Publications by authors named "Roshan Karunamuni"

44 Publications

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

Mov Disord 2021 Oct 6. Epub 2021 Oct 6.

NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway.

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.
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http://dx.doi.org/10.1002/mds.28808DOI Listing
October 2021

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

Prostate Cancer Prostatic Dis 2021 Jun 14. Epub 2021 Jun 14.

School of Public Health, Louisiana State University Health Sciences Center, New Orleans, LA, USA.

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.
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http://dx.doi.org/10.1038/s41391-021-00403-7DOI Listing
June 2021

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

Int J Radiat Oncol Biol Phys 2021 11 6;111(3):754-763. Epub 2021 Jun 6.

Department of Radiation Medicine and Applied Sciences, University of California San Diego, San Diego, California. Electronic address:

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.
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http://dx.doi.org/10.1016/j.ijrobp.2021.05.134DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8463493PMC
November 2021

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

J Magn Reson Imaging 2021 09 31;54(3):975-984. Epub 2021 Mar 31.

Department of Radiation Medicine and Applied Sciences, UC San Diego School of Medicine, La Jolla, California, USA.

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 (RSI ) model was recently found to optimally characterize pelvic diffusion signals, and the model coefficient for the slowest diffusion compartment, RSI -C , yielded greatest tumor conspicuity.

Purpose: To evaluate the slowest diffusion compartment of a four-compartment spectrum imaging model (RSI -C ) 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 RSI -C 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. RSI -C was compared to conventional ADC for two metrics: area under the ROC curve (AUC) and false-positive rate for a sensitivity of 90% (FPR ). Statistical significance was assessed using bootstrap difference with two-sided α = 0.05.

Results: RSI -C outperformed conventional ADC, with greater AUC (mean 0.977 [95% CI: 0.951-0.991] vs. 0.922 [0.878-0.948]) and lower FPR (0.032 [0.009-0.082] vs. 0.201 [0.132-0.290]). These improvements were statistically significant (P < 0.05).

Data Conclusion: RSI -C 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.
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http://dx.doi.org/10.1002/jmri.27623DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8363567PMC
September 2021

Common genetic and clinical risk factors: association with fatal prostate cancer in the Cohort of Swedish Men.

Prostate Cancer Prostatic Dis 2021 09 15;24(3):845-851. Epub 2021 Mar 15.

Department of Radiation Medicine and Applied Sciences, University of California San Diego, La Jolla, CA, USA.

Background: Clinical variables-age, family history, genetics-are used for prostate cancer risk stratification. Recently, polygenic hazard scores (PHS46, PHS166) were validated as associated with age at prostate cancer diagnosis. While polygenic scores are associated with all prostate cancer (not specific for fatal cancers), PHS46 was also associated with age at prostate cancer death. We evaluated if adding PHS to clinical variables improves associations with prostate cancer death.

Methods: Genotype/phenotype data were obtained from a nested case-control Cohort of Swedish Men (n = 3279; 2163 with prostate cancer, 278 prostate cancer deaths). PHS and clinical variables (family history, alcohol intake, smoking, heart disease, hypertension, diabetes, body mass index) were tested via univariable Cox proportional hazards models for association with age at prostate cancer death. Multivariable Cox models with/without PHS were compared with log-likelihood tests.

Results: Median age at last follow-up/prostate cancer death was 78.0 (IQR: 72.3-84.1) and 81.4 (75.4-86.3) years, respectively. On univariable analysis, PHS46 (HR 3.41 [95% CI 2.78-4.17]), family history (HR 1.72 [1.46-2.03]), alcohol (HR 1.74 [1.40-2.15]), diabetes (HR 0.53 [0.37-0.75]) were each associated with prostate cancer death. On multivariable analysis, PHS46 (HR 2.45 [1.99-2.97]), family history (HR 1.73 [1.48-2.03]), alcohol (HR 1.45 [1.19-1.76]), diabetes (HR 0.62 [0.42-0.90]) all remained associated with fatal disease. Including PHS46 or PHS166 improved multivariable models for fatal prostate cancer (p < 10).

Conclusions: PHS had the most robust association with fatal prostate cancer in a multivariable model with common risk factors, including family history. Adding PHS to clinical variables may improve prostate cancer risk stratification strategies.
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http://dx.doi.org/10.1038/s41391-021-00341-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8387332PMC
September 2021

Polygenic hazard score is associated with prostate cancer in multi-ethnic populations.

Nat Commun 2021 02 23;12(1):1236. Epub 2021 Feb 23.

Division of Cancer Sciences, University of Manchester, Manchester Academic Health Science Centre, Radiotherapy Related Research, The Christie Hospital NHS Foundation Trust, Manchester, UK.

Genetic models for cancer have been evaluated using almost exclusively European data, which could exacerbate health disparities. A polygenic hazard score (PHS) is associated with age at prostate cancer diagnosis and improves screening accuracy in Europeans. Here, we evaluate performance of PHS (PHS, adapted for OncoArray) in a multi-ethnic dataset of 80,491 men (49,916 cases, 30,575 controls). PHS is associated with age at diagnosis of any and aggressive (Gleason score ≥ 7, stage T3-T4, PSA ≥ 10 ng/mL, or nodal/distant metastasis) cancer and prostate-cancer-specific death. Associations with cancer are significant within European (n = 71,856), Asian (n = 2,382), and African (n = 6,253) genetic ancestries (p < 10). Comparing the 80/20 PHS percentiles, hazard ratios for prostate cancer, aggressive cancer, and prostate-cancer-specific death are 5.32, 5.88, and 5.68, respectively. Within European, Asian, and African ancestries, hazard ratios for prostate cancer are: 5.54, 4.49, and 2.54, respectively. PHS risk-stratifies men for any, aggressive, and fatal prostate cancer in a multi-ethnic dataset.
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http://dx.doi.org/10.1038/s41467-021-21287-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7902617PMC
February 2021

Longitudinal change in fine motor skills after brain radiotherapy and in vivo imaging biomarkers associated with decline.

Neuro Oncol 2021 08;23(8):1393-1403

Department of Radiation Medicine and Applied Sciences, University of California San Diego, La Jolla, California, USA.

Background: We explored fine motor skills (FMS) before and after brain radiotherapy (RT), analyzing associations between longitudinal FMS and imaging biomarkers of cortical and white matter (WM) integrity in motor regions of interest (ROIs).

