5 research outputs found

    Deep-Learning for Epicardial Adipose Tissue Assessment with Computed Tomography: Implications for Cardiovascular Risk Prediction

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    Background: Epicardial adipose tissue (EAT) volume is a marker of visceral obesity that can be measured in coronary computed tomography angiograms (CCTA). The clinical value of integrating this measurement in routine CCTA interpretation has not been documented./ Objectives: This study sought to develop a deep-learning network for automated quantification of EAT volume from CCTA, test it in patients who are technically challenging, and validate its prognostic value in routine clinical care./ Methods: The deep-learning network was trained and validated to autosegment EAT volume in 3,720 CCTA scans from the ORFAN (Oxford Risk Factors and Noninvasive Imaging Study) cohort. The model was tested in patients with challenging anatomy and scan artifacts and applied to a longitudinal cohort of 253 patients post-cardiac surgery and 1,558 patients from the SCOT-HEART (Scottish Computed Tomography of the Heart) Trial, to investigate its prognostic value./ Results: External validation of the deep-learning network yielded a concordance correlation coefficient of 0.970 for machine vs human. EAT volume was associated with coronary artery disease (odds ratio [OR] per SD increase in EAT volume: 1.13 [95% CI: 1.04-1.30]; P = 0.01), and atrial fibrillation (OR: 1.25 [95% CI:1.08-1.40]; P = 0.03), after correction for risk factors (including body mass index). EAT volume predicted all-cause mortality (HR per SD: 1.28 [95% CI: 1.10-1.37]; P = 0.02), myocardial infarction (HR: 1.26 [95% CI:1.09-1.38]; P = 0.001), and stroke (HR: 1.20 [95% CI: 1.09-1.38]; P = 0.02) independently of risk factors in SCOT-HEART (5-year follow-up). It also predicted in-hospital (HR: 2.67 [95% CI: 1.26-3.73]; P ≤ 0.01) and long-term post–cardiac surgery atrial fibrillation (7-year follow-up; HR: 2.14 [95% CI: 1.19-2.97]; P ≤ 0.01). Conclusions: Automated assessment of EAT volume is possible in CCTA, including in patients who are technically challenging; it forms a powerful marker of metabolically unhealthy visceral obesity, which could be used for cardiovascular risk stratification

    DNA Repair in Prostate Cancer: Biology and Clinical Implications

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    CONTEXT: For more precise, personalized care in prostate cancer (PC), a new classification based on molecular features relevant for prognostication and treatment stratification is needed. Genomic aberrations in the DNA damage repair pathway are common in PC, particularly in late-stage disease, and may be relevant for treatment stratification. OBJECTIVE: To review current knowledge on the prevalence and clinical significance of aberrations in DNA repair genes in PC, particularly in metastatic disease. EVIDENCE ACQUISITION: A literature search up to July 2016 was conducted, including clinical trials and preclinical basic research studies. Keywords included DNA repair, BRCA, ATM, CRPC, prostate cancer, PARP, platinum, predictive biomarkers, and hereditary cancer. EVIDENCE SYNTHESIS: We review how the DNA repair pathway is relevant to prostate carcinogenesis and progression. Data on how this may be relevant to hereditary cancer and genetic counseling are included, as well as data from clinical trials of PARP inhibitors and platinum therapeutics in PC. CONCLUSIONS: Relevant studies have identified genomic defects in DNA repair in PCs in 20-30% of advanced castration-resistant PC cases, a proportion of which are germline aberrations and heritable. Phase 1/2 clinical trial data, and other supporting clinical data, support the development of PARP inhibitors and DNA-damaging agents in this molecularly defined subgroup of PC following success in other cancer types. These studies may be an opportunity to improve patient care with personalized therapeutic strategies. PATIENT SUMMARY: Key literature on how genomic defects in the DNA damage repair pathway are relevant for prostate cancer biology and clinical management is reviewed. Potential implications for future changes in patient care are discussed

    Scattering attenuation microscopy of oral epithelial dysplasia

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    We present a new method for quantitative visualization of premalignant oral epithelium called scattering attenuation microscopy (SAM). Using low-coherence interferometry, SAM projects measurements of epithelial optical attenuation onto an image of the tissue surface as a color map. The measured attenuation is dominated by optical scattering that provides a metric of the severity of oral epithelial dysplasia (OED). Scattering is sensitive to the changes in size and distribution of nuclear material that are characteristic of OED, a condition recognized by the occurrence of basal-cell-like features throughout the epithelial depth. SAM measures the axial intensity change of light backscattered from epithelial tissue. Scattering measurements are obtained from sequential axial scans of a 3-D tissue volume and displayed as a 2-D SAM image. A novel segmentation method is used to confine scattering measurement to epithelial tissue. This is applied to oral biopsy samples obtained from 19 patients. Our results show that imaging of tissue scattering can be used to discriminate between different dysplastic severities and furthermore presents a powerful tool for identifying the most representative tissue site for biops
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