Baseline [18F]FDG PET/CT and MRI first-order breast tumor features do not improve pathological complete response prediction to neoadjuvant chemotherapy.

PURPOSE: To verify the ability of pretreatment [18F]FDG PET/CT and T1-weighed dynamic contrast-enhanced MRI to predict pathological complete response (pCR) after neoadjuvant chemotherapy (NAC) in breast cancer (BC) patients. METHODS: This retrospective study includes patients with BC of no special type submitted to baseline [18F]FDG PET/CT, NAC and surgery. [18F]FDG PET-based features reflecting intensity and heterogeneity of tracer uptake were extracted from the primary BC and suspicious axillary lymph nodes (ALN), for comparative analysis related to NAC response (pCR vs. non-pCR). Multivariate logistic regression was performed for response prediction combining the breast tumor-extracted PET-based features and clinicopathological features. A subanalysis was performed in a patients' subsample by adding breast tumor-extracted first-order MRI-based features to the multivariate logistic regression. RESULTS: A total of 170 tumors from 168 patients were included. pCR was observed in 60/170 tumors (20/107 luminal B-like, 25/45 triple-negative and 15/18 HER2-enriched surrogate molecular subtypes). Higher intensity and higher heterogeneity of [18F]FDG uptake in the primary BC were associated with NAC response in HER2-negative tumors (immunohistochemistry score 0, 1 + or 2 + non-amplified by in situ hybridization). Also, higher intensity of tracer uptake was observed in ALN in the pCR group among HER2-negative tumors. No [18F]FDG PET-based features were associated with pCR in the other subgroup analyses. A subsample of 103 tumors was also submitted to extraction of MRI-based features. When combined with clinicopathological features, neither [18F]FDG PET nor MRI-based features had additional value for pCR prediction. The only significant predictors were estrogen receptor status, HER2 expression and grade. CONCLUSION: Pretreatment [18F]FDG PET-based features from primary BC and ALN are not associated with response to NAC, except in HER2-negative tumors. As compared with pathological features, no breast tumor-extracted PET or MRI-based feature improved response prediction.

Evaluation of Semiautomatic and Deep Learning-Based Fully Automatic Segmentation Methods on [18F]FDG PET/CT Images from Patients with Lymphoma: Influence on Tumor Characterization.

The objective is to assess the performance of seven semiautomatic and two fully automatic segmentation methods on [18F]FDG PET/CT lymphoma images and evaluate their influence on tumor quantification. All lymphoma lesions identified in 65 whole-body [18F]FDG PET/CT staging images were segmented by two experienced observers using manual and semiautomatic methods. Semiautomatic segmentation using absolute and relative thresholds, k-means and Bayesian clustering, and a self-adaptive configuration (SAC) of k-means and Bayesian was applied. Three state-of-the-art deep learning-based segmentations methods using a 3D U-Net architecture were also applied. One was semiautomatic and two were fully automatic, of which one is publicly available. Dice coefficient (DC) measured segmentation overlap, considering manual segmentation the ground truth. Lymphoma lesions were characterized by 31 features. Intraclass correlation coefficient (ICC) assessed features agreement between different segmentation methods. Nine hundred twenty [18F]FDG-avid lesions were identified. The SAC Bayesian method achieved the highest median intra-observer DC (0.87). Inter-observers' DC was higher for SAC Bayesian than manual segmentation (0.94 vs 0.84, p < 0.001). Semiautomatic deep learning-based median DC was promising (0.83 (Obs1), 0.79 (Obs2)). Threshold-based methods and publicly available 3D U-Net gave poorer results (0.56 ≤ DC ≤ 0.68). Maximum, mean, and peak standardized uptake values, metabolic tumor volume, and total lesion glycolysis showed excellent agreement (ICC ≥ 0.92) between manual and SAC Bayesian segmentation methods. The SAC Bayesian classifier is more reproducible and produces similar lesion features compared to manual segmentation, giving the best concordant results of all other methods. Deep learning-based segmentation can achieve overall good segmentation results but failed in few patients impacting patients' clinical evaluation.

123I-FP-CIT SPECT in dementia with Lewy bodies, Parkinson's disease and Alzheimer's disease: a new quantitative analysis of autopsy confirmed cases.

