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2.
Artigo em Inglês | MEDLINE | ID: mdl-33723363

RESUMO

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 < 10-15). 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.

3.
J Magn Reson Imaging ; 2021 Mar 31.
Artigo em Inglês | MEDLINE | ID: mdl-33786915

RESUMO

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.

4.
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.

5.
Clin Cancer Res ; 2020 Nov 04.
Artigo em Inglês | MEDLINE | ID: mdl-33148675

RESUMO

PURPOSE: Diffusion-weighted magnetic resonance imaging (DW-MRI) is a contrast-free modality that has demonstrated ability to discriminate between pre-defined benign and malignant breast lesions. However, how well DW-MRI discriminates cancer from all other breast tissue voxels in a clinical setting is unknown. Here we explore the voxel-wise ability to distinguish cancer from healthy breast tissue using signal contributions from the newly developed three-component multi-b-value DW-MRI model. EXPERIMENTAL DESIGN: Pathology-proven breast cancer patients from two datasets (n=81 and n=25) underwent multi-b-value DW-MRI. The three-component signal contributions C1 and C2 and their product, C1C2, and signal fractions F1, F2 and F1F2 were compared to the image defined on maximum b-value (DWImax), conventional apparent diffusion coefficient (ADC), and apparent diffusion kurtosis (Kapp). The ability to discriminate between cancer and healthy breast tissue was assessed by the false positive rate given a sensitivity of 80% (FPR80) and receiver operating characteristic (ROC) area under the curve (AUC). RESULTS: Mean FPR80 for both datasets was 0.016 (95%CI=0.008-0.024) for C1C2, 0.136 (95%CI=0.092-0.180) for C1, 0.068 (95%CI=0.049-0.087) for C2, 0.462 (95%CI=0.425-0.499) for F1F2, 0.832 (95%CI=0.797-0.868) for F1, 0.176 (95%CI=0.150-0.203) for F2, 0.159 (95%CI=0.114-0.204) for DWImax, 0.731 (95%CI=0.692-0.770) for ADC and 0.684 (95%CI=0.660-0.709) for Kapp Mean ROC AUC for C1C2 was 0.984 (95%CI=0.977-0.991). CONCLUSIONS: The C1C2 parameter of the three-component model yields a clinically useful discrimination between cancer and healthy breast tissue, superior to other DW-MRI methods and obliviating pre-defining lesions. This novel DW-MRI method may serve as non-contrast alternative to standard-of-care dynamic contrast-enhanced MRI (DCE-MRI).

6.
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.

7.
Radiat Oncol ; 15(1): 251, 2020 Oct 30.
Artigo em Inglês | MEDLINE | ID: mdl-33126894

RESUMO

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.

9.
Front Oncol ; 10: 24, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32047723

RESUMO

Immunotherapy is increasingly used in the treatment of glioblastoma (GBM), with immune checkpoint therapy gaining in popularity given favorable outcomes achieved for other tumors. However, immune-mediated (IM)-pseudoprogression is common, remains poorly characterized, and renders conventional imaging of little utility when evaluating for treatment response. We present the case of a 64-year-old man with GBM who developed pathologically proven IM-pseudoprogression after initiation of a checkpoint inhibitor, and who subsequently developed true tumor progression at a distant location. Based on both qualitative and quantitative analysis, we demonstrate that an advanced diffusion-weighted imaging (DWI) technique called restriction spectrum imaging (RSI) can differentiate IM-pseudoprogression from true progression even when conventional imaging, including standard DWI/apparent diffusion coefficient (ADC), is not informative. These data complement existing literature supporting the ability of RSI to estimate tumor cellularity, which may help to resolve complex diagnostic challenges such as the identification of IM-pseudoprogression.

10.
Cancer ; 126(8): 1691-1699, 2020 04 15.
Artigo em Inglês | MEDLINE | ID: mdl-31899813

RESUMO

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.


