in carefully selected patients.

Prognostic Significance of 18F-FDG PET/CT and Tumor Metabolic Changes in Patients With Pancreatic Ductal Adenocarcinoma.

BACKGROUND/AIM: 18F-fluorodeoxyglucose positron emission tomography/computed tomography (FDG-PET/CT) is reportedly associated with the malignant potential of cancer. This study aimed to evaluate the association between FDG accumulation and tumor metabolism in pancreatic ductal adenocarcinoma (PDAC). PATIENTS AND METHODS: A prognostic analysis of data from 131 patients with PDAC who underwent FDG-PET/CT before curative-intent pancreatic surgery was performed. Capillary electrophoresis-mass spectrometry (CE-MS) was used to analyze the metabolome of tumor and non-neoplastic pancreas from 80 patients. These patients were divided into two groups: low SUVmax group (SUVmax <6.09) and high SUVmax group (SUVmax ≥6.09). RESULTS: Carbohydrate antigen 19-9 (CA19-9), maximum standardized uptake value (SUVmax) of PET, N stage, and postoperative chemotherapy were identified as significant prognostic factors by univariate analysis. SUVmax emerged as an independent prognostic factor for overall survival [hazard ratio (HR)=1.88, p<0.05] and disease-free survival (HR=2.01, p<0.05) in multivariate analysis. Metabolic analyses confirmed that 43 metabolites significantly differed depending on the accumulation of SUV in tumors. Metabolites involved in the removal of reactive oxygen species (e.g., hypotaurine, glutathione, Met), treatment resistance (UDP-N-acetylglucosamine), and proliferation (e.g., choline, leucine, isoleucine) were increased in the high SUVmax group. CONCLUSION: FDG accumulation is an important independent prognostic factor reflecting tumor activity associated with metabolic changes in cancer cells.

Prediction of Histological Grade of Oral Squamous Cell Carcinoma Using Machine Learning Models Applied to 18F-FDG-PET Radiomics.

The histological grade of oral squamous cell carcinoma affects the prognosis. In the present study, we performed a radiomics analysis to extract features from 18F-FDG PET image data, created machine learning models from the features, and verified the accuracy of the prediction of the histological grade of oral squamous cell carcinoma. The subjects were 191 patients in whom an 18F-FDG-PET examination was performed preoperatively and a histopathological grade was confirmed after surgery, and their tumor sizes were sufficient for a radiomics analysis. These patients were split in a 70%/30% ratio for use as training data and testing data, respectively. We extracted 2993 radiomics features from the PET images of each patient. Logistic Regression (LR), Support Vector Machine (SVM), Random Forest (RF), Naïve Bayes (NB), and K-Nearest Neighbor (KNN) machine learning models were created. The areas under the curve obtained from receiver operating characteristic curves for the prediction of the histological grade of oral squamous cell carcinoma were 0.72, 0.71, 0.84, 0.74, and 0.73 for LR, SVM, RF, NB, and KNN, respectively. We confirmed that a PET radiomics analysis is useful for the preoperative prediction of the histological grade of oral squamous cell carcinoma.

Cerebral hypometabolism in a pediatric patient with clinically resolved posterior reversible encephalopathy syndrome.

A 4-year-old boy with Nuclear factor-kappa B Essential Modulator deficiency syndrome presented with encephalopathy post haematopoietic stem cell transplantation. MRI demonstrated T2/FLAIR-hyperintensities in the posterior cerebral cortex concerning for posterior reversible encephalopathy syndrome. Clinical improvement was appreciated following withdrawal of the suspected offending pharmacological agent (Cyclosporine). An 18F-FDG PET/CT performed 2 months later to screen for post-transplant lymphoproliferative disease demonstrated markedly reduced FDG uptake in the posterior cerebral cortex, involving the parietal and occipital lobes. We describe, to the best of our knowledge, the first case of profound cerebral hypometabolism in a child with clinically resolved posterior reversible encephalopathy syndrome.

Comparison of the Performance of [18F]-FDG PET/CT and [18F]-FDG PET/MRI for Lymph Node Metastasis in Breast Cancer: A Systematic Review and Meta- Analysis.

OBJECTIVE: The primary objective of this study was to conduct a comparative analysis of the diagnostic efficacy of [18F]-FDG PET/CT and [18F]-FDG PET/MRI in the detection of breast cancer lymph node metastasis. METHODS: We conducted a comprehensive search on PubMed, Embase, and Web of Science databases, encompassing eligible articles until March 2023. The pooled sensitivity and specificity for [18F]-FDG PET/CT and [18F]-FDG PET/MRI have been reported as estimates with 95% Confidence Intervals (CIs) using a bivariate random-effect model. Utilizing the I square (I2) statistic, heterogeneity among pooled studies was evaluated. The quality assessment of the included studies was conducted using the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) methodology. RESULTS: We included 18 studies (2057 patients). The sensitivity, specificity, and AUC (Area Under the Curve) values of [18F]-FDG PET/CT for overall lymph node metastasis in breast cancer have been found to be 0.58 (0.39 - 0.75), 0.83 (0.69-0.92), and 0.79 (0.75-0.82), respectively. Correspondingly, the values for [18F]-FDG PET/MRI were found to be 0.76 (0.60-0.88), 0.85 (0.77-0.91), and 0.89 (0.86-0.91), respectively. The sensitivity, specificity, and AUC values of [18F]-FDG PET/CT for axillary lymph node metastasis in breast cancer were 0.52 (0.37-0.67), 0.84 (0.68-0.92), and 0.73 (0.69-0.76), respectively. Correspondingly, the values for [18F]-FDG PET/MRI were 0.84 (0.76-0.89), 0.87 (0.75-0.94), and 0.86 (0.83-0.89), respectively. CONCLUSION: This study has suggested [18F]-FDG PET/MRI to have greater diagnostic power than [18F]-FDG PET/CT in detecting lymph node metastasis in breast cancer. However, the [18F]-FDG PET/MRI results have been obtained from a small sample size study, and more and larger prospective studies are needed for further confirmation on this issue.