Healthy lifestyle and prostate cancer risk in the Million Veteran Program.

BACKGROUND: This study aims to assess the impact of healthy lifestyle on prostate cancer (PCa) risk in a diverse population. METHODS: Data for 281,923 men from the Million Veteran Program (MVP), a nationwide, health system-based cohort study, were analyzed. Self-reported information at enrollment included smoking status, exercise, diet, family history of PCa, and race/ethnicity. Body mass index (BMI) was obtained from clinical records. Genetic risk was assessed via a validated polygenic score. Cox proportional hazards models were used to assess associations with PCa outcomes. RESULTS: After accounting for ancestry, family history, and genetic risk, smoking was associated with an increased risk of metastatic PCa (hazard ratio [HR], 1.83; 95% confidence interval [CI], 1.64-2.02; p < 10-16) and fatal PCa (HR, 2.73; 95% CI, 2.36-3.25; p < 10-16). Exercise was associated with a reduced risk of fatal PCa (HR, 0.86; 95% CI, 0.76-0.98; p = .03). Higher BMI was associated with a slightly reduced risk of fatal PCa, and diet score was not independently associated with any end point. Association with exercise was strongest among those who had nonmetastatic PCa at MVP enrollment. Absolute reductions in the risk of fatal PCa via lifestyle factors were greatest among men of African ancestry (1.7% for nonsmokers vs. 6.1% for smokers) or high genetic risk (1.4% for nonsmokers vs. 4.3% for smokers). CONCLUSIONS: Healthy lifestyle is minimally related to the overall risk of developing PCa but is associated with a substantially reduced risk of dying from PCa. In multivariable analyses, both exercise and not smoking remain independently associated with reduced metastatic and fatal PCa.

Agent orange exposure and prostate cancer risk in the million veteran program.

BACKGROUND: The US government considers veterans to have been exposed to Agent Orange if they served in Vietnam while the carcinogen was in use, and these veterans are often deemed at high risk of prostate cancer (PCa). Here, we assess whether presumed Agent Orange exposure is independently associated with increased risk of any metastatic or fatal PCa in a diverse Veteran cohort still alive in the modern era (at least 2011), when accounting for race/ethnicity, family history, and genetic risk. PATIENTS AND METHODS: Participants in the Million Veteran Program (MVP; enrollment began in 2011) who were on active duty during the Vietnam War era (August 1964-April 1975) were included (n = 301,470). Agent Orange exposure was determined using the US government definition. Genetic risk was assessed via a validated polygenic hazard score. Associations with age at diagnosis of any PCa, metastatic PCa, and death from PCa were assessed via Cox proportional hazards models. RESULTS AND INTERPRETATION: On univariable analysis, exposure to Agent Orange was not associated with increased PCa (hazard ratio [HR]: 1.02, 95% confidence interval [CI]: 1.00-1.04, p = 0.06), metastatic PCa (HR: 0.98, 95% CI: 0.91-1.05, p = 0.55), or fatal PCa (HR: 0.94, 95% CI: 0.79-1.09, p = 0.41). When accounting for race/ethnicity and family history, Agent Orange exposure was independently associated with slightly increased risk of PCa (HR: 1.06, 95% CI: 1.04-1.09, <10-6) but not with metastatic PCa (HR: 1.07, 95% CI: 0.98-1.15, p = 0.10) or PCa death (HR: 1.02, 95% CI: 0.83-1.23, p = 0.09). Similar results were found when accounting for genetic risk. Agent Orange exposure history may not improve modern PCa risk stratification.

An accessible deep learning tool for voxel-wise classification of brain malignancies from perfusion MRI.

Noninvasive differential diagnosis of brain tumors is currently based on the assessment of magnetic resonance imaging (MRI) coupled with dynamic susceptibility contrast (DSC). However, a definitive diagnosis often requires neurosurgical interventions that compromise patients' quality of life. We apply deep learning on DSC images from histology-confirmed patients with glioblastoma, metastasis, or lymphoma. The convolutional neural network trained on ∼50,000 voxels from 40 patients provides intratumor probability maps that yield clinical-grade diagnosis. Performance is tested in 400 additional cases and an external validation cohort of 128 patients. The tool reaches a three-way accuracy of 0.78, superior to the conventional MRI metrics cerebral blood volume (0.55) and percentage of signal recovery (0.59), showing high value as a support diagnostic tool. Our open-access software, Diagnosis In Susceptibility Contrast Enhancing Regions for Neuro-oncology (DISCERN), demonstrates its potential in aiding medical decisions for brain tumor diagnosis using standard-of-care MRI.