Methods: On a prospective trial, 52 primary brain tumor patients receiving fractionated brain RT underwent volumetric brain MRI, diffusion tensor imaging, and FMS assessments (Delis-Kaplan Executive Function System Trail Making Test Motor Speed [DKEFS-MS], Grooved Pegboard Dominant Hands [PDH], and Grooved Pegboard Nondominant Hands [PNDH]) at baseline and 3-, 6-, and 12-month post-RT. Motor ROIs autosegmented included: sensorimotor cortices and superficial WM, corticospinal tracts, cerebellar cortices and WM, and basal ganglia. Volume (cc) was measured in all ROIs at each timepoint. Diffusion biomarkers (FA [fractional anisotropy] and MD [mean diffusivity]) were additionally measured in WM ROIs. Linear mixed-effects models assessed biomarkers as predictors of FMS scores. P values were corrected for multiple comparisons.

Results: Higher RT dose was associated with right paracentral cortical thinning (β = -2.42 Gy/(month × mm), P = .03) and higher right precentral WM MD (β = 0.69 Gy/(month × µm2/ms), P = .04). Higher left (β = 38.7 points/(month × µm2/ms), P = .004) and right (β = 42.4 points/(month × µm2/ms), P = .01) cerebellar WM MD, left precentral cortical atrophy (β = -8.67 points/(month × mm), P = .02), and reduced right cerebral peduncle FA (β = -0.50 points/month, P = .01) were associated with worse DKEFS-MS performance. Left precentral cortex thinning was associated with worse PDH scores (β = -17.3 points/(month × mm), P = .02). Left (β = -0.87 points/(month × cm3), P = .001) and right (β = -0.64 points/(month × cm3), P = .02) cerebellar cortex, left pons (β = -19.8 points/(month × cm3), P = .02), and right pallidum (β = -10.8 points/(month × cm3), P = .02) atrophy and reduced right internal capsule FA (β = -1.02 points/month, P = .03) were associated with worse PNDH performance.

Conclusions: Biomarkers of microstructural injury in motor-associated brain regions were associated with worse FMS. Dose avoidance in these areas may preserve FMS.
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http://dx.doi.org/10.1093/neuonc/noab017DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8328007PMC
August 2021

Additional SNPs improve risk stratification of a polygenic hazard score for prostate cancer.

Prostate Cancer Prostatic Dis 2021 06 8;24(2):532-541. Epub 2021 Jan 8.

Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, 02115, USA.

Background: Polygenic hazard scores (PHS) can identify individuals with increased risk of prostate cancer. We estimated the benefit of additional SNPs on performance of a previously validated PHS (PHS46).

Materials And Method: 180 SNPs, shown to be previously associated with prostate cancer, were used to develop a PHS model in men with European ancestry. A machine-learning approach, LASSO-regularized Cox regression, was used to select SNPs and to estimate their coefficients in the training set (75,596 men). Performance of the resulting model was evaluated in the testing/validation set (6,411 men) with two metrics: (1) hazard ratios (HRs) and (2) positive predictive value (PPV) of prostate-specific antigen (PSA) testing. HRs were estimated between individuals with PHS in the top 5% to those in the middle 40% (HR95/50), top 20% to bottom 20% (HR80/20), and bottom 20% to middle 40% (HR20/50). PPV was calculated for the top 20% (PPV80) and top 5% (PPV95) of PHS as the fraction of individuals with elevated PSA that were diagnosed with clinically significant prostate cancer on biopsy.

Results: 166 SNPs had non-zero coefficients in the Cox model (PHS166). All HR metrics showed significant improvements for PHS166 compared to PHS46: HR95/50 increased from 3.72 to 5.09, HR80/20 increased from 6.12 to 9.45, and HR20/50 decreased from 0.41 to 0.34. By contrast, no significant differences were observed in PPV of PSA testing for clinically significant prostate cancer.

Conclusions: Incorporating 120 additional SNPs (PHS166 vs PHS46) significantly improved HRs for prostate cancer, while PPV of PSA testing remained the same.
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http://dx.doi.org/10.1038/s41391-020-00311-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8157993PMC
June 2021

Microstructural Injury to Corpus Callosum and Intrahemispheric White Matter Tracts Correlate With Attention and Processing Speed Decline After Brain Radiation.

Int J Radiat Oncol Biol Phys 2021 06 4;110(2):337-347. Epub 2021 Jan 4.

Department of Radiation Medicine and Applied Sciences, University of California San Diego, La Jolla, California; Center for Multimodal Imaging and Genetics, University of California San Diego, La Jolla, California. Electronic address:

Purpose: The corpus callosum (CC) and intrahemispheric white matter tracts (IHWM) subserve critical aspects of attention and processing speed. We analyzed imaging biomarkers of microstructural injury within these regions and association with attention and processing speed performance before and after radiation therapy in primary brain tumor patients.

Methods And Materials: In a prospective clinical trial, 44 primary brain tumor patients underwent cognitive testing and magnetic resonance imaging/diffusion-weighted imaging at baseline (pre-radiation therapy) and 3-, 6-, and 12-months post-radiation therapy. CC (subregions, total) and IHWM tracts (left/right without CC, total) were autosegmented; tumor, tumor bed, and edema were censored. Biomarkers included volume changes (cm), mean diffusivity ([MD]; higher values indicate white matter injury), fractional anisotropy ([FA]; lower values indicate white matter injury). Reliable-change indices measured changes in attention (Weschler Adult Intelligence Scale [WAIS-IV] digits-forward; Delis-Kaplan Executive Function System Trail Making [D-KEFS-TM] visual-scanning), and processing speed (WAIS-IV coding; D-KEFS-TM number-sequencing, letter-sequencing), accounting for practice effects. Linear mixed-effects models evaluated associations between mean radiation dose and biomarkers (volume, MD, FA) and imaging biomarkers and neurocognitive performance. Statistics were corrected for multiple comparisons.

Results: Processing speed declined at 6 months following radiation therapy (number sequencing, letter sequencing; P < .04). Seizures and antiepileptic drug therapy were associated with lower visual-scanning attention reliable-change indices at 6 months (P = .039). Higher radiation dose correlated with smaller midanterior CC volume (P = .023); lower FA in posterior CC, anterior CC, and total CC (all P < .03); and higher MD in anterior CC (P = .012). Smaller midanterior CC and left IHWM volume correlated with worse processing speed (coding, letter-sequencing, number-sequencing; all P < .03). Higher FA in right, left, and total IHWM correlated with better coding scores (all P < .01). Lower FA in total IHWM (P = .009) was associated with worse visual-scanning attention scores. Higher FA in midposterior CC (P = .029) correlated with better digits-forward attention scores.

Conclusions: The CC demonstrated radiation dose-dependent atrophy and WM injury. Microstructural injury within the CC and IHWM was associated with attention and processing speed decline after radiation therapy. These areas represent possible avoidance regions for preservation of attention and processing speed.
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http://dx.doi.org/10.1016/j.ijrobp.2020.12.046DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8162991PMC
June 2021

Improved Characterization of Diffusion in Normal and Cancerous Prostate Tissue Through Optimization of Multicompartmental Signal Models.

