Atomoxetine treatment may decrease striatal dopaminergic transporter availability after 8 weeks: pilot SPECT report of three cases

Attention deficit/hyperactivity disorder is one of the most common neurodevelopmental disorders. The pathophysiology is thought to involve noradrenaline and dopamine. The role of dopamine transporter (DAT) was evaluated in imaging studies using mostly dopamine reuptake inhibitors. Atomoxetine is a selective noradrenaline reuptake inhibitor. Here we report the results of a pilot study conducted to evaluate changes in striatal DAT after 8 weeks of atomoxetine treatment. Our results suggest that 8 weeks of atomoxetine treatment may change striatal DAT bioavailability as measured via SPECT but that change was not correlated with genotype or clinical improvement

Is SUV Corrected for Lean Body Mass Superior to SUV of Body Weight in Ga-68-PSMA PET/CT?

Objectives: This study aimed to investigate the relationship between the standard uptake value (SUV) of body weight and SUV corrected for lean body mass (SUL) parameters obtained from the prostate gland in gallium-68 (Ga-68)-prostate-specific membrane antigen (PSMA) positron emission tomography-computed tomography (PET/CT) with Gleason grade (GG) groups, D'Amico risk groups, and presence of metastases

Value of volumetric and textural analysis in predicting the treatment response in patients with locally advanced rectal cancer

Objective The aim of this study was to assess the value of baseline 18F-FDG PET/CT in predicting the response to neoadjuvant chemo-radiotherapy (NCRT) in patients with locally advanced rectal cancer (LARC) via the volumetric and texture data obtained from 18F-FDG PET/CT images. Methods In total, 110 patients who had undergone NCRT after initial PET/CT and followed by surgical resection were included in this study. Patients were divided into two groups randomly as a train set (n: 88) and test set (n: 22). Pathological response using three-point tumor regression grade (TRG) and metastatic lymph nodes in PET/CT images were determined. TRG1 were accepted as responders and TRG2-3 as non-responders. Region of interest for the primary tumors was drawn and volumetric features (metabolic tumor volume (MTV) and total lesion glycolysis (TLG)) and texture features were calculated. In train set, the relationship between these features and TRG was investigated with Mann-WhitneyUtest. Receiver operating curve analysis was performed for features withp < 0.05. Correlation between features were evaluated with Spearman correlation test, features with correlation coefficient < 0.8 were evaluated with the logistic regression analysis for creating a model. The model obtained was tested with a test set that has not been used in modeling before. Results In train set 32 (36.4%) patients were responders. The rate of visually detected metastatic lymph node at baseline PET/CT was higher in non-responders than responders (71.4% and 46.9%, respectively,p = 0.022). There was a statistically significant difference between TLG, MTV, SHAPE_compacity, NGLDMcoarseness, GLRLM_GLNU, GLRLM_RLNU, GLZLM_LZHGE and GLZLM_GLNU between responders and non-responders. MTV and NGLDMcoarseness demonstrated the most significance (p = 0.011). A multivariate logistic regression analysis that included MTV, coarseness, GLZLM_LZHGE and lymph node metastasis was performed. Multivariate analysis demonstrated MTV and lymph node metastasis were the most meaningful parameters. The model's AUC was calculated as 0.714 (p = 0.001,0.606-0.822, 95% CI). In test set, AUC was determined 0.838 (p = 0.008,0.671-1.000, 95% CI) in discriminating non-responders. Conclusions Although there were points where textural features were found to be significant, multivariate analysis revealed no diagnostic superiority over MTV in predicting treatment response. In this study, it was thought higher MTV value and metastatic lymph nodes in PET/CT images could be a predictor of low treatment response in patients with LARC

Prevalence and Localization of Hibernating Myocardium Among Patients with Left Ventricular Dysfunction

Objective: This study evaluated how much of the myocardium was hibernating in patients with left ventricle dysfunction and/or comorbidities who planned to undergo either surgical or interventional revascularization. Furthermore, this study also identified which irrigation areas of the coronary arteries presented more scar and hibernating tissue

Does lymph node localization affect prostate-specific membrane antigen uptake?