Assuntos
Próstata/patologia , Neoplasias da Próstata/patologia , Idoso , Idoso de 80 Anos ou mais , Estudos Transversais , Humanos , Masculino , Pessoa de Meia-Idade , Gradação de Tumores/métodos , Noruega , Próstata/metabolismo , Antígeno Prostático Específico/metabolismo , Neoplasias da Próstata/metabolismo , Fatores de Risco
11.
J Neurooncol ; 146(1): 131-138, 2020 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-31760596

RESUMO

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.


Assuntos
Neoplasias Encefálicas/radioterapia , Função Executiva/efeitos da radiação , Transtornos da Memória/patologia , Transtornos Neurocognitivos/patologia , Radioterapia/efeitos adversos , Adulto , Neoplasias Encefálicas/patologia , Feminino , Seguimentos , Humanos , Masculino , Transtornos da Memória/etiologia , Pessoa de Meia-Idade , Transtornos Neurocognitivos/classificação , Transtornos Neurocognitivos/etiologia , Testes Neuropsicológicos , Prognóstico , Estudos Prospectivos
12.
J Cardiovasc Comput Tomogr ; 13(4): 203-210, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31104941

RESUMO

BACKGROUND: Genetic risk scores (GRSs) have been associated with CHD events and coronary artery calcium (CAC). We sought to evaluate the ability of a GRS to improve CAC as a screening test. METHODS: Using the results of the most recent genome-wide association studies, we calculated a GRS in 6660 individuals from the Multi-Ethnic Study of Atherosclerosis and used it to determine the optimal age for an individual to undergo CAC screening. RESULTS: This 157-SNP GRS was predictive of non-zero CAC in individuals aged 44-54 and improved the positive yield of CAC as a screening test in this age group. The GRS was predictive of CAC in the entire multi-ethnic cohort and in each self-identified ethnic group (European American, Chinese American, African American, and Hispanic American) assessed individually. Given a specified target yield rate of non-zero CAC, an equation was derived to calculate an individual's optimal age to undergo CAC screening. In addition, a "direct-to-consumer" GRS consisting of only risk SNPs or their proxies that are directly genotyped on the 23andMe v5 chip (102-SNP GRS) was assessed in the European American population and was predictive of non-zero CAC in younger individuals. CONCLUSION: A GRS is associated with non-zero CAC in a multi-ethnic cohort and can be used to calculate the age of a person's first calcium scan, given a target threshold for CAC discovery. Furthermore, an inexpensive and widely available "direct-to-consumer" GRS was found to be a viable option to calculate the optimal age for CAC screening.


Assuntos
Angiografia Coronária , Doença da Artéria Coronariana/diagnóstico por imagem , Doença da Artéria Coronariana/genética , Testes Genéticos , Polimorfismo de Nucleotídeo Único , Calcificação Vascular/diagnóstico por imagem , Calcificação Vascular/genética , Adulto , Fatores Etários , Idoso , Idoso de 80 Anos ou mais , Tomada de Decisão Clínica , Doença da Artéria Coronariana/etnologia , Feminino , Predisposição Genética para Doença , Humanos , Masculino , Pessoa de Meia-Idade , Fenótipo , Valor Preditivo dos Testes , Medição de Risco , Fatores de Risco , Estados Unidos/epidemiologia , Calcificação Vascular/etnologia
13.
Radiother Oncol ; 136: 44-49, 2019 07.
Artigo em Inglês | MEDLINE | ID: mdl-31015128

RESUMO

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.


Assuntos
Tonsila do Cerebelo/patologia , Tonsila do Cerebelo/efeitos da radiação , Neoplasias Encefálicas/radioterapia , Lesões por Radiação/patologia , Adulto , Idoso , Tonsila do Cerebelo/diagnóstico por imagem , Atrofia/etiologia , Neoplasias Encefálicas/diagnóstico por imagem , Irradiação Craniana/efeitos adversos , Irradiação Craniana/métodos , Feminino , Humanos , Imagem por Ressonância Magnética/métodos , Masculino , Memória/efeitos da radiação , Pessoa de Meia-Idade , Estudos Retrospectivos , Adulto Jovem
14.
Radiother Oncol ; 132: 27-33, 2019 03.
Artigo em Inglês | MEDLINE | ID: mdl-30825966

RESUMO

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.