J Magn Reson Imaging 2021 02 31;53(2):628-639. Epub 2020 Oct 31.

Department of Radiology, UC San Diego School of Medicine, La Jolla, California, USA.

Background: Multicompartmental modeling outperforms conventional diffusion-weighted imaging (DWI) in the assessment of prostate cancer. Optimized multicompartmental models could further improve the detection and characterization of prostate cancer.

Purpose: To optimize multicompartmental signal models and apply them to study diffusion in normal and cancerous prostate tissue in vivo.

Study Type: Retrospective.

Subjects: Forty-six patients who underwent MRI examination for suspected prostate cancer; 23 had prostate cancer and 23 had no detectable cancer.

Field Strength/sequence: 3T multishell diffusion-weighted sequence.

Assessment: Multicompartmental models with 2-5 tissue compartments were fit to DWI data from the prostate to determine optimal compartmental apparent diffusion coefficients (ADCs). These ADCs were used to compute signal contributions from the different compartments. The Bayesian Information Criterion (BIC) and model-fitting residuals were calculated to quantify model complexity and goodness-of-fit. Tumor contrast-to-noise ratio (CNR) and tumor-to-background signal intensity ratio (SIR) were computed for conventional DWI and multicompartmental signal-contribution maps.

Statistical Tests: Analysis of variance (ANOVA) and two-sample t-tests (α = 0.05) were used to compare fitting residuals between prostate regions and between multicompartmental models. T-tests (α = 0.05) were also used to assess differences in compartmental signal-fraction between tissue types and CNR/SIR between conventional DWI and multicompartmental models.

Results: The lowest BIC was observed from the 4-compartment model, with optimal ADCs of 5.2e-4, 1.9e-3, 3.0e-3, and >3.0e-2 mm /sec. Fitting residuals from multicompartmental models were significantly lower than from conventional ADC mapping (P < 0.05). Residuals were lowest in the peripheral zone and highest in tumors. Tumor tissue showed the largest reduction in fitting residual by increasing model order. Tumors had a greater proportion of signal from compartment 1 than normal tissue (P < 0.05). Tumor CNR and SIR were greater on compartment-1 signal maps than conventional DWI (P < 0.05) and increased with model order.

Data Conclusion: The 4-compartment signal model best described diffusion in the prostate. Compartmental signal contributions revealed by this model may improve assessment of prostate cancer. Level of Evidence 3 Technical Efficacy Stage 3 J. MAGN. RESON. IMAGING 2021;53:628-639.
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http://dx.doi.org/10.1002/jmri.27393DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8178435PMC
February 2021

Automated contouring and planning pipeline for hippocampal-avoidant whole-brain radiotherapy.

Radiat Oncol 2020 Oct 30;15(1):251. Epub 2020 Oct 30.

UC San Diego Department of Radiation Medicine and Applied Sciences, Altman Clinical and Translational Research Institute, 9500 Gilman Dr. #0861, La Jolla, CA, USA.

Background: Whole-brain radiotherapy (WBRT) remains an important treatment for over 200,000 cancer patients in the United States annually. Hippocampal-avoidant WBRT (HA-WBRT) reduces neurocognitive toxicity compared to standard WBRT, but HA-WBRT contouring and planning are more complex and time-consuming than standard WBRT. We designed and evaluated a workflow using commercially available artificial intelligence tools for automated hippocampal segmentation and treatment planning to efficiently generate clinically acceptable HA-WBRT radiotherapy plans.

Methods: We retrospectively identified 100 consecutive adult patients treated for brain metastases outside the hippocampal region. Each patient's T1 post-contrast brain MRI was processed using NeuroQuant, an FDA-approved software that provides segmentations of brain structures in less than 8 min. Automated hippocampal segmentations were reviewed for accuracy, then converted to files compatible with a commercial treatment planning system, where hippocampal avoidance regions and planning target volumes (PTV) were generated. Other organs-at-risk (OARs) were previously contoured per clinical routine. A RapidPlan knowledge-based planning routine was applied for a prescription of 30 Gy in 10 fractions using volumetric modulated arc therapy (VMAT) delivery. Plans were evaluated based on NRG CC001 dose-volume objectives (Brown et al. in J Clin Oncol, 2020).

Results: Of the 100 cases, 99 (99%) had acceptable automated hippocampi segmentations without manual intervention. Knowledge-based planning was applied to all cases; the median processing time was 9 min 59 s (range 6:53-13:31). All plans met per-protocol dose-volume objectives for PTV per the NRG CC001 protocol. For comparison, only 65.5% of plans on NRG CC001 met PTV goals per protocol, with 26.1% within acceptable variation. In this study, 43 plans (43%) met OAR constraints, and the remaining 57 (57%) were within acceptable variation, compared to 42.5% and 48.3% on NRG CC001, respectively. No plans in this study had unacceptable dose to OARs, compared to 0.8% of manually generated plans from NRG CC001. 8.4% of plans from NRG CC001 were not scored or unable to be evaluated.

Conclusions: An automated pipeline harnessing the efficiency of commercially available artificial intelligence tools can generate clinically acceptable VMAT HA-WBRT plans with minimal manual intervention. This process could improve clinical efficiency for a treatment established to improve patient outcomes over standard WBRT.
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http://dx.doi.org/10.1186/s13014-020-01689-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7602303PMC
October 2020

African-specific improvement of a polygenic hazard score for age at diagnosis of prostate cancer.

Int J Cancer 2021 01 24;148(1):99-105. Epub 2020 Sep 24.

UMR Inserm 1134 Biologie Intégrée du Globule Rouge, INSERM/Université Paris Diderot-Université Sorbonne Paris Cité/INTS/Université des Antilles, Paris, France.

Polygenic hazard score (PHS) models are associated with age at diagnosis of prostate cancer. Our model developed in Europeans (PHS46) showed reduced performance in men with African genetic ancestry. We used a cross-validated search to identify single nucleotide polymorphisms (SNPs) that might improve performance in this population. Anonymized genotypic data were obtained from the PRACTICAL consortium for 6253 men with African genetic ancestry. Ten iterations of a 10-fold cross-validation search were conducted to select SNPs that would be included in the final PHS46+African model. The coefficients of PHS46+African were estimated in a Cox proportional hazards framework using age at diagnosis as the dependent variable and PHS46, and selected SNPs as predictors. The performance of PHS46 and PHS46+African was compared using the same cross-validated approach. Three SNPs (rs76229939, rs74421890 and rs5013678) were selected for inclusion in PHS46+African. All three SNPs are located on chromosome 8q24. PHS46+African showed substantial improvements in all performance metrics measured, including a 75% increase in the relative hazard of those in the upper 20% compared to the bottom 20% (2.47-4.34) and a 20% reduction in the relative hazard of those in the bottom 20% compared to the middle 40% (0.65-0.53). In conclusion, we identified three SNPs that substantially improved the association of PHS46 with age at diagnosis of prostate cancer in men with African genetic ancestry to levels comparable to Europeans.
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http://dx.doi.org/10.1002/ijc.33282DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8135907PMC
January 2021

Microstructural Injury to Left-Sided Perisylvian White Matter Predicts Language Decline After Brain Radiation Therapy.