Objective To investigate the relationship between lymph node (LN) size and localization and prostate-specific membrane antigen (PSMA) uptake in patients with prostate cancer

EVALUATION OF TUMOR BURDEN RESPONSE TO SINGLE-CYCLE OF Lu-177 PSMA TREATMENT WITH WHOLE BODY SCINTIGRAPHIC PLANAR IMAGES IN PROSTATE CANCER PATIENTS

Purpose: The aim of this study was to evaluate treatment response and survival with post-therapy images in patients who received one cycle of Lu-177 PSMA I&T treatment. Material and Methods: After Lu-177 PSMA I&T treatment was administered to 54 patients, maximum count, pixel count (tumor extent) and sum (total tumor burden) values were calculated with a semiautomatic program. The images after the first treatment were evaluated as basal disease images. Images obtained after the second treatment were considered the response to the first cycle treatment. Results: It was determined that the number of maximum counts (p: 0.015) and tumor extent (p: 0.014) were significantly reduced after one cycle of Lu177 PSMA treatment. No significant change in total tumor burden (p:0.206) was detected. After one treatment cycle the maximum count in 46% of the patients and the total tumor burden in 63% of the patients. The number of pixels (tumor prevalence) in 41% of the patients decreased by >= 25%. Based on the Naive-Bayes method, one-year survival accuracy was 71.6%. Conclusion: With the texture analysis and machine learning of the Lu-177 PSMA post-therapy images, treatment response and survival were determined with high accuracy

Dual time point imaging of staging PSMA PET/CT quantification; spread and radiomic analyses

Objective The aims were to evaluate the performance of models that predict Gleason Grade (GG) groups with radiomic data obtained from the prostate gland in dual time 68Ga-Prostate Specific Membrane Antigen (PSMA) Positron Emission Tomography/Computerized Tomography (PET/CT) images for prostate cancer (PCa) staging, and to analyze the contribution of late imaging to the radiomic model and to evaluate the relationship of the distance between tumor foci in the body (Dmax) obtained in early PET images with histopathology and prostate specific antigen (PSA) value. Methods Between October 2020 and August 2021, 41 patients who underwent 68Ga-PSMA PET/CT for staging of PCa were retrospectively analyzed. Volumetric and radiomics data were obtained from early and late PSMA PET images. The differences between age, metastasis status, PSA, standard uptake value (SUV), volumetric and radiomics parameters between GG groups were analyzed. Early and late PET radiomic models were created, area under curve (AUC), sensitivity, specificity and accuracy values of the models were obtained. In addition, the correlation of Dmax values with total PSMA-tumor volume (TV), Total lesion (TL)-PSMA and PSA values was evaluated. In metastatic patients, the difference in Dmax between GG groups was analyzed. Results There was a significant difference between patients with GG 3 in 35 of the early PET radiomic features. In the early PET model, multivariate analyses showed that GLRLM_RLNU and PSA were the most meaningful parameters. The AUC, sensitivity, specificity and accuracy values of the early model in detecting patients with GG > 3 were calculated as 0.902, 76.2%, 84% and 78.1%, respectively. In 36 late PET radiomic features, there was a significant difference between patients with GG 3. In multivariate analyses; SHAPE_compacity and PSA were obtained as the most meaningful parameters. The AUC, sensitivity, specificity and accuracy values of the late model in detecting patients with GG > 3 were calculated as 0.924, 85.7%, 85% and 85.4%. There was a strong correlation between Dmax and PSA values (p 3 group were higher than GG <= 3 group; A statistically significant difference was obtained between these two groups (p = 0.023). Conclusions Model generated from the late PSMA PET radiomic data had better performance in the current study. Without the use of invasive methods, the heterogeneity and aggressiveness of the primary tumor and the prediction of GG groups may be possible with 68Ga-PSMA PET/CT images obtained for diagnostic purposes especially with late PSMA PET/CT imaging

Machine learning for differentiating metastatic and completely responded sclerotic bone lesion in prostate cancer: a retrospective radiomics study

Objective: Using CT texture analysis and machine learning methods, this study aims to distinguish the lesions imaged via 68Ga-prostate-specific membrane antigen (PSMA) positron emission tomography (PET)/CT as metastatic and completely responded in patients with known bone metastasis and who were previously treated