Agent Orange exposure and prostate cancer risk in the Million Veteran Program.

Purpose: Exposure to Agent Orange, a known carcinogen, might increase risk of prostate cancer (PCa). We sought to investigate the association of Agent Orange exposure and PCa risk when accounting for race/ethnicity, family history, and genetic risk in a diverse population of US Vietnam War veterans. Methods & Materials: This study utilized the Million Veteran Program (MVP), a national, population-based cohort study of United States military veterans conducted 2011-2021 with 590,750 male participants available for analysis. Agent Orange exposure was obtained using records from the Department of Veterans Affairs (VA) using the US government definition of Agent Orange exposure: active service in Vietnam while Agent Orange was in use. Only veterans who were on active duty (anywhere in the world) during the Vietnam War were included in this analysis (211,180 participants). Genetic risk was assessed via a previously validated polygenic hazard score calculated from genotype data. Age at diagnosis of any PCa, diagnosis of metastatic PCa, and death from PCa were assessed via Cox proportional hazards models. Results: Exposure to Agent Orange was associated with increased PCa diagnosis (HR 1.04, 95% CI 1.01-1.06, p=0.003), primarily among Non-Hispanic White men (HR 1.09, 95% CI 1.06- 1.12, p<0.001). When accounting for race/ethnicity and family history, Agent Orange exposure remained an independent risk factor for PCa diagnosis (HR 1.06, 95% CI 1.04-1.09, p<0.05). Univariable associations of Agent Orange exposure with PCa metastasis (HR 1.08, 95% CI 0.99-1.17) and PCa death (HR 1.02, 95% CI 0.84-1.22) did not reach significance on multivariable analysis. Similar results were found when accounting for polygenic hazard score. Conclusions: Among US Vietnam War veterans, Agent Orange exposure is an independent risk factor for PCa diagnosis, though associations with PCa metastasis or death are unclear when accounting for race/ethnicity, family history, and/or polygenic risk.

ReIGNITE Radiation Therapy Boost: A Prospective, International Study of Radiation Oncologists' Accuracy in Contouring Prostate Tumors for Focal Radiation Therapy Boost on Conventional Magnetic Resonance Imaging Alone or With Assistance of Restriction Spectrum Imaging.

PURPOSE: In a phase III randomized trial, adding a radiation boost to tumor(s) visible on MRI improved prostate cancer (PCa) disease-free and metastasis-free survival without additional toxicity. Radiation oncologists' ability to identify prostate tumors is critical to widely adopting intraprostatic tumor radiotherapy boost for patients. A diffusion MRI biomarker, called the Restriction Spectrum Imaging restriction score (RSIrs), has been shown to improve radiologists' identification of clinically significant PCa. We hypothesized that (1) radiation oncologists would find accurately delineating PCa tumors on conventional MRI challenging and (2) using RSIrs maps would improve radiation oncologists' accuracy for PCa tumor delineation. METHODS AND MATERIALS: In this multi-institutional, international, prospective study, 44 radiation oncologists (participants) and 2 expert radiologists (experts) contoured prostate tumors on 39 total patient cases using conventional MRI with or without RSIrs maps. Participant volumes were compared to the consensus expert volumes. Contouring accuracy metrics included percent overlap with expert volume, Dice coefficient, conformal number, and maximum distance beyond expert volume. RESULTS: 1604 participant volumes were produced. 40 of 44 participants (91%) completely missed ≥1 expert-defined target lesion without RSIrs, compared to 13 of 44 (30%) with RSIrs maps. On conventional MRI alone, 134 of 762 contour attempts (18%) completely missed the target, compared to 18 of 842 (2%) with RSIrs maps. Use of RSIrs maps improved all contour accuracy metrics by approximately 50% or more. Mixed effects modeling confirmed that RSIrs maps were the main variable driving improvement in all metrics. System Usability Scores indicated RSIrs maps significantly improved the contouring experience (72 vs. 58, p < 0.001). CONCLUSIONS: Radiation oncologists struggle with accurately delineating visible PCa tumors on conventional MRI. RSIrs maps improve radiation oncologists' ability to target MRI-visible tumors for prostate tumor boost.

Microstructural Cerebellar Injury Independently Associated With Processing Speed in Adult Patients With Primary Brain Tumors: Implications for Cognitive Preservation.