PURPOSE: The aim of this study was to re-evaluate the differentiation of patients with dementia with Lewy bodies (DLB) from Alzheimer's disease (AD) and Parkinson's disease (PD) using a quantitative analysis of 123I-FP-CIT SPECT scans. METHODS: Thirty-six patients with in vivo 123I-FP-CIT SPECT and neuropathological diagnoses were included. Based on neuropathological criteria, patients were further subclassified into nine AD, eight DLB, ten PD and nine with other diagnoses. An additional 16 healthy controls (HC) scanned with 123I-FP-CIT SPECT were also included. All images were visually assessed as normal versus abnormal uptake by consensus of five nuclear medicine physicians. Bihemispheric mean was calculated for caudate binding potential (CBP), putamen binding potential (PBP) and putamen-to-caudate ratio (PCR). RESULTS: Patients with DLB had significantly lower CBP and PBP than patients with AD and significantly higher PCR than patients with PD. Qualitative visual analysis of the images gave an accuracy of 88% in the evaluation of the status of the nigrostriatal pathway considering all individuals, and 96% considering only the patients with PD, AD and DLB. Quantitative analyses provided a balanced accuracy of 94%, 94% and 100% in binary classifications DLB versus AD, DLB versus PD and PD versus AD, respectively, and an accuracy of 93% in the differentiation among patients with DLB, AD and PD simultaneously. No statistically significant differences were observed between the AD and HC. CONCLUSIONS: This study demonstrates a very high diagnostic accuracy of the quantitative analysis of(123I-FP-CIT SPECT data to differentiate among patients with DLB, PD and AD.

Are lesion features reproducible between 18F-FDG PET/CT images when acquired on analog or digital PET/CT scanners?

OBJECTIVES: To compare lesion features extracted from 18F-FDG PET/CT images acquired on analog and digital scanners, on consecutive imaging data from the same subjects. METHODS: Whole-body 18F-FDG PET/CT images from 55 oncological patients were acquired twice after a single 18F-FDG injection, with a digital and an analog PET/CT scanner, alternately. Twenty-nine subjects were examined first on the digital, and 26 first on the analog equipment. Image reconstruction was performed using manufacturer standard clinical protocols and protocols that fulfilled EARL1 specifications. Twenty-five features based on lesion standardized uptake value (SUV) and geometry were assessed. To compare these features, intraclass correlation coefficient (ICC), relative difference (RD), absolute value of RD (|RD|), and repeatability coefficient (RC) were used. RESULTS: In total, 323 18F-FDG avid lesions were identified. High agreement (ICC > 0.75) was obtained for most of the lesion features pulled out from both scanners' imaging data, especially when reconstruction protocols fulfilled EARL1 specifications. For EARL1 reconstruction images, the features frequently used in clinics, SUVmax, SUVpeak, SUVmean, metabolic tumor volume, and total lesion glycolysis, reached an ICC of 0.92, 0.95, 0.87, 0.98, and 0.98, and a median RD (digital-analog) of 3%, 5%, 4%, - 3% and 1%, respectively. Using standard reconstruction protocols, the ICC were 0.84, 0.93, 0.80, 0.98, and 0.98, and the RD were 20%, 11%, 13%, - 7%, and 7%, respectively. CONCLUSION: Under controlled acquisition and reconstruction parameters, most of the features studied can be used for research and clinical work. This is especially important for multicenter studies and patient follow-ups. KEY POINTS: • Using manufacturer standard clinical reconstruction protocols, lesions SUV was significantly higher when using the digital scanner, especially the SUVmax that was approximately 20% higher. • High agreement was obtained for the majority of the lesion features when using reconstruction protocols that fulfilled EARL1 specifications. • Longitudinal patient studies can be performed interchangeably between digital and analog scanners when both fulfill EARL1 specifications.

Negative affect and stress-related brain metabolism in patients with metastatic breast cancer.