Int J Radiat Oncol Biol Phys 2020 12 23;108(5):1218-1228. Epub 2020 Jul 23.

Department of Radiation Medicine and Applied Sciences, University of California San Diego, La Jolla, California; Center for Multimodal Imaging and Genetics, University of California San Diego, La Jolla, California. Electronic address:

Purpose: Our purpose was to investigate the association between imaging biomarkers of radiation-induced white matter (WM) injury within perisylvian regions and longitudinal language decline in patients with brain tumors.

Methods And Materials: Patients with primary brain tumors (n = 44) on a prospective trial underwent brain magnetic resonance imaging, diffusion-weighted imaging, and language assessments of naming (Boston Naming Test [BNT]) and fluency (Delis-Kaplan Executive Function System Category Fluency [DKEFS-CF]) at baseline and 3, 6, and 12 months after fractionated radiation therapy (RT). Reliable change indices of language function (0-6 months), accounting for practice effects (RCI-PE), evaluated decline. Bilateral perisylvian WM regions (superficial WM subadjacent to Broca's area and the superior temporal gyrus [STG], inferior longitudinal fasciculus [ILF], inferior fronto-occipital fasciculus [IFOF], and arcuate fasciculus) were autosegmented. We quantified volume and diffusion measures of WM microstructure: fractional anisotropy (FA; lower values indicate disruption) and mean diffusivity (MD; higher values indicate injury). Linear mixed-effects models assessed mean dose as predictor of imaging biomarker change and imaging biomarkers as longitudinal predictors of language scores.

Results: DKEFS-CF scores declined at 6 months post-RT (RCI-PE, -0.483; P = .01), whereas BNT scores improved (RCI-PE, 0.262; P = .04). Higher mean dose to left and right regions was predictive of decreased volume (left-STG, P = .02; right-ILF and IFOF, P = .03), decreased FA (left-WM tracts, all P < .01; right-STG and IFOF, P < .02), and increased MD of left-WM tracts (all P < .03). Volume loss within left-Broca's area (P = .01), left-ILF (P = .01), left-IFOF (P = .01), and left-arcuate fasciculus (P = .04) was associated with lower BNT scores. Lower FA correlated with poorer DKEFS-CF and BNT scores within left-ILF (P = .02, not significant), left-IFOF (P = .02, .04), and left-arcuate fasciculus (P = .01, .01), respectively. Poorer DKEFS-CF scores correlated with increased MD values within the left-arcuate fasciculus (P = .03). Right-sided biomarkers did not correlate with language scores.

Conclusions: Patients with primary brain tumors experience language fluency decline post-RT. Poorer fluency and naming function may be explained by microstructural injury to left-sided perisylvian WM, representing potential dose-avoidance targets for language preservation.
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http://dx.doi.org/10.1016/j.ijrobp.2020.07.032DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7680351PMC
December 2020

Longitudinal Analysis of Depression and Anxiety Symptoms as Independent Predictors of Neurocognitive Function in Primary Brain Tumor Patients.

Int J Radiat Oncol Biol Phys 2020 12 4;108(5):1229-1239. Epub 2020 Jul 4.

Department of Radiation Medicine and Applied Sciences, University of California San Diego, La Jolla, California. Electronic address:

Purpose: Primary brain tumor patients are vulnerable to depression and anxiety symptoms, which may affect their neurocognitive functioning. We performed a prospective longitudinal analysis to examine the association between depression and anxiety symptoms and domain-specific neurocognitive functioning in primary brain tumor patients receiving radiation therapy (RT).

Methods And Materials: On a prospective trial, 54 primary brain tumor patients receiving RT underwent comprehensive neurocognitive evaluation at baseline (pre-RT), and 3, 6, and 12 months post-RT. Neurocognitive assessments measured attention/processing speed, verbal and visuospatial memory, and executive functioning, including Delis-Kaplan Executive Function System Trail-Making Test (DKEFS-TMT), DKEFS Verbal Fluency, and Brief Visuospatial Memory Test-Revised. Depression and anxiety symptoms were also assessed at each time point with Beck Depression and Anxiety Inventories (BDI-II and BAI), respectively. Higher scores reflect more numerous or severe depression or anxiety symptoms. Univariable and multivariable linear mixed-effects models assessed associations between BDI-II and BAI scores and domain-specific neurocognitive scores over time, controlling for pre-existing depression or anxiety disorders and other patient, tumor, and treatment characteristics.

Results: Higher BAI scores were associated with worse attention and processing speed in univariable analyses: DKEFS-TMT visual scanning (P = .003), number sequencing (P = .011), and letter sequencing (P <.001). On multivariable analyses, these associations remained significant (all P ≤ .01). Higher BDI-II scores were also associated with poorer attention/processing speed (DKEFS-TMT Letter Sequencing) in univariable (P = .002) and multivariable (P = .013) models. Higher BAI scores were associated with worse visuospatial memory (Brief Visuospatial Memory Test-Revised Delayed Recall) on univariable (P = .012) but not multivariable analyses (P = .383). Similarly, higher BDI-II scores were associated with poorer executive functioning (DKEFS Verbal Fluency Category Switching) on univariable (P = .031) but not multivariable analyses (P = .198).

Conclusions: Among primary brain tumor patients receiving RT, increased depression and anxiety were independently associated with worsened neurocognition, particularly in attention/processing speed. Depression and anxiety symptoms should be controlled for in prospective clinical trials and managed in the clinical setting to optimize neurocognitive functioning.
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http://dx.doi.org/10.1016/j.ijrobp.2020.07.002DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7680441PMC
December 2020

A Genetic Risk Score to Personalize Prostate Cancer Screening, Applied to Population Data.

Cancer Epidemiol Biomarkers Prev 2020 09 24;29(9):1731-1738. Epub 2020 Jun 24.

Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota.

Background: A polygenic hazard score (PHS), the weighted sum of 54 SNP genotypes, was previously validated for association with clinically significant prostate cancer and for improved prostate cancer screening accuracy. Here, we assess the potential impact of PHS-informed screening.