PURPOSE: The cerebellum's role in posttreatment neurocognitive decline is unexplored. This study investigated associations between cerebellar microstructural integrity using quantitative neuroimaging biomarkers and neurocognition among patients with primary brain tumors receiving partial-brain radiation therapy (RT). METHODS AND MATERIALS: In a prospective trial, 65 patients underwent volumetric brain magnetic resonance imaging, diffusion tensor imaging, and memory, executive function, language, attention, and processing speed (PS) assessment before RT and at 3, 6, and 12 months after RT. Delis-Kaplan Executive Function System-Trail Making (D-KEFS-TM) visual scanning and number and letter sequencing and Wechsler Adult Intelligence Scale, Fourth Edition, coding were used to evaluate PS. The cerebellar cortex and white matter (WM) and supratentorial structures subserving the previously mentioned cognitive domains were autosegmented. Volume was measured within each structure at each time point along with diffusion biomarkers (fractional anisotropy and mean diffusivity) in WM structures. Linear mixed-effects models assessed cerebellar biomarkers as predictors of neurocognitive scores. If associated, cerebellar biomarkers were evaluated as independent predictors of cognitive scores controlling for domain-specific supratentorial biomarkers. RESULTS: Left (P = .04) and right (P < .001) cerebellar WM volume declined significantly over time. Cerebellar biomarkers were not associated with memory, executive function, or language. Smaller left cerebellar cortex volume was associated with worse D-KEFS-TM number (P = .01) and letter (P = .01) sequencing scores. A smaller right cerebellar cortex volume correlated with worse D-KEFS-TM visual scanning (P = .02) and number (P = .03) and letter (P = .02) sequencing scores. Greater right cerebellar WM mean diffusivity, indicating WM injury, was associated with worse D-KEFS-TM visual scanning performance (P = .03). Associations remained significant after controlling for corpus callosum and intrahemispheric WM injury biomarkers. CONCLUSIONS: Injury to the cerebellum as measured with quantitative biomarkers correlates with worse post-RT PS, independent of corpus callosum and intrahemispheric WM damage. Efforts to preserve cerebellar integrity may preserve PS.

Dose-Dependent Atrophy in Bilateral Amygdalae and Nuclei After Brain Radiation Therapy and Its Association With Mood and Memory Outcomes on a Longitudinal Clinical Trial.

PURPOSE: Amygdalae are bilateral, almond-shaped structures located anterior to the hippocampi, critical to limbic system functions of emotional processing and memory consolidation. The amygdalae are heterogeneous, composed of multiple nuclei with distinct structural and functional properties. We prospectively assessed associations between longitudinal changes in amygdala morphometry, including component nuclei, and functional outcomes in patients with primary brain tumors receiving radiation therapy (RT). METHODS AND MATERIALS: On a prospective longitudinal trial, 63 patients underwent high-resolution volumetric brain magnetic resonance imaging and testing for mood (Beck Depression Inventory and Beck Anxiety Inventory), memory (Brief Visuospatial Memory Test-Revised [BVMT] Total Recall and Delayed Recall; Hopkins Verbal Learning Test-Revised [HVLT] Total Recall and Delayed Recall), and health-related quality-of-life outcomes (Functional Assessment of Cancer Therapy-Brain Social/Family Well-Being and Emotional Well-Being) at baseline and 3, 6, and 12 months after RT. Amygdalae, including 8 nuclei, were autosegmented bilaterally using validated techniques. Linear mixed-effects models assessed longitudinal change in amygdalae and nuclei volumes and associations with dose and outcomes. Wilcoxon rank sum tests compared amygdala volume change between patient groups with worse and more stable outcomes at each time point. RESULTS: Atrophy was found in the right amygdala at 6 months (P = .001) and the left amygdala at 12 months (P = .046). A higher dose was associated with atrophy of the left amygdala (P = .013) at 12 months. The right amygdala showed dose-dependent atrophy at 6 months (P = .016) and 12 months (P = .001). Worse BVMT-Total, HVLT-Total, and HVLT-Delayed performance was associated with smaller left lateral (P = .014, P = .004, and P = .007, respectively) and left basal (P = .034, P = .016, and P = .026, respectively) nuclei volumes. Increased anxiety at 6 months was associated with greater combined (P = .031) and right (P = .007) amygdala atrophy. Greater left amygdala atrophy (P = .038) was noted in patients with decreased emotional well-being at 12 months. CONCLUSIONS: Bilateral amygdalae and nuclei undergo time- and dose-dependent atrophy after brain RT. Atrophy in amygdalae and specific nuclei was associated with poorer memory, mood, and emotional well-being. Amygdalae-sparing treatment planning may preserve neurocognitive and neuropsychiatric outcomes in this population.