BACKGROUND: Cancer and its treatment represent major stressors requiring that patients make multiple adaptations. Despite evidence that poor adaptation to stressors is associated with more distress and negative affect (NA), neuroimmune dysregulation and poorer health outcomes, current understanding is very limited of how NA covaries with central nervous system changes to account for these associations. METHODS: NA was correlated with brain metabolic activity using 18 F-fluorodeoxyglucose positron emission tomography/computed tomography (18 F-FDG PET/CT) in several regions of interest in 61 women with metastatic breast cancer. Patients underwent 18 F-FDG PET/CT and completed an assessment of NA using the Brief Symptom Inventory. RESULTS: Regression analyses revealed that NA was significantly negatively correlated with the standardized uptake value ratio of the insula, thalamus, hypothalamus, ventromedial prefrontal cortex, and lateral prefrontal cortex. Voxel-wise correlation analyses within these 5 regions of interest demonstrated high left-right symmetry and the highest NA correlations with the anterior insula, thalamus (medial and ventral portion), lateral prefrontal cortex (right Brodmann area 9 [BA9], left BA45, and right and left BA10 and BA8), and ventromedial prefrontal cortex (bilateral BA11). CONCLUSIONS: The regions of interest most strongly negatively associated with NA represent key areas for successful adaptation to stressors and may be particularly relevant in patients with metastatic breast cancer who are dealing with multiple challenges of cancer and its treatment.

Extraction, selection and comparison of features for an effective automated computer-aided diagnosis of Parkinson's disease based on [123I]FP-CIT SPECT images.

PURPOSE: This work aimed to assess the potential of a set of features extracted from [123I]FP-CIT SPECT brain images to be used in the computer-aided "in vivo" confirmation of dopaminergic degeneration and therefore to assist clinical decision to diagnose Parkinson's disease. METHODS: Seven features were computed from each brain hemisphere: five standard features related to uptake ratios on the striatum and two features related to the estimated volume and length of the striatal region with normal uptake. The features were tested on a dataset of 652 [123I]FP-CIT SPECT brain images from the Parkinson's Progression Markers Initiative. The discrimination capacities of each feature individually and groups of features were assessed using three different machine learning techniques: support vector machines (SVM), k-nearest neighbors and logistic regression. RESULTS: Cross-validation results based on SVM have shown that, individually, the features that generated the highest accuracies were the length of the striatal region (96.5%), the putaminal binding potential (95.4%) and the striatal binding potential (93.9%) with no statistically significant differences among them. The highest classification accuracy was obtained using all features simultaneously (accuracy 97.9%, sensitivity 98% and specificity 97.6%). Generally, slightly better results were obtained using the SVM with no statistically significant difference to the other classifiers for most of the features. CONCLUSIONS: The length of the striatal region uptake is clinically useful and highly valuable to confirm dopaminergic degeneration "in vivo" as an aid to the diagnosis of Parkinson's disease. It compares fairly well to the standard uptake ratio-based features, reaching, at least, similar accuracies and is easier to obtain automatically. Thus, we propose its day to day clinical use, jointly with the uptake ratio-based features, in the computer-aided diagnosis of dopaminergic degeneration in Parkinson's disease.

Greater perceived stress management skills and heightened brain metabolic activity in cortical and subcortical stress processing regions in metastatic breast cancer patients.

PURPOSE: Emotional distress and adversity can contribute to negative health outcomes in women with breast cancer. Individual differences in perceived stress management skills such as cognitive reframing and relaxation for coping with adversity have been shown to predict less distress and better psychological and physiological adaptation. Prior work shows that more distressed breast cancer patients reveal less metabolic activity in brain regions such as the insula, thalamus, ventromedial and lateral prefrontal cortices. This led us to pose the hypothesis that breast cancer patients with greater stress management skills (e.g., ability to reframe stressors and use relaxation) may conversely show greater activation in these brain regions and thereby identify brain activity that may be modifiable through stress management interventions. The main objective of this study was to examine the association of perceived stress management skill efficacy with the metabolism of 9 key stress-implicated brain regions in women diagnosed with metastatic breast cancer. METHODS: Sixty women (mean age 59.86 ± 10.04) with a diagnosis of mBC underwent 18F-fluorodeoxyglucose positron emission tomography. Perceived stress management skill efficacy was assessed with the Measure of Current Status Scale. RESULTS: Greater perceived stress management skill efficacy related significantly to higher metabolic activity in the insula, thalamus, ventromedial and lateral prefrontal cortices, and basal ganglia; this network of regions overlaps with those previously shown to be under-activated with greater level of distress in this same sample of metastatic breast cancer patients. CONCLUSION: This is the first study to demonstrate in metastatic cancer patients that greater perceptions of stress management skill efficacy are associated with metabolic activity in key brain regions and paves the way for future studies tracking neural mechanisms sensitive to change following stress management interventions for this population.

