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.

Targeted radionuclide therapy directed to the tumor phenotypes: A dosimetric approach using MC simulations.

BACKGROUND: In Targeted Radionuclide Therapy (TRT), the continuous technological effort in imaging tumor phenotypes (i.e. sub-volumes with different phenotypic characteristics) and in precise radiopharmaceutical tumor-targeting, is allowing for a better dosimetric optimization at the tumor phenotype level. The aim of this study was to evaluate the dosimetric efficiency (considering strategic absorbed dose delivery to the phenotypes) of personalized TRT directed to the tumor phenotypes. METHODS: The dosimetric assessment was performed using a four-phenotype realistic tumor model implemented within the ICRP reference voxel phantom and simulations using the state-of-the-art Monte Carlo program PENELOPE. The dose assessment was performed for five radionuclides commonly used in therapy and/or diagnostic procedures: 125I, 99mTc, 177Lu, 161Tb and 67Ga. Two irradiation scenarios were considered: (i) the Whole Tumor Treatment Planning Scenario (WTTPS), i.e. the four phenotypes irradiated with the same radionuclide; (ii) the Phenotype Treatment Planning Scenario (PTPS), i.e. each phenotype irradiated by a single radionuclide. The optimal radionuclide configurations were studied considering the maximization of the absorbed dose delivered to the tumor and the minimization of dose to healthy tissues. RESULTS: In WTTPS, 125I outperforms the other radionuclides in terms of the ratio of the maximum absorbed dose delivered to the tumor and the minimum absorbed dose delivered to healthy tissues. In the PTPS, the use of 161Tb in combination with the other radionuclides maximizes the absorbed dose in the tumor tissues while simultaneously minimizing dose to healthy tissue, compared to the WTTPS. In agreement with recent pre-clinical studies, our computational results confirm and indicate the beneficial additive dosimetric effects of Auger and conversion electrons of 161Tb with respect to 177Lu, when considering the same cumulated activity for both. Interestingly, in considering a realistic tumor model, the better dosimetric performances of 161Tb were confirmed also for tumor volumes ranging from 1.98 cm3 to 33.32 cm3. CONCLUSIONS: Dose assessment in realistic non-homogeneous tumor models could provide more insights with respect to consider only homogenous water-spheres tumor models and should be taken into account in dosimetry-based TRT planning studies.

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.

Positron Emission Tomography-Derived Metrics Predict the Probability of Local Relapse After Oligometastasis-Directed Ablative Radiation Therapy.

PURPOSE: Early positron emission tomography-derived metrics post-oligometastasis radioablation may predict impending local relapses (LRs), providing a basis for a timely ablation. METHODS AND MATERIALS: Positron emission tomography data of 623 lesions treated with either 24 Gy single-dose radiation therapy (SDRT) (n = 475) or 3 ×  9 Gy stereotactic body radiation therapy (SBRT) (n = 148) were analyzed in a training data set (n = 246) to obtain optimal cutoffs for pretreatment maximum standardized uptake value (SUVmax) and its 3-month posttreatment decline (ΔSUVmax) in predicting LR risk, validated in a data set unseen to testing (n = 377). RESULTS: At a median of 21.7 months, 91 lesions developed LRs: 39 of 475 (8.2%) after SDRT and 52 of 148 (35.1%) after SBRT. The optimal cutoff values were 12 for SUVmax and -75% for ΔSUVmax. Bivariate SUVmax/ΔSUVmax permutations rendered a 3-tiered LR risk stratification of dual-favorable (low risk), 1 adverse (intermediate risk) and dual-adverse (high risk). Actuarial 5-year local relapse-free survival rates were 93.9% versus 89.6% versus 57.1% (P < .0001) and 76.1% versus 48.3% versus 8.2% (P < .0001) for SDRT and SBRT, respectively. The SBRT area under the ROC curve was 0.71 (95% CI, 0.61-0.79) and the high-risk subgroup yielded a 76.5% true positive LR prediction rate. CONCLUSIONS: The SBRT dual-adverse SUVmax/ΔSUVmax category LR prediction power provides a basis for prospective studies testing whether a timely ablation of impending LRs affects oligometastasis outcomes.