Fine Motor Skill Decline After Brain Radiation Therapy-A Multivariate Normal Tissue Complication Probability Study of a Prospective Trial.

PURPOSE: Brain radiation therapy can impair fine motor skills (FMS). Fine motor skills are essential for activities of daily living, enabling hand-eye coordination for manipulative movements. We developed normal tissue complication probability (NTCP) models for the decline in FMS after fractionated brain radiation therapy (RT). METHODS AND MATERIALS: On a prospective trial, 44 patients with primary brain tumors received fractioned RT; underwent high-resolution volumetric magnetic resonance imaging, diffusion tensor imaging, and comprehensive FMS assessments (Delis-Kaplan Executive Function System Trail Making Test Motor Speed [DKEFS-MS]; and Grooved Pegboard dominant/nondominant hands) at baseline and 6 months postRT. Regions of interest subserving motor function (including cortex, superficial white matter, thalamus, basal ganglia, cerebellum, and white matter tracts) were autosegmented using validated methods and manually verified. Dosimetric and clinical variables were included in multivariate NTCP models using automated bootstrapped logistic regression, least absolute shrinkage and selection operator logistic regression, and random forests with nested cross-validation. RESULTS: Half of the patients showed a decline on grooved pegboard test of nondominant hands, 17 of 42 (40.4%) on grooved pegboard test of -dominant hands, and 11 of 44 (25%) on DKEFS-MS. Automated bootstrapped logistic regression selected a 1-term model including maximum dose to dominant postcentral white matter. The least absolute shrinkage and selection operator logistic regression selected this term and steroid use. The top 5 variables in the random forest were all dosimetric: maximum dose to dominant thalamus, mean dose to dominant caudate, mean and maximum dose to the dominant corticospinal tract, and maximum dose to dominant postcentral white matter. This technique performed best with an area under the curve of 0.69 (95% CI, 0.68-0.70) on nested cross-validation. CONCLUSIONS: We present the first NTCP models for FMS impairment after brain RT. Dose to several supratentorial motor-associated regions of interest correlated with a decline in dominant-hand fine motor dexterity in patients with primary brain tumors in multivariate models, outperforming clinical variables. These data can guide prospective fine motor-sparing strategies for brain RT.

The relationship between radiation dose and bevacizumab-related imaging abnormality in patients with brain tumors: A voxel-wise normal tissue complication probability (NTCP) analysis.

PURPOSE: Bevacizumab-related imaging abnormality (BRIA), appearing as areas of restricted diffusion on magnetic resonance imaging (MRI) and representing atypical coagulative necrosis pathologically, has been observed in patients with brain tumors receiving radiotherapy and bevacizumab. We investigated the role of cumulative radiation dose in BRIA development in a voxel-wise analysis. METHODS: Patients (n = 18) with BRIA were identified. All had high-grade gliomas or brain metastases treated with radiotherapy and bevacizumab. Areas of BRIA were segmented semi-automatically on diffusion-weighted MRI with apparent diffusion coefficient (ADC) images. To avoid confounding by possible tumor, hypoperfusion was confirmed with perfusion imaging. ADC images and radiation dose maps were co-registered to a high-resolution T1-weighted MRI and registration accuracy was verified. Voxel-wise normal tissue complication probability analyses were performed using a logistic model analyzing the relationship between cumulative voxel equivalent total dose in 2 Gy fractions (EQD2) and BRIA development at each voxel. Confidence intervals for regression model predictions were estimated with bootstrapping. RESULTS: Among 18 patients, 39 brain tumors were treated. Patients received a median of 4.5 cycles of bevacizumab and 1-4 radiation courses prior to BRIA appearance. Most (64%) treated tumors overlapped with areas of BRIA. The median proportion of each BRIA region of interest volume overlapping with tumor was 98%. We found a dose-dependent association between cumulative voxel EQD2 and the relative probability of BRIA (ß0 = -5.1, ß1 = 0.03 Gy-1, γ = 1.3). CONCLUSIONS: BRIA is likely a radiation dose-dependent phenomenon in patients with brain tumors receiving bevacizumab and radiotherapy. The combination of radiation effects and tumor microenvironmental factors in potentiating BRIA in this population should be further investigated.

Automated Patient-level Prostate Cancer Detection with Quantitative Diffusion Magnetic Resonance Imaging.

