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1.
Artigo em Inglês | MEDLINE | ID: mdl-33420416

RESUMO

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.

2.
Int J Cancer ; 148(1): 99-105, 2021 Jan 01.
Artigo em Inglês | MEDLINE | ID: mdl-32930425

RESUMO

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.

3.
J Magn Reson Imaging ; 2020 Oct 31.
Artigo em Inglês | MEDLINE | ID: mdl-33131186

RESUMO

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 mm2 /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.

4.
Eur J Hum Genet ; 28(10): 1467-1475, 2020 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-32514134

RESUMO

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 HR98/50 (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 HR98/50 of the Discovery-SNP model increased from 1.05 [0.93-1.18] to 2.19 [2.16-2.23]. HR98/50 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.

6.
Acta Radiol ; 59(12): 1523-1529, 2018 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-29665707

RESUMO

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.


Assuntos
Imagem de Difusão por Ressonância Magnética/métodos , Neoplasias da Próstata/diagnóstico por imagem , Adulto , Idoso , Idoso de 80 Anos ou mais , Humanos , Interpretação de Imagem Assistida por Computador/métodos , Masculino , Pessoa de Meia-Idade , Próstata/diagnóstico por imagem , Reprodutibilidade dos Testes , Estudos Retrospectivos
7.
Acta Oncol ; 56(3): 427-430, 2017 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-28156177

RESUMO

BACKGROUND: Radiation-induced cognitive impairment may be mediated by hippocampal damage, but the structural integrity of this region in tumor patients at baseline is unclear. Hippocampal volumes of 31 glioma patients prior to receiving radiotherapy were compared to a group of 34 healthy controls. MATERIALS AND METHODS: Left and right hippocampi on T1-weighted pre-contrast magnetic resonance images were automatically segmented using Freesurfer, and visually inspected for segmentation errors. Normalized hippocampal volume for each subject was calculated as the sum of left and right hippocampal volumes divided by the estimated total intracranial volume. The normalized amygdala volume was similarly analyzed as a reference structure. RESULTS: A Wilcoxon rank-sum test showed a significant difference in normalized hippocampal volumes between patients and controls (mean value 0.499 vs. 0.524, p = .01). No statistically significant difference was found for the amygdala. A post-hoc analysis revealed a significant difference in normalized hippocampal volumes between patients who had experienced seizures (mean value: 0.480, p < .05) and controls. No difference was noted between patients without seizures (mean value: 0.513) and controls. CONCLUSIONS: Hippocampi of glioma patients prior to radiotherapy were significantly smaller than those of age-matched controls. Group differences were larger in patients with tumor-associated seizures. This may be secondary to other processes such as tumor biology and inflammation.


Assuntos
Neoplasias Encefálicas/patologia , Neoplasias Encefálicas/radioterapia , Glioma/patologia , Glioma/radioterapia , Hipocampo/patologia , Adulto , Idoso , Neoplasias Encefálicas/diagnóstico por imagem , Estudos de Casos e Controles , Feminino , Glioma/diagnóstico por imagem , Hipocampo/diagnóstico por imagem , Humanos , Imagem por Ressonância Magnética , Masculino , Pessoa de Meia-Idade , Tamanho do Órgão/efeitos da radiação , Adulto Jovem
8.
Med Phys ; 44(5): 1747-1754, 2017 May.
Artigo em Inglês | MEDLINE | ID: mdl-28222217

RESUMO

PURPOSE: We used multi-b-value diffusion models to characterize microstructural white matter changes after brain radiation into fast and slow components, in order to better understand the pathophysiology of radiation-induced tissue damage. METHODS: Fourteen patients were included in this retrospective analysis with imaging prior to, and at 1, 4-5, and 9-10 months after radiotherapy (RT). Diffusion signal decay within brain white matter was fit to a biexponential model to separate changes within the slow and fast components. Linear mixed-effects models were used to obtain estimates of the effect of radiation dose and time on the model parameters. RESULTS: We found an increase of 0.11 × 10-4 and 0.14 × 10-4 mm2 /s in the fast diffusion coefficient per unit dose-time (Gy-month) in the longitudinal and transverse directions, respectively. By contrast, the longitudinal slow diffusion coefficient decreased independently of dose, by 0.18 × 10-4 , 0.16 × 10-4 , and 0.098 × 10-4 mm2 /s at 1, 4, and 9 months post-RT, respectively. CONCLUSIONS: Radiation-induced white matter changes in the first year following RT are driven by dose-dependent increases in the fast component and dose-independent decreases in the slow component.