Parkinson's disease is overdiagnosed clinically at baseline in diagnostically uncertain cases: a 3-year European multicenter study with repeat [123I]FP-CIT SPECT.

Overdiagnosis of Parkinson's disease (PD) is suggested by specialist review of community diagnosis, and in postmortem studies. In specialist centers 4 to 15% of patients entered into clinical trials as early PD do not have functional imaging support for a PD diagnosis. In a European multicenter, prospective, longitudinal study, we compared clinical diagnosis with functional SPECT imaging using [123I]FP-CIT (DaTSCAN, GE Healthcare). Repeat observations were performed over 3 years in patients with tremor and/or parkinsonism in whom there was initial diagnostic uncertainty between degenerative parkinsonism and nondegenerative tremor disorders. Video-recording of clinical features was scored independently of functional imaging results by two blinded clinicians at 36 months (= gold standard clinical diagnosis). Three readers, unaware of the clinical diagnosis, classified the images as normal or abnormal by visual inspection. The main endpoint was the sensitivity and specificity of SPECT imaging at baseline compared with the gold standard. In 99 patients completing the three serial assessments, on-site clinical diagnosis overdiagnosed degenerative parkinsonism at baseline in diagnostically uncertain cases compared with the gold standard clinical diagnosis (at 36 months), the latter giving a sensitivity of 93% and specificity of 46%. The corresponding baseline [123I]FP-CIT SPECT results showed a mean sensitivity of 78% and a specificity of 97%. Inter-reader agreement for rating scans as normal or abnormal was high (Cohen's kappa = 0.94-0.97).

Phenotype-Oriented Ablation of Oligometastatic Cancer with Single Dose Radiation Therapy.

PURPOSE: The current oligometastatic (OM) model postulates that the disease evolves dynamically with sequential emergence of OM (SOM) lesions requiring successive rounds of SOM ablation to afford tumor cure. The present phase 2 study explores the ablative efficacy of 24 Gy single-dose radiation therapy (SDRT), its feasibility in diverse OM settings, and the impact of radioablation on polymetastatic (PM) dissemination. METHODS AND MATERIALS: One hundred seventy-five consecutive patients with 566 OM or SOM lesions underwent periodic positron emission tomography/computed tomography (PET/CT) imaging to stage the disease before treatment, determine tumor response, and monitor timing of PM conversion after SDRT. When 24 Gy SDRT was restricted by dose or volume constraints of serial normal organs, radioablation was diverted to a nontoxic 3×9 Gy SBRT schedule. RESULTS: SOM/SOMA occurred in 42% of the patients, and 24 Gy SDRT was feasible in 76% of the lesions. Despite 92% actuarial 5-year OM ablation by 24 Gy SDRT, respective PM-free survival (PMFS) was 26%, indicating PM conversion dominates over effective OM radioablation in many patients. Multivariate analysis of OM metrics derived from staging PET/CT scanning before first treatment predicted PMFS outcome after SDRT. Bivariate analysis of dichotomized high versus low baseline metric combinations of CT-derived tumor load (cutoff at 14.8 cm3) and PET-derived metabolic SUVmax (cutoff at 6.5) yielded a 3-tiered PMFS categorization of 89%, 58% and 17% actuarial 5-year PMFS in categories 1, 2, and 3, respectively (P < .001), defining OM disease as a syndrome of diverse clinical and prognostic phenotypes. CONCLUSION: Long-term risk of PM dissemination, predicted by preablation PET/CT staging, provides guidelines for phenotype-oriented OM therapy. In categories 1 and 2, radioablation should be a primary therapeutic element when pursuing tumor cure, whereas in the PM-prone category 3, radioablation should be a component of multimodal trials addressing primarily the risk of PM dissemination. PET/CT baseline staging also provides a platform for discovery of pharmacologically accessible PM drivers as targets for new phenotype-oriented treatment protocols.