Background: Multiparametric magnetic resonance imaging (mpMRI) improves detection of clinically significant prostate cancer (csPCa), but the subjective Prostate Imaging Reporting and Data System (PI-RADS) system and quantitative apparent diffusion coefficient (ADC) are inconsistent. Restriction spectrum imaging (RSI) is an advanced diffusion-weighted MRI technique that yields a quantitative imaging biomarker for csPCa called the RSI restriction score (RSIrs). Objective: To evaluate RSIrs for automated patient-level detection of csPCa. Design setting and participants: We retrospectively studied all patients (n = 151) who underwent 3 T mpMRI and RSI (a 2-min sequence on a clinical scanner) for suspected prostate cancer at University of California San Diego during 2017-2019 and had prostate biopsy within 180 d of MRI. Intervention: We calculated the maximum RSIrs and minimum ADC within the prostate, and obtained PI-RADS v2.1 from medical records. Outcome measurements and statistical analysis: We compared the performance of RSIrs, ADC, and PI-RADS for the detection of csPCa (grade group ≥2) on the best available histopathology (biopsy or prostatectomy) using the area under the curve (AUC) with two-tailed α = 0.05. We also explored whether the combination of PI-RADS and RSIrs might be superior to PI-RADS alone and performed subset analyses within the peripheral and transition zones. Results and limitations: AUC values for ADC, RSIrs, and PI-RADS were 0.48 (95% confidence interval: 0.39, 0.58), 0.78 (0.70, 0.85), and 0.77 (0.70, 0.84), respectively. RSIrs and PI-RADS were each superior to ADC for patient-level detection of csPCa (p < 0.0001). RSIrs alone was comparable with PI-RADS (p = 0.8). The combination of PI-RADS and RSIrs had an AUC of 0.85 (0.78, 0.91) and was superior to either PI-RADS or RSIrs alone (p < 0.05). Similar patterns were seen in the peripheral and transition zones. Conclusions: RSIrs is a promising quantitative marker for patient-level csPCa detection, warranting a prospective study. Patient summary: We evaluated a rapid, advanced prostate magnetic resonance imaging technique called restriction spectrum imaging to see whether it could give an automated score that predicted the presence of clinically significant prostate cancer. The automated score worked about as well as expert radiologists' interpretation. The combination of the radiologists' scores and automated score might be better than either alone.

Neurocognitive considerations in the treatment of meningioma with radiation therapy: applications for quantitative neuroimaging and precision radiation medicine.

This article focuses on the role of radiotherapy in the management of meningioma, in the definitive and adjuvant setting and across the spectrum of meningioma grade. Treatment paradigms, informed by clinical evidence, are discussed. Notably, we focus on the impact of radiotherapy on normal brain tissues and neurocognitive function, particularly the dose-dependent changes in white matter and cerebral cortex thickness. Novel imaging techniques have allowed the identification of microstructural changes to eloquent white matter, cortex, and subcortical regions as biomarkers for understanding RT-induced changes in cognitive functioning. Deficits in multiple domains including attention, memory, language and executive function can become more pronounced following radiation. Longitudinal assessment with imaging and neurocognitive testing pre- and post-radiation have allowed correlation between dose to specific regions of the brain and decline in associated domains of neurocognitive function. These findings suggest incorporation of areas at higher risk for neurocognitive sequelae into precision radiation planning. Volumetric arc therapy, advanced planning with cortical sparing, proton therapy and stereotactic radiosurgery are reviewed as options for delivering therapeutic dose to target volumes while minimizing risk to adjacent sensitive regions. The treatment of meningioma is an evolving area, with improving outcomes for higher grade disease in modern trials, where care must be taken to maximize both disease control as well as quality of life for patients.

Polygenic risk of any, metastatic, and fatal prostate cancer in the Million Veteran Program.

BACKGROUND: Genetic scores may provide an objective measure of prostate cancer risk and thus inform screening decisions. We evaluated whether a polygenic hazard score based on 290 genetic variants (PHS290) is associated with prostate cancer risk in a diverse population, including Black men, who have higher average risk of prostate cancer death but are often treated as a homogeneously high-risk group. METHODS: This was a retrospective analysis of the Million Veteran Program, a national, population-based cohort study of US military veterans conducted 2011-2021. Cox proportional hazards analyses tested for association of genetic and other risk factors (including self-reported race and ethnicity and family history) with age at death from prostate cancer, age at diagnosis of metastatic (nodal or distant) prostate cancer, and age at diagnosis of any prostate cancer. RESULTS: A total of 590 750 male participants were included. Median age at last follow-up was 69 years. PHS290 was associated with fatal prostate cancer in the full cohort and for each racial and ethnic group (P < .001). Comparing men in the highest 20% of PHS290 with those in the lowest 20% (based on percentiles from an independent training cohort), the hazard ratio for fatal prostate cancer was 4.42 (95% confidence interval = 3.91 to 5.02). When accounting for guideline-recommended risk factors (family history, race, and ethnicity), PHS290 remained a strong independent predictor of any, metastatic, and fatal prostate cancer. CONCLUSIONS: PHS290 stratified US veterans of diverse ancestry for lifetime risk of prostate cancer, including metastatic and fatal cancer. Predicting genetic risk of lethal prostate cancer with PHS290 might inform individualized decisions about prostate cancer screening.