Assuntos
Neoplasias Encefálicas/radioterapia , Imagem de Difusão por Ressonância Magnética , Substância Branca/patologia , Encéfalo , Difusão , Humanos , Estudos Retrospectivos , Substância Branca/efeitos da radiação
9.
Radiother Oncol ; 118(1): 29-34, 2016 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-26806266

RESUMO

BACKGROUND AND PURPOSE: Neurocognitive decline in brain tumor patients treated with radiotherapy (RT) may be linked to cortical atrophy. We developed models to determine radiation treatment-planning objectives for cortex, which were tested on a sample population to identify the dosimetric cost of cortical sparing. MATERIAL AND METHODS: The relationship between the probability of cortical atrophy in fifteen high-grade glioma patients at 1-year post-RT and radiation dose was fit using logistic mixed effects modeling. Cortical sparing was implemented using two strategies: region-specific sparing using model parameters, and non-specific sparing of all normal brain tissue. RESULTS: A dose threshold of 28.6 Gy was found to result in a 20% probability of severe atrophy. Average cortical sparing at 30 Gy was greater for region-specific dose avoidance (4.6%) compared to non-specific (3.6%). Cortical sparing resulted in an increase in heterogeneity index of the planning target volume (PTV) with an average increase of 1.9% (region-specific) and 0.9% (non-specific). CONCLUSIONS: We found RT doses above 28.6 Gy resulted in a greater than 20% probability of cortical atrophy. Cortical sparing can be achieved using region-specific or non-specific dose avoidance strategies at the cost of an increase in the dose heterogeneity of the PTV.


Assuntos
Neoplasias Encefálicas/radioterapia , Córtex Cerebral/efeitos da radiação , Glioma/radioterapia , Neuroimagem/métodos , Lesões por Radiação/prevenção & controle , Planejamento da Radioterapia Assistida por Computador/métodos , Adulto , Atrofia/prevenção & controle , Neoplasias Encefálicas/patologia , Córtex Cerebral/patologia , Estudos de Coortes , Estudos de Viabilidade , Feminino , Glioma/patologia , Humanos , Imagem por Ressonância Magnética , Masculino , Dosagem Radioterapêutica
10.
Radiother Oncol ; 118(1): 72-8, 2016 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-26674924

RESUMO

BACKGROUND AND PURPOSE: We compared [(18)F]fluoro-2-deoxy-2-d-glucose (FDG) versus 3'-deoxy-3'-[(18)F]fluorothymidine (FLT) for the purpose of identifying active pelvic bone marrow (BM), quantifying its locational variation, and determining which technique is likely to be better for BM-sparing radiation planning. MATERIAL AND METHODS: We sampled 41 patients, of which 25 underwent FDG-PET/CT only, 7 underwent FLT-PET/CT only, and 9 underwent both. Active BM subvolumes were defined as subsets of the pelvic BM with the highest standardized uptake values comprising 40%, 50%, and 60% of the total pelvic BM volume. We used the Dice similarity coefficient to quantify the percent overlap of active BM volumes of equal size. Differences in the spatial distribution of active BM were assessed using a region-growing algorithm. RESULTS: For patients with both modalities, the mean Dice coefficients for the 40%, 50%, and 60% subvolumes were 0.683, 0.732, and 0.781 respectively. Comparing individual active BM subvolumes to the mean subvolume, Dice coefficients varied from 0.598-0.889 for FDG and 0.739-0.912 for FLT. Region growing analysis showed FLT-PET defined more highly clustered active BM subvolumes. CONCLUSIONS: Within the limitations of a small sample size, we found significant agreement between FDG-PET and FLT-PET; however, FLT-PET had significantly less individual variation and is likely to be superior to FDG-PET for BM-sparing radiotherapy.


Assuntos
Medula Óssea/efeitos da radiação , Neoplasias do Colo do Útero/radioterapia , Adulto , Idoso , Idoso de 80 Anos ou mais , Algoritmos , Medula Óssea/diagnóstico por imagem , Didesoxinucleosídeos , Feminino , Fluordesoxiglucose F18 , Humanos , Masculino , Pessoa de Meia-Idade , Tratamentos com Preservação do Órgão/métodos , Ossos Pélvicos/diagnóstico por imagem , Ossos Pélvicos/efeitos da radiação , Tomografia por Emissão de Pósitrons/métodos , Planejamento da Radioterapia Assistida por Computador/métodos , Tomografia Computadorizada por Raios X/métodos
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