Methods: United Kingdom population incidence data (Cancer Research United Kingdom) and data from the Cluster Randomized Trial of PSA Testing for Prostate Cancer were combined to estimate age-specific clinically significant prostate cancer incidence (Gleason score ≥7, stage T3-T4, PSA ≥10, or nodal/distant metastases). Using HRs estimated from the ProtecT prostate cancer trial, age-specific incidence rates were calculated for various PHS risk percentiles. Risk-equivalent age, when someone with a given PHS percentile has prostate cancer risk equivalent to an average 50-year-old man (50-year-standard risk), was derived from PHS and incidence data. Positive predictive value (PPV) of PSA testing for clinically significant prostate cancer was calculated using PHS-adjusted age groups.

Results: The expected age at diagnosis of clinically significant prostate cancer differs by 19 years between the 1st and 99th PHS percentiles: men with PHS in the 1st and 99th percentiles reach the 50-year-standard risk level at ages 60 and 41, respectively. PPV of PSA was higher for men with higher PHS-adjusted age.

Conclusions: PHS provides individualized estimates of risk-equivalent age for clinically significant prostate cancer. Screening initiation could be adjusted by a man's PHS.

Impact: Personalized genetic risk assessments could inform prostate cancer screening decisions.
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http://dx.doi.org/10.1158/1055-9965.EPI-19-1527DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7483627PMC
September 2020

The effect of sample size on polygenic hazard models for prostate cancer.

Eur J Hum Genet 2020 10 8;28(10):1467-1475. Epub 2020 Jun 8.

Humangenetik Tuebingen, Paul-Ehrlich-Str 23, D-72076, Tuebingen, Germany.

We determined the effect of sample size on performance of polygenic hazard score (PHS) models in prostate cancer. Age and genotypes were obtained for 40,861 men from the PRACTICAL consortium. The dataset included 201,590 SNPs per subject, and was split into training and testing sets. Established-SNP models considered 65 SNPs that had been previously associated with prostate cancer. Discovery-SNP models used stepwise selection to identify new SNPs. The performance of each PHS model was calculated for random sizes of the training set. The performance of a representative Established-SNP model was estimated for random sizes of the testing set. Mean HR (hazard ratio of top 2% to average in test set) of the Established-SNP model increased from 1.73 [95% CI: 1.69-1.77] to 2.41 [2.40-2.43] when the number of training samples was increased from 1 thousand to 30 thousand. Corresponding HR of the Discovery-SNP model increased from 1.05 [0.93-1.18] to 2.19 [2.16-2.23]. HR of a representative Established-SNP model using testing set sample sizes of 0.6 thousand and 6 thousand observations were 1.78 [1.70-1.85] and 1.73 [1.71-1.76], respectively. We estimate that a study population of 20 thousand men is required to develop Discovery-SNP PHS models while 10 thousand men should be sufficient for Established-SNP models.
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http://dx.doi.org/10.1038/s41431-020-0664-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7608255PMC
October 2020

Modeling the diffusion-weighted imaging signal for breast lesions in the b = 200 to 3000 s/mm range: quality of fit and classification accuracy for different representations.

Magn Reson Med 2020 08 23;84(2):1011-1023. Epub 2020 Jan 23.

Department of Physics, NTNU-Norwegian University of Science and Technology, Trondheim, Norway.

Purpose: To evaluate different non-Gaussian representations for the diffusion-weighted imaging (DWI) signal in the b-value range 200 to 3000 s/mm in benign and malignant breast lesions.

Methods: Forty-three patients diagnosed with benign (n = 18) or malignant (n = 25) tumors of the breast underwent DWI (b-values 200, 600, 1200, 1800, 2400, and 3000 s/mm ). Six different representations were fit to the average signal from regions of interest (ROIs) at different b-value ranges. Quality of fit was assessed by the corrected Akaike information criterion (AICc), and the Friedman test was used for assessing representation ranks. The area under the curve (AUC) of receiver operating characteristic curves were used to evaluate the power of derived parameters to differentiate between malignant and benign lesions. The lesion ROI was divided in central and peripheral parts to assess potential effect of heterogeneity. Sensitivity to noise-floor correction was also evaluated.

Results: The Padé exponent was ranked as the best based on AICc, whereas 3 models (kurtosis, fractional, and biexponential) achieved the highest AUC = 0.99 for lesion differentiation. The monoexponential model at b = 600 s/mm already provides AUC = 0.96, with considerably shorter acquisition time and simpler analysis. Significant differences between central and peripheral parts of lesions were found in malignant lesions. The mono- and biexponential models were most stable against varying degrees of noise-floor correction.

Conclusion: Non-Gaussian representations are required for fitting of the DWI curve at high b-values in breast lesions. However, the added clinical value from the high b-value data for differentiation of benign and malignant lesions is not clear.
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http://dx.doi.org/10.1002/mrm.28161DOI Listing
August 2020

Age dependence of modern clinical risk groups for localized prostate cancer-A population-based study.

Cancer 2020 04 3;126(8):1691-1699. Epub 2020 Jan 3.

Department of Radiation Medicine and Applied Sciences, University of California San Diego, La Jolla, California.

Background: Optimal prostate cancer (PCa) screening strategies will focus on men likely to have potentially lethal disease. Age-specific incidence rates (ASIRs) by modern clinical risk groups could inform risk stratification efforts for screening.

Methods: This cross-sectional population study identified all men diagnosed with PCa in Norway from 2014 to 2017 (n = 20,356). Age, Gleason score (primary plus secondary), and clinical stage were extracted. Patients were assigned to clinical risk groups: low, favorable intermediate, unfavorable intermediate, high, regional, and metastatic. Chi-square tests analyzed the independence of Gleason scores and modern PCa risk groups with age. ASIRs for each risk group were calculated as the product of Norwegian ASIRs for all PCa and the proportions observed for each risk category.

Results: Older age was significantly associated with a higher Gleason score and more advanced disease. The percentages of men with Gleason 8 to 10 disease among men aged 55 to 59, 65 to 69, 75 to 79, and 85 to 89 years were 16.5%, 23.4%, 37.2%, and 59.9%, respectively (P < .001); the percentages of men in the same age groups with at least high-risk disease were 29.3%, 39.1%, 60.4%, and 90.6%, respectively (P < .001). The maximum ASIRs (per 100,000 men) for low-risk, favorable intermediate-risk, unfavorable intermediate-risk, high-risk, regional, and metastatic disease were 157.1 for those aged 65 to 69 years, 183.8 for those aged 65 to 69 years, 194.8 for those aged 70 to 74 years, 408.3 for those aged 75 to 79 years, 159.7 for those aged ≥85 years, and 314.0 for those aged ≥85 years, respectively. At the ages of 75 to 79 years, the ASIR of high-risk disease was approximately 6 times greater than the ASIR at 55 to 59 years.

Conclusions: The risk of clinically significant localized PCa increases with age. Healthy older men may benefit from screening.
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http://dx.doi.org/10.1002/cncr.32702DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7103486PMC
April 2020

Multi-domain neurocognitive classification of primary brain tumor patients prior to radiotherapy on a prospective clinical trial.