Prostate cancer risk stratification improvement across multiple ancestries with new polygenic hazard score.

BACKGROUND: Prostate cancer risk stratification using single-nucleotide polymorphisms (SNPs) demonstrates considerable promise in men of European, Asian, and African genetic ancestries, but there is still need for increased accuracy. We evaluated whether including additional SNPs in a prostate cancer polygenic hazard score (PHS) would improve associations with clinically significant prostate cancer in multi-ancestry datasets. METHODS: In total, 299 SNPs previously associated with prostate cancer were evaluated for inclusion in a new PHS, using a LASSO-regularized Cox proportional hazards model in a training dataset of 72,181 men from the PRACTICAL Consortium. The PHS model was evaluated in four testing datasets: African ancestry, Asian ancestry, and two of European Ancestry-the Cohort of Swedish Men (COSM) and the ProtecT study. Hazard ratios (HRs) were estimated to compare men with high versus low PHS for association with clinically significant, with any, and with fatal prostate cancer. The impact of genetic risk stratification on the positive predictive value (PPV) of PSA testing for clinically significant prostate cancer was also measured. RESULTS: The final model (PHS290) had 290 SNPs with non-zero coefficients. Comparing, for example, the highest and lowest quintiles of PHS290, the hazard ratios (HRs) for clinically significant prostate cancer were 13.73 [95% CI: 12.43-15.16] in ProtecT, 7.07 [6.58-7.60] in African ancestry, 10.31 [9.58-11.11] in Asian ancestry, and 11.18 [10.34-12.09] in COSM. Similar results were seen for association with any and fatal prostate cancer. Without PHS stratification, the PPV of PSA testing for clinically significant prostate cancer in ProtecT was 0.12 (0.11-0.14). For the top 20% and top 5% of PHS290, the PPV of PSA testing was 0.19 (0.15-0.22) and 0.26 (0.19-0.33), respectively. CONCLUSIONS: We demonstrate better genetic risk stratification for clinically significant prostate cancer than prior versions of PHS in multi-ancestry datasets. This is promising for implementing precision-medicine approaches to prostate cancer screening decisions in diverse populations.

Automated segmentation of multiparametric magnetic resonance images for cerebral AVM radiosurgery planning: a deep learning approach.

Stereotactic radiosurgery planning for cerebral arteriovenous malformations (AVM) is complicated by the variability in appearance of an AVM nidus across different imaging modalities. We developed a deep learning approach to automatically segment cerebrovascular-anatomical maps from multiple high-resolution magnetic resonance imaging/angiography (MRI/MRA) sequences in AVM patients, with the goal of facilitating target delineation. Twenty-three AVM patients who were evaluated for radiosurgery and underwent multi-parametric MRI/MRA were included. A hybrid semi-automated and manual approach was used to label MRI/MRAs with arteries, veins, brain parenchyma, cerebral spinal fluid (CSF), and embolized vessels. Next, these labels were used to train a convolutional neural network to perform this task. Imaging from 17 patients (6362 image slices) was used for training, and 6 patients (1224 slices) for validation. Performance was evaluated by Dice Similarity Coefficient (DSC). Classification performance was good for arteries, veins, brain parenchyma, and CSF, with DSCs of 0.86, 0.91, 0.98, and 0.91, respectively in the validation image set. Performance was lower for embolized vessels, with a DSC of 0.75. This demonstrates the proof of principle that accurate, high-resolution cerebrovascular-anatomical maps can be generated from multiparametric MRI/MRA. Clinical validation of their utility in radiosurgery planning is warranted.

Correcting B0 inhomogeneity-induced distortions in whole-body diffusion MRI of bone.