Striatal dopamine D2-like receptors availability in obesity and its modulation by bariatric surgery: a systematic review and meta-analysis.

There is significant evidence linking a 'reward deficiency syndrome' (RDS), comprising decreased availability of striatal dopamine D2-like receptors (DD2lR) and addiction-like behaviors underlying substance use disorders and obesity. Regarding obesity, a systematic review of the literature with a meta-analysis of such data is lacking. Following a systematic review of the literature, we performed random-effects meta-analyses to determine group differences in case-control studies comparing DD2lR between individuals with obesity and non-obese controls and prospective studies of pre- to post-bariatric surgery DD2lR changes. Cohen's d was used to measure effect size. Additionally, we explored factors potentially associated with group differences in DD2lR availability, such as obesity severity, using univariate meta-regression. In a meta-analysis including positron emission tomography (PET) and single-photon emission computed tomography (SPECT) studies, striatal DD2lR availability did not significantly differ between obesity and controls. However, in studies comprising patients with class III obesity or higher, group differences were significant, favoring lower DD2lR availability in the obesity group. This effect of obesity severity was corroborated by meta-regressions showing inverse associations between the body mass index (BMI) of the obesity group and DD2lR availability. Post-bariatric changes in DD2lR availability were not found, although a limited number of studies were included in this meta-analysis. These results support lower DD2lR in higher classes of obesity which is a more targeted population to explore unanswered questions regarding the RDS.

Differentiation of frontotemporal dementia from dementia with Lewy bodies using FP-CIT SPECT.

INTRODUCTION: There is increasing evidence that imaging with [123I]FP-CIT SPECT is helpful in differentiating dementia with Lewy bodies (DLB) from Alzheimer's disease (AD) but it is not known how well the scan performs in differentiating DLB from frontotemporal dementia (FTD). METHOD: We compared the striatal dopamine transporter (DAT) binding in FTD (n=12), DLB (n=10) and AD (n=9) by visually rating the caudate and putamen on [123I]FP-CIT SPECT scans. RESULTS: The majority (9/10) of DLB cases had an abnormal scan and a significant reduction of uptake of DAT binding in the putamen and the caudate. A third (4/12) of the FTD cases also had an abnormal scan and a significant reduction in uptake in the putamen and the caudate. In contrast, only one out of nine AD cases had an abnormal scan. Significant differences were found when comparisons were made between the groups for visual analysis of the entire scan (p=0.001) and the four regions of interest (p=0.001 - 0.013). In contrast to the AD group (specificity of scan 89%), the specificity of [123I]FP-CIT SPECT scans was reduced in the FTD group to 67%. Three quarters of the study population had at least one extrapyramidal motor sign (EPMS), with bradykinesia being the most common EPMS in both FTD (83%) and DLB (70%). CONCLUSIONS: This study highlights to clinicians that a positive (abnormal) [123I]FP-CIT SPECT scan, even in a patient with an EPMS, does not exclude the diagnosis of FTD and emphasises the importance of a comprehensive clinical evaluation and a detailed cognitive assessment.

Patlak plot based on the first 30 minutes post-injection dynamic 18F-florbetaben positron emission tomography scan separates amyloid-ß positive from negative studies.