J Neurooncol 2020 Jan 23;146(1):131-138. Epub 2019 Nov 23.

Department of Radiation Medicine and Applied Sciences, University of California San Diego, 3960 Health Sciences Dr, Mail Code 0865, La Jolla, CA, USA.

Introduction: We investigated multi-domain baseline neurocognition of primary brain tumor patients prior to radiotherapy (RT), including clinical predictors of function and association between pre-RT and post-RT impairment on a prospective trial.

Methods: A multi-domain neuropsychological battery (memory, executive functioning, language, attention, processing) was performed on 37 patients, pre-RT and 3-(n = 21), 6-(n = 22) and 12-(n = 14) months post-RT. Impairment rate was the proportion of patients with standardized T-scores ≤ 1.5 standard deviations below normative means. Per-patient impairment across all domains was calculated using a global deficit score (GDS; higher value indicates more impairment). Associations between baseline GDS and clinical variables were tested. Global GDS impairment rate at each time point was the fraction of patients with GDS scores > 0.5.

Results: Statistically significant baseline neurocognitive impairments were identified on 4 memory (all p ≤ 0.03) and 2 out of 3 (p = 0.01, p = 0.027) executive functioning tests. Per-patient baseline GDS was significantly associated with tumor volume (p = 0.048), tumor type (p = 0.043), seizure history (p = 0.007), and use of anti-epileptics (p = 0.009). The percentage of patients with the same impairment status at 3-, 6-, and 12-months as at baseline were 88%, 85%, and 85% respectively.

Conclusions: Memory and executive functioning impairment were the most common cognitive deficits prior to RT. Patients with larger tumors, more aggressive histology, and use of anti-epileptics had higher baseline GDS values. GDS is a promising tool to encompass multi-domain neurocognitive function, and baseline GDS can identify those at risk of cognitive impairment.
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http://dx.doi.org/10.1007/s11060-019-03353-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7025809PMC
January 2020

Quantitative Imaging Biomarkers of Damage to Critical Memory Regions Are Associated With Post-Radiation Therapy Memory Performance in Brain Tumor Patients.

Int J Radiat Oncol Biol Phys 2019 11 10;105(4):773-783. Epub 2019 Aug 10.

Department of Radiation Medicine and Applied Sciences; Center for Multimodal Imaging and Genetics. Electronic address:

Purpose: We used quantitative magnetic resonance imaging to prospectively analyze the association between microstructural damage to memory-associated structures within the medial temporal lobe and longitudinal memory performance after brain radiation therapy (RT).

Methods And Materials: Patients with a primary brain tumor receiving fractionated brain RT were enrolled on a prospective trial (n = 27). Patients underwent high-resolution volumetric brain magnetic resonance imaging, diffusion-weighted imaging, and neurocognitive testing before and 3, 6, and 12 months post-RT. Medial temporal lobe regions (hippocampus; entorhinal, parahippocampal, and temporal pole white matter [WM]) were autosegmented, quantifying volume and diffusion biomarkers of WM integrity (mean diffusivity [MD]; fractional anisotropy [FA]). Reliable change indices measured changes in verbal (Hopkins Verbal Learning Test-Revised) and visuospatial (Brief Visuospatial Memory Test-Revised [BVMT-R]) memory. Linear mixed-effects models assessed longitudinal associations between imaging parameters and memory.

Results: Visuospatial memory significantly declined at 6 months post-RT (mean reliable change indices, -1.3; P = .012). Concurrent chemotherapy and seizures trended toward a significant association with greater decline in visuospatial memory (P = .053 and P = .054, respectively). Higher mean dose to the left temporal pole WM was significantly associated with decreased FA (r = -0.667; P = .002). Over all time points, smaller right hippocampal volume (P = .021), lower right entorhinal FA (P = .023), greater right entorhinal MD (P = .047), and greater temporal pole MD (BVMT-R total recall, P = .003; BVMT-R delayed recall, P = .042) were associated with worse visuospatial memory. The interaction between right entorhinal MD (BVMT-R total recall, P = .021; BVMT-R delayed recall, P = .004) and temporal pole FA (BVMT-R delayed recall, P = .024) significantly predicted visuospatial memory performance.

Conclusions: Brain tumor patients exhibited visuospatial memory decline post-RT. Microstructural damage to critical memory regions, including the hippocampus and medial temporal lobe WM, were associated with post-RT memory decline. The integrity of medial temporal lobe structures is critical to memory performance post-RT, representing possible avoidance targets for memory preservation.
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http://dx.doi.org/10.1016/j.ijrobp.2019.08.003DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6876859PMC
November 2019

Dose-dependent atrophy of the amygdala after radiotherapy.

Radiother Oncol 2019 07 6;136:44-49. Epub 2019 Apr 6.

Department of Radiation Medicine and Applied Sciences, University of California San Diego, La Jolla, CA, United States; Department of Bioengineering, University of California San Diego, La Jolla, CA, United States. Electronic address:

Background And Purpose: The amygdalae are deep brain nuclei critical to emotional processing and the creation and storage of memory. It is not known whether the amygdalae are affected by brain radiotherapy (RT). We sought to quantify dose-dependent amygdala change one year after brain RT.

Materials And Methods: 52 patients with primary brain tumors were retrospectively identified. Study patients underwent high-resolution, volumetric magnetic resonance imaging before RT and 1 year afterward. Images were processed using FDA-cleared software for automated segmentation of amygdala volume. Tumor, surgical changes, and segmentation errors were manually censored. Mean amygdala RT dose was tested for correlation with amygdala volume change 1 year after RT via the Pearson correlation coefficient. A linear mixed-effects model was constructed to evaluate potential predictors of amygdala volume change, including age, tumor hemisphere, sex, seizure history, and bevacizumab treatment during the study period. As 51 of 52 patients received chemotherapy, possible chemotherapy effects could not be studied. A two-tailed p-value <0.05 was considered statistically significant.

Results: Mean amygdala RT dose (r = -0.28, p = 0.01) was significantly correlated with volume loss. On multivariable analysis, the only significant predictor of amygdala atrophy was radiation dose. The final linear mixed-effects model estimated amygdala volume loss of 0.17% for every 1 Gy increase in mean amygdala RT dose (p = 0.008).

Conclusions: The amygdala demonstrates dose-dependent atrophy one year after radiotherapy for brain tumors. Amygdala atrophy may mediate neuropsychological effects seen after brain RT.
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http://dx.doi.org/10.1016/j.radonc.2019.03.024DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7041546PMC
July 2019

Identifying early diffusion imaging biomarkers of regional white matter injury as indicators of executive function decline following brain radiotherapy: A prospective clinical trial in primary brain tumor patients.