Diffusion-weighted magnetic resonance imaging (DWI) of the musculoskeletal system has various applications, including visualization of bone tumors. However, DWI acquired with echo-planar imaging is susceptible to distortions due to static magnetic field inhomogeneities. This study aimed to estimate spatial displacements of bone and to examine whether distortion corrected DWI images more accurately reflect underlying anatomy. Whole-body MRI data from 127 prostate cancer patients were analyzed. The reverse polarity gradient (RPG) technique was applied to DWI data to estimate voxel-level distortions and to produce a distortion corrected DWI dataset. First, an anatomic landmark analysis was conducted, in which corresponding vertebral landmarks on DWI and anatomic T2-weighted images were annotated. Changes in distance between DWI- and T2-defined landmarks (i.e., changes in error) after distortion correction were calculated. In secondary analyses, distortion estimates from RPG were used to assess spatial displacements of bone metastases. Lastly, changes in mutual information between DWI and T2-weighted images of bone metastases after distortion correction were calculated. Distortion correction reduced anatomic error of vertebral DWI up to 29 mm. Error reductions were consistent across subjects (Wilcoxon signed-rank p < 10-20). On average (± SD), participants' largest error reduction was 11.8 mm (± 3.6). Mean (95% CI) displacement of bone lesions was 6.0 mm (95% CI 5.0-7.2); maximum displacement was 17.1 mm. Corrected diffusion images were more similar to structural MRI, as evidenced by consistent increases in mutual information (Wilcoxon signed-rank p < 10-12). These findings support the use of distortion correction techniques to improve localization of bone on DWI.

Genetic Stratification of Age-Dependent Parkinson's Disease Risk by Polygenic Hazard Score.

BACKGROUND: Parkinson's disease (PD) is a highly age-related disorder, where common genetic risk variants affect both disease risk and age at onset. A statistical approach that integrates these effects across all common variants may be clinically useful for individual risk stratification. A polygenic hazard score methodology, leveraging a time-to-event framework, has recently been successfully applied in other age-related disorders. OBJECTIVES: We aimed to develop and validate a polygenic hazard score model in sporadic PD. METHODS: Using a Cox regression framework, we modeled the polygenic hazard score in a training data set of 11,693 PD patients and 9841 controls. The score was then validated in an independent test data set of 5112 PD patients and 5372 controls and a small single-study sample of 360 patients and 160 controls. RESULTS: A polygenic hazard score predicts the onset of PD with a hazard ratio of 3.78 (95% confidence interval 3.49-4.10) when comparing the highest to the lowest risk decile. Combined with epidemiological data on incidence rate, we apply the score to estimate genetically stratified instantaneous PD risk across age groups. CONCLUSIONS: We demonstrate the feasibility of a polygenic hazard approach in PD, integrating the genetic effects on disease risk and age at onset in a single model. In combination with other predictive biomarkers, the approach may hold promise for risk stratification in future clinical trials of disease-modifying therapies, which aim at postponing the onset of PD. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Performance of African-ancestry-specific polygenic hazard score varies according to local ancestry in 8q24.

BACKGROUND: We previously developed an African-ancestry-specific polygenic hazard score (PHS46+African) that substantially improved prostate cancer risk stratification in men with African ancestry. The model consists of 46 SNPs identified in Europeans and 3 SNPs from 8q24 shown to improve model performance in Africans. Herein, we used principal component (PC) analysis to uncover subpopulations of men with African ancestry for whom the utility of PHS46+African may differ. MATERIALS AND METHODS: Genotypic data were obtained from the PRACTICAL consortium for 6253 men with African genetic ancestry. Genetic variation in a window spanning 3 African-specific 8q24 SNPs was estimated using 93 PCs. A Cox proportional hazards framework was used to identify the pair of PCs most strongly associated with the performance of PHS46+African. A calibration factor (CF) was formulated using Cox coefficients to quantify the extent to which the performance of PHS46+African varies with PC. RESULTS: CF of PHS46+African was strongly associated with the first and twentieth PCs. Predicted CF ranged from 0.41 to 2.94, suggesting that PHS46+African may be up to 7 times more beneficial to some African men than others. The explained relative risk for PHS46+African varied from 3.6% to 9.9% for individuals with low and high CF values, respectively. By cross-referencing our data set with 1000 Genomes, we identified significant associations between continental and calibration groupings. CONCLUSION: We identified PCs within 8q24 that were strongly associated with the performance of PHS46+African. Further research to improve the clinical utility of polygenic risk scores (or models) is needed to improve health outcomes for men of African ancestry.

Quality of Life Is Independently Associated With Neurocognitive Function in Patients With Brain Tumors: Analysis of a Prospective Clinical Trial.