OBJECTIVE: This work aims to search for the shortest duration of an early 18F-florbetaben positron emission tomography (PET) dynamic acquisition to obtain reliable information on the brain amyloid-ß (Aß) deposition and perfusion. METHODS: 25 patients that underwent an early 18F-florbetaben PET dynamic acquisition starting immediately post-injection (maximum of 60 min duration) were retrospectively included. Reference region-based Patlak plot [Formula: see text] (transference rate to the irreversible compartment) and [Formula: see text] (distribution volume) were computed. Shorter early dynamic acquisitions were simulated to a minimum of 15 min duration. Three nuclear medicine physicians evaluated qualitatively the [Formula: see text] parametric images obtained in comparison with those obtained from the standard clinical protocol defined by a late acquisition of 20 min duration starting 90 min post-injection. RESULTS: All the [Formula: see text] parametric images obtained with at least an early 30-min dynamic acquisitions were suitable for visual classification. Shorter early acquisitions originated images with too much noise, making qualitative assessment difficult. Aß deposition visual classification based on the [Formula: see text] images were highly concordant with the evaluation of standard late acquisitions (readers consensus agreement of 92%). [Formula: see text] images obtained from the different early dynamic acquisition's duration were visually indistinguishable from each other (voxelwise r ≥ 0.98). CONCLUSION: Patlak plot method applied to early 30-min 18F-florbetaben PET dynamic acquisition may be an alternative to the dual acquisition protocol sometimes used in clinics. This improves patients' comfort, service logistics and reduces radiation exposure. ADVANCES IN KNOWLEDGE: This work shows, for the first time, that early (0-30 min post-injection) 18F-florbetaben dynamic PET scans with reference region-based Patlak plot method could replace the dual acquisition protocol and the 90-110 min standard acquisition.

(123)I-FP-CIT SPET striatal uptake in parkinsonian patients with the alpha-synuclein (G209A) mutation A.

Autosomal dominant familial Parkinson's disease (PD) due to the alpha-synuclein (G209A) mutation shares similar clinical characteristics with sporadic PD. Pathological studies however indicate more widespread neuronal degeneration in the familial form. We performed (123)I-FP-CIT SPET (DaTSCAN) study in nine patients with familial PD carrying the alpha-synuclein (G209A) mutation and fifteen matched patients with sporadic disease. Both groups had equal radioligand reduction uptake in the striatum but the alpha-synuclein patients showed less asymmetry and increased putamen to caudate ratio. Our findings indicate that there are minor differences in DAT SPET parameters between alpha-synuclein and sporadic PD patients insufficient to provide differential diagnosis.

Gastric GIST Incidentally Detected on 68Ga-PSMA-PET/CT: Correlation Between Functional Imaging and Histology.

Prostate-specific membrane antigen (PSMA) is specific for prostate cancer cells; nevertheless when finding uptake in abnormal locations for prostate cancer metastases, it is important to consider other hypothesis, including second cancers. There are several papers about PSMA expression in many different types of cancer, but few reported expression in gastrointestinal stromal tumors (GIST). In this case, we documented the GIST lesion not only by PET/CT but also by gastroscopy and histology. Additionally, PSMA immunochemistry was performed, showing PSMA expression in tumoral GIST cells (not in endothelial cells), evidencing a good correlation between PET/CT image and histology.

Dementia with Lewy bodies: a comparison of clinical diagnosis, FP-CIT single photon emission computed tomography imaging and autopsy.

BACKGROUND: Dementia with Lewy bodies (DLB) is a common form of dementia. The presence of Alzheimer's disease (AD) pathology modifies the clinical features of DLB, making it harder to distinguish DLB from AD clinically during life. Clinical diagnostic criteria for DLB applied at presentation can fail to identify up to 50% of cases. Our aim was to determine, in a series of patients with dementia in whom autopsy confirmation of diagnosis was available, whether functional imaging of the nigrostriatal pathway improves the accuracy of diagnosis compared with diagnosis by means of clinical criteria alone. METHODS: A single photon emission computed tomography (SPECT) scan was carried out with a dopaminergic presynaptic ligand [123I]-2beta-carbometoxy-3beta-(4-iodophenyl)-N-(3-fluoropropyl) nortropane (FP-CIT; ioflupane) on a group of patients with a clinical diagnosis of DLB or other dementia. An abnormal scan was defined as one in which right and left posterior putamen binding, measured semiquantitatively, was more than 2 SDs below the mean of the controls. RESULTS: Over a 10 year period it was possible to collect 20 patients who had been followed from the time of first assessment and time of scan through to death and subsequent detailed neuropathological autopsy. Eight patients fulfilled neuropathological diagnostic criteria for DLB. Nine patients had AD, mostly with coexisting cerebrovascular disease. Three patients had other diagnoses. The sensitivity of an initial clinical diagnosis of DLB was 75% and specificity was 42%. The sensitivity of the FP-CIT scan for the diagnosis of DLB was 88% and specificity was 100%. CONCLUSION: FP-CIT SPECT scans substantially enhanced the accuracy of diagnosis of DLB by comparison with clinical criteria alone.