Cancers
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The knowledge on thyroid cancer biology has grown over the past decade. Thus, diagnostic and therapeutic strategies to manage thyroid cancer are rapidly evolving. With new insights into tumor biology and cancer genetics, several novel therapies have been approved for the treatment of thyroid cancer. ⋯ The FDA-approved BRAF/MEK inhibitor combination of dabrafenib and trametinib has revolutionized treatment of BRAFV600E mutation positive anaplastic thyroid cancer. Several other emerging classes of medications, such as gene fusion inhibitors and immune checkpoint inhibitors, are being actively investigated in several clinical trials. In this review, we describe the molecular landscape of thyroid cancer and novel targeted therapies and treatment combinations available for the treatment of metastatic thyroid cancer.
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(1) Background: The relatively poor expert restaging accuracy of MRI in rectal cancer after neoadjuvant chemoradiation may be due to the difficulties in visual assessment of residual tumor on post-treatment MRI. In order to capture underlying tissue alterations and morphologic changes in rectal structures occurring due to the treatment, we hypothesized that radiomics texture and shape descriptors of the rectal environment (e.g., wall, lumen) on post-chemoradiation T2-weighted (T2w) MRI may be associated with tumor regression after neoadjuvant chemoradiation therapy (nCRT). (2) Methods: A total of 94 rectal cancer patients were retrospectively identified from three collaborating institutions, for whom a 1.5 or 3T T2w MRI was available after nCRT and prior to surgical resection. ⋯ The best performing features for distinguishing low (ypT0-2) and high (ypT3-4) pathologic tumor stages after nCRT comprised directional gradient texture expression and morphologic shape differences in the entire rectal wall and lumen. Not only were these radiomic features found to be resilient to variations in magnetic field strength and expert segmentations, a quadratic discriminant model combining them yielded consistent performance across multiple institutions (hold-out AUC of 0.73). (4) Conclusions: Radiomic texture and shape descriptors of the rectal wall from post-treatment T2w MRIs may be associated with low and high pathologic tumor stage after neoadjuvant chemoradiation therapy and generalized across variations between scanners and institutions.
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Desmoid tumors represent a rare entity of monoclonal origin characterized by locally aggressive behavior and inability to metastasize. Most cases present in a sporadic pattern and are characterized by a mutation in the CTNNB1 gene; while 5-15% show a hereditary pattern associated with APC gene mutation, both resulting in abnormal β-catenin accumulation within the cell. The most common sites of presentation are the extremities and the thoracic wall, whereas FAP associated cases present intra-abdominally or in the abdominal wall. ⋯ Current approaches advocate for an initial active surveillance period due to the stabilization and even regression capacity of desmoid tumors. For progressive, symptomatic, or disabling cases, systemic treatment, radiotherapy or surgery may be used. This is a narrative review of this uncommon disease; we present current knowledge about molecular pathogenesis, diagnosis and treatment.
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Radiomics is an emerging field of image analysis with potential applications in patient risk stratification. This study developed and evaluated machine learning models using quantitative radiomic features extracted from multiparametric magnetic resonance imaging (mpMRI) to detect and classify prostate cancer (PCa). In total, 191 patients that underwent prostatic mpMRI and combined targeted and systematic fusion biopsy were retrospectively included. ⋯ In our study, radiomics accurately characterizes prostatic index lesions and shows performance comparable to radiologists for PCa characterization. Quantitative image data represent a potential biomarker, which, when combined with PI-RADS, PSAD and DRE, predicts csPCa more accurately than mADC. Prognostic machine learning models could assist in csPCa detection and patient selection for MRI-guided biopsy.