Assuntos
Neoplasias Encefálicas/radioterapia , Função Executiva/efeitos da radiação , Lesões por Radiação/diagnóstico por imagem , Lesões por Radiação/psicologia , Substância Branca/diagnóstico por imagem , Substância Branca/efeitos da radiação , Biomarcadores , Encéfalo/diagnóstico por imagem , Encéfalo/patologia , Encéfalo/efeitos da radiação , Neoplasias Encefálicas/diagnóstico por imagem , Neoplasias Encefálicas/patologia , Imagem de Tensor de Difusão/métodos , Feminino , Humanos , Estudos Longitudinais , Masculino , Pessoa de Meia-Idade , Estudos Prospectivos , Lesões por Radiação/patologia , Lesões por Radiação/fisiopatologia
15.
J Neurooncol ; 139(3): 633-642, 2018 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-29860714

RESUMO

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.


Assuntos
Neoplasias Encefálicas/classificação , Neoplasias Encefálicas/diagnóstico por imagem , Glioma/classificação , Glioma/diagnóstico por imagem , Imagem por Ressonância Magnética , Adulto , Idoso , Neoplasias Encefálicas/genética , Neoplasias Encefálicas/patologia , Metilação de DNA , Metilases de Modificação do DNA/genética , Metilases de Modificação do DNA/metabolismo , Enzimas Reparadoras do DNA/genética , Enzimas Reparadoras do DNA/metabolismo , Feminino , Glioma/genética , Glioma/patologia , Humanos , Imageamento Tridimensional , Isocitrato Desidrogenase/genética , Isocitrato Desidrogenase/metabolismo , Masculino , Pessoa de Meia-Idade , Gradação de Tumores , Estudos Retrospectivos , Proteínas Supressoras de Tumor/genética , Proteínas Supressoras de Tumor/metabolismo , Adulto Jovem
16.
Int J Radiat Oncol Biol Phys ; 101(1): 235, 2018 05 01.
Artigo em Inglês | MEDLINE | ID: mdl-29619968
17.
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
18.
Radiother Oncol ; 127(1): 128-135, 2018 04.
Artigo em Inglês | MEDLINE | ID: mdl-29519628

RESUMO

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 (V50, V40 and V30) compared with the original IMRT plans, and reduced cortical V30 by 7% (p = 0.008) compared with optimized IMRT. White matter EUD, mean dose, and fractional volumes V50, V40 and V30 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.


Assuntos
Neoplasias Encefálicas/radioterapia , Córtex Cerebral/efeitos da radiação , Órgãos em Risco/efeitos da radiação , Planejamento da Radioterapia Assistida por Computador/métodos , Radioterapia de Intensidade Modulada/métodos , Adulto , Idoso , Neoplasias Encefálicas/diagnóstico por imagem , Córtex Cerebral/diagnóstico por imagem , Feminino , Hipocampo/diagnóstico por imagem , Hipocampo/efeitos da radiação , Humanos , Imagem por Ressonância Magnética , Masculino , Pessoa de Meia-Idade , Órgãos em Risco/diagnóstico por imagem , Probabilidade , Lesões por Radiação/etiologia , Lesões por Radiação/prevenção & controle , Dosagem Radioterapêutica , Radioterapia de Intensidade Modulada/efeitos adversos , Estudos Retrospectivos
19.
BMJ ; 360: j5757, 2018 01 10.
Artigo em Inglês | MEDLINE | ID: mdl-29321194

RESUMO

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<10-16). 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.


Assuntos
Detecção Precoce de Câncer/métodos , Calicreínas/análise , Polimorfismo de Nucleotídeo Único/genética , Antígeno Prostático Específico/análise , Neoplasias da Próstata/sangue , Neoplasias da Próstata/genética , Idade de Início , Idoso , Estudos de Coortes , Intervalo Livre de Doença , Grupo com Ancestrais do Continente Europeu/genética , Genótipo , Humanos , Masculino , Pessoa de Meia-Idade , Avaliação de Resultados em Cuidados de Saúde , Valor Preditivo dos Testes , Neoplasias da Próstata/diagnóstico , Medição de Risco , Análise de Sobrevida
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