Radiother Oncol 2019 03 20;132:27-33. Epub 2018 Dec 20.

Department of Psychiatry, University of California, San Diego, USA; Center for Multimodal Imaging and Genetics, University of California, San Diego, USA; Department of Radiation Medicine and Applied Sciences, University of California, San Diego, USA. Electronic address:

Background And Purpose: Executive function (EF) decline is common after brain radiation therapy (RT), yet the etiology is unclear. We analyzed the association between longitudinal changes in frontal lobe white matter microstructure and decline in EF following RT in brain tumor patients on a prospective clinical trial.

Materials And Methods: Diffusion tensor imaging was obtained on 22 patients with brain tumors prior to RT, as well as 3- and 6-months post-RT, in a prospective, observational trial. Fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), and axial diffusivity (AD) were calculated within the superficial white matter (SWM) of the anterior cingulate (AC) and dorsolateral prefrontal cortex. Measures of cognitive flexibility, verbal fluency, and verbal set-shifting were obtained pre- and post-RT. Reliable change indices were calculated to determine significant baseline to 6-month EF changes.

Results: Decreases in FA and increases in MD were observed in the caudal AC (CAC) at 3-months post-RT. CAC changes were characterized by increased RD bilaterally. From baseline to 6-months post-RT, decreased FA and increased MD and RD of the CAC was associated with decline in verbal set-shifting ability, whereas increased MD in the CAC was associated with a decline in cognitive flexibility.

Conclusion: White matter underlying the AC may be particularly vulnerable to radiation effects. Early microstructural loss within AC SWM represents an important biomarker for EF decline, and dose reduction in this region may represent a possibility for cognitive preservation for patients receiving radiotherapy.
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http://dx.doi.org/10.1016/j.radonc.2018.11.018DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6400307PMC
March 2019

Improved characterization of cerebral infarction using combined tissue T2 and high b-value diffusion MRI in post-thrombectomy patients: a feasibility study.

Acta Radiol 2019 Oct 9;60(10):1294-1300. Epub 2019 Jan 9.

Center for Multimodal Imaging and Genetics, University of California San Diego, La Jolla, CA, USA.

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http://dx.doi.org/10.1177/0284185118820063DOI Listing
October 2019

Molecular classification of patients with grade II/III glioma using quantitative MRI characteristics.

J Neurooncol 2018 Sep 2;139(3):633-642. Epub 2018 Jun 2.

Center for Multimodal Imaging and Genetics (CMIG), University of California, San Diego, La Jolla, CA, 92037, USA.

Background: Molecular markers of WHO grade II/III glioma are known to have important prognostic and predictive implications and may be associated with unique imaging phenotypes. The purpose of this study is to determine whether three clinically relevant molecular markers identified in gliomas-IDH, 1p/19q, and MGMT status-show distinct quantitative MRI characteristics on FLAIR imaging.

Methods: Sixty-one patients with grade II/III gliomas who had molecular data and MRI available prior to radiation were included. Quantitative MRI features were extracted that measured tissue heterogeneity (homogeneity and pixel correlation) and FLAIR border distinctiveness (edge contrast; EC). T-tests were conducted to determine whether patients with different genotypes differ across the features. Logistic regression with LASSO regularization was used to determine the optimal combination of MRI and clinical features for predicting molecular subtypes.

Results: Patients with IDH wildtype tumors showed greater signal heterogeneity (p = 0.001) and lower EC (p = 0.008) within the FLAIR region compared to IDH mutant tumors. Among patients with IDH mutant tumors, 1p/19q co-deleted tumors had greater signal heterogeneity (p = 0.002) and lower EC (p = 0.005) compared to 1p/19q intact tumors. MGMT methylated tumors showed lower EC (p = 0.03) compared to the unmethylated group. The combination of FLAIR border distinctness, heterogeneity, and pixel correlation optimally classified tumors by IDH status.

Conclusion: Quantitative imaging characteristics of FLAIR heterogeneity and border pattern in grade II/III gliomas may provide unique information for determining molecular status at time of initial diagnostic imaging, which may then guide subsequent surgical and medical management.
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http://dx.doi.org/10.1007/s11060-018-2908-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8120480PMC
September 2018

Analyses of regional radiosensitivity of white matter structures along tract axes using novel white matter segmentation and diffusion imaging biomarkers.

Phys Imaging Radiat Oncol 2018 Apr 1;6:39-46. Epub 2018 May 1.

Department of Radiation Medicine and Applied Sciences, University of California San Diego, La Jolla, CA, USA.

Background And Purpose: Brain radiotherapy (RT) can cause white matter damage and downstream neurocognitive decline. We developed a computational neuroimaging tool to regionally partition individual white matter tracts, then analyze regional changes in diffusion metrics of white matter damage following brain RT.

Materials And Methods: RT dose, diffusion metrics and white matter tract structures were extracted and mapped to a reference brain for 49 patients who received brain RT, and underwent diffusion tensor imaging pre- and 9-12 months post-RT. Based on their elongation, 23 of 48 white matter tracts were selected. The Tract-Crawler software was developed in MATLAB to create cross-sectional slice planes normal to a tract's computed medial axis. We then performed slice- and voxel-wise analysis of radiosensitivity, defined as percent change in mean diffusivity (MD) and fractional anisotropy (FA) as a function of dose relative to baseline.

Results: Distinct patterns of FA/MD radiosensitivity were seen for specific tracts, including the corticospinal tract, medial lemniscus, and inferior cerebellar peduncle, in particular at terminal ends. These patterns persisted for corresponding tracts in left and right hemispheres. Local sensitivities were as high as 40%/Gy (e.g., voxel-wise: -39 ± 31%/Gy in right corticospinal tract FA, -45 ± 25%/Gy in right inferior cerebellar peduncle FA), p < 0.05.

Conclusions: Tract-Crawler, a novel tool to visualize and analyze cuts of white matter structures normal to medial axes, was used to demonstrate that particular white matter tracts exhibit significant regional variations in radiosensitivity based on diffusion biomarkers.
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http://dx.doi.org/10.1016/j.phro.2018.04.003DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7807616PMC
April 2018

Relationship between kurtosis and bi-exponential characterization of high b-value diffusion-weighted imaging: application to prostate cancer.

Acta Radiol 2018 Dec 17;59(12):1523-1529. Epub 2018 Apr 17.

2 Department of Radiology, University of California San Diego, La Jolla, CA, USA.

Background: High b-value diffusion-weighted imaging has application in the detection of cancerous tissue across multiple body sites. Diffusional kurtosis and bi-exponential modeling are two popular model-based techniques, whose performance in relation to each other has yet to be fully explored.

Purpose: To determine the relationship between excess kurtosis and signal fractions derived from bi-exponential modeling in the detection of suspicious prostate lesions.