PURPOSE: We conducted the first prospective longitudinal study examining the independent association between patient-reported health-related quality of life (hrQoL) (physical, social/family, emotional, functional, and brain cancer-specific) and neurocognitive function (NCF), while controlling for mood symptoms in patients with primary brain tumors. METHODS AND MATERIALS: Patients with primary brain tumors (n = 59) receiving brain radiation therapy underwent hrQOL (Functional Assessment of Cancer Therapy-Brain), mood (Beck Depression and Anxiety Inventories), and neurocognitive evaluation at baseline and 3, 6, and 12 months postradiation therapy in a prospective clinical trial. Neurocognitive assessments measured attention/processing speed, memory, and executive function, including the Delis-Kaplan Executive Function System Verbal Fluency, Hopkins Verbal Learning Test Revised (HVLT-R), and Brief Visuospatial Memory Test. Subjects underwent neurocognitive, mood, and hrQoL assessments in the same testing session. Multivariable linear mixed-effects models assessed associations between hrQOL and NCF over time, controlling for patient, tumor, and treatment characteristics as well as timepoint-specific patient-reported mood (ie, anxiety and depression symptoms). P values were adjusted for multiple comparisons. RESULTS: Higher physical hrQoL was associated with better verbal memory (HVLT-R Total Recall, P = .047), and higher functional hrQoL was associated with better executive function (Delis-Kaplan Executive Function System Verbal Fluency Switching Total, P = .009) and verbal memory (HVLT-R Delayed Recall, P = .006). Higher brain tumor-specific hrQoL was associated with better verbal and nonverbal memory (HVLT-R Total, P = .004 and Delayed Recall, P = .030; Brief Visuospatial Memory Test Total, P = .049 and Delayed Recall, P = .049). There was no association between social/family or emotional hrQoL and NCF after controlling for mood. CONCLUSIONS: Higher physical, functional, and brain tumor-specific hrQoL were associated with better executive function and memory among patients with primary brain tumors. Physical and functional impairments are correlated with cognitive performance. Interventions to maximize quality of life after treatment may influence neurocognition and vice versa.

Voxel-level Classification of Prostate Cancer on Magnetic Resonance Imaging: Improving Accuracy Using Four-Compartment Restriction Spectrum Imaging.

BACKGROUND: Diffusion magnetic resonance imaging (MRI) is integral to detection of prostate cancer (PCa), but conventional apparent diffusion coefficient (ADC) cannot capture the complexity of prostate tissues and tends to yield noisy images that do not distinctly highlight cancer. A four-compartment restriction spectrum imaging (RSI4 ) model was recently found to optimally characterize pelvic diffusion signals, and the model coefficient for the slowest diffusion compartment, RSI4 -C1 , yielded greatest tumor conspicuity. PURPOSE: To evaluate the slowest diffusion compartment of a four-compartment spectrum imaging model (RSI4 -C1 ) as a quantitative voxel-level classifier of PCa. STUDY TYPE: Retrospective. SUBJECTS: Forty-six men who underwent an extended MRI acquisition protocol for suspected PCa. Twenty-three men had benign prostates, and the other 23 men had PCa. FIELD STRENGTH/SEQUENCE: A 3 T, multishell diffusion-weighted and axial T2-weighted sequences. ASSESSMENT: High-confidence cancer voxels were delineated by expert consensus, using imaging data and biopsy results. The entire prostate was considered benign in patients with no detectable cancer. Diffusion images were used to calculate RSI4 -C1 and conventional ADC. Classifier images were also generated. STATISTICAL TESTS: Voxel-level discrimination of PCa from benign prostate tissue was assessed via receiver operating characteristic (ROC) curves generated by bootstrapping with patient-level case resampling. RSI4 -C1 was compared to conventional ADC for two metrics: area under the ROC curve (AUC) and false-positive rate for a sensitivity of 90% (FPR90 ). Statistical significance was assessed using bootstrap difference with two-sided α = 0.05. RESULTS: RSI4 -C1 outperformed conventional ADC, with greater AUC (mean 0.977 [95% CI: 0.951-0.991] vs. 0.922 [0.878-0.948]) and lower FPR90 (0.032 [0.009-0.082] vs. 0.201 [0.132-0.290]). These improvements were statistically significant (P < 0.05). DATA CONCLUSION: RSI4 -C1 yielded a quantitative, voxel-level classifier of PCa that was superior to conventional ADC. RSI classifier images with a low false-positive rate might improve PCa detection and facilitate clinical applications like targeted biopsy and treatment planning. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 2.