Material And Methods: This retrospective study analyzed patients with normal prostate tissue (n = 12) or suspicious lesions (n = 13, one lesion per patient), as determined by a radiologist whose clinical care included a high b-value diffusion series. The observed signal intensity was modeled using a bi-exponential decay, from which the signal fraction of the slow-moving component was derived ( SFs). In addition, the excess kurtosis was calculated using the signal fractions and ADCs of the two exponentials ( KCOMP). As a comparison, the kurtosis was also calculated using the cumulant expansion for the diffusion signal ( KCE).

Results: Both K and KCE were found to increase with SFs within the range of SFs commonly found within the prostate. Voxel-wise receiver operating characteristic performance of SFs, KCE, and KCOMP in discriminating between suspicious lesions and normal prostate tissue was 0.86 (95% confidence interval [CI] = 0.85 - 0.87), 0.69 (95% CI = 0.68-0.70), and 0.86 (95% CI = 0.86-0.87), respectively.

Conclusion: In a two-component diffusion environment, KCOMP is a scaled value of SFs and is thus able to discriminate suspicious lesions with equal precision . KCE provides a computationally inexpensive approximation of kurtosis but does not provide the same discriminatory abilities as SFs and KCOMP.
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http://dx.doi.org/10.1177/0284185118770889DOI Listing
December 2018

4π plan optimization for cortical-sparing brain radiotherapy.

Radiother Oncol 2018 04 5;127(1):128-135. Epub 2018 Mar 5.

Department of Radiation Medicine and Applied Sciences, University of California San Diego, La Jolla, California, United States. Electronic address:

Background And Purpose: Incidental irradiation of normal brain tissue during radiotherapy is linked to cognitive decline, and may be mediated by damage to healthy cortex. Non-coplanar techniques may be used for cortical sparing. We compared normal brain sparing and probability of cortical atrophy using 4π radiation therapy planning vs. standard fixed gantry intensity-modulated radiotherapy (IMRT).

Material And Methods: Plans from previously irradiated brain tumor patients ("original IMRT", n = 13) were re-planned to spare cortex using both 4π optimization ("4π") and IMRT optimization ("optimized IMRT"). Homogeneity index (HI), gradient measure, doses to cortex and white matter (excluding tumor), brainstem, optics, and hippocampus were compared with matching PTV coverage. Probability of three grades of post-treatment cortical atrophy was modeled based on previously established dose response curves.

Results: With matching PTV coverage, 4π significantly improved HI by 27% (p = 0.005) and gradient measure by 8% (p = 0.001) compared with optimized IMRT. 4π optimization reduced mean and equivalent uniform doses (EUD) to all standard OARs, with 14-15% reduction in hippocampal EUD (p ≤ 0.003) compared with the other two plans. 4π significantly reduced dose to fractional cortical volumes (V, V and V) compared with the original IMRT plans, and reduced cortical V by 7% (p = 0.008) compared with optimized IMRT. White matter EUD, mean dose, and fractional volumes V, V and V were also significantly lower with 4π (p ≤ 0.001). With 4π, probability of grade 1, 2 and 3 cortical atrophy decreased by 12%, 21% and 26% compared with original IMRT and by 8%, 14% and 3% compared with optimized IMRT, respectively (p ≤ 0.001).

Conclusions: 4π radiotherapy significantly improved cortical sparing and reduced doses to standard brain OARs, white matter, and the hippocampus. This was achieved with superior PTV dose homogeneity. Such sparing could reduce the probability of cortical atrophy that may lead to cognitive decline.
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http://dx.doi.org/10.1016/j.radonc.2018.02.011DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6084493PMC
April 2018

Polygenic hazard score to guide screening for aggressive prostate cancer: development and validation in large scale cohorts.

BMJ 2018 01 10;360:j5757. Epub 2018 Jan 10.

Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Strangeways Research Laboratory, Cambridge, UK.

Objectives: To develop and validate a genetic tool to predict age of onset of aggressive prostate cancer (PCa) and to guide decisions of who to screen and at what age.

Design: Analysis of genotype, PCa status, and age to select single nucleotide polymorphisms (SNPs) associated with diagnosis. These polymorphisms were incorporated into a survival analysis to estimate their effects on age at diagnosis of aggressive PCa (that is, not eligible for surveillance according to National Comprehensive Cancer Network guidelines; any of Gleason score ≥7, stage T3-T4, PSA (prostate specific antigen) concentration ≥10 ng/L, nodal metastasis, distant metastasis). The resulting polygenic hazard score is an assessment of individual genetic risk. The final model was applied to an independent dataset containing genotype and PSA screening data. The hazard score was calculated for these men to test prediction of survival free from PCa.

Setting: Multiple institutions that were members of international PRACTICAL consortium.

Participants: All consortium participants of European ancestry with known age, PCa status, and quality assured custom (iCOGS) array genotype data. The development dataset comprised 31 747 men; the validation dataset comprised 6411 men.

Main Outcome Measures: Prediction with hazard score of age of onset of aggressive cancer in validation set.

Results: In the independent validation set, the hazard score calculated from 54 single nucleotide polymorphisms was a highly significant predictor of age at diagnosis of aggressive cancer (z=11.2, P<10). When men in the validation set with high scores (>98th centile) were compared with those with average scores (30th-70th centile), the hazard ratio for aggressive cancer was 2.9 (95% confidence interval 2.4 to 3.4). Inclusion of family history in a combined model did not improve prediction of onset of aggressive PCa (P=0.59), and polygenic hazard score performance remained high when family history was accounted for. Additionally, the positive predictive value of PSA screening for aggressive PCa was increased with increasing polygenic hazard score.

Conclusions: Polygenic hazard scores can be used for personalised genetic risk estimates that can predict for age at onset of aggressive PCa.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5759091PMC
http://dx.doi.org/10.1136/bmj.j5757DOI Listing
January 2018

Unilateral hippocampal wasting after combined-modality therapy for glioblastoma.

Acta Oncol 2018 05 10;57(5):688-691. Epub 2017 Nov 10.

a Department of Radiation Medicine and Applied Sciences , University of California , San Diego, La Jolla , CA , USA.

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http://dx.doi.org/10.1080/0284186X.2017.1398412DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6086579PMC
May 2018

Erratum to: Imaging correlates for the 2016 update on WHO classification of grade II/III gliomas: implications for IDH, 1p/19q and ATRX status.

J Neurooncol 2017 12;135(3):611

Department of Radiology, University of California, San Diego, 200 West Arbor Drive, La Jolla, CA, 92037, USA.

In the initial online publication, the values in the last two rows in Table 1 were in the wrong rows. The original article has been corrected.
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http://dx.doi.org/10.1007/s11060-017-2620-8DOI Listing
December 2017
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