Dr. Mark Tulchinsky

Nuclear Medicine
Second Opinion: Did thyroid imaging study miss the mark?
In an article published July 21 in BMJ, researchers from the University of Michigan Comprehensive Cancer Center questioned whether the use of imaging after treatment for thyroid cancer improved patient outcomes. Dr. Mark Tulchinsky of Pennsylvania State University offers a response in this Second Opinion column.
October 26, 2016
2016 10 11 13 31 21 852 Am Second Opinion 400
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Practice Management
Florida approves NBPAS as recognized board certification option
NBPAS-certified physicians can now represent themselves as board certified in Florida physician advertising.
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Thermal ablation achieves long-term survival in kidney cancer
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Low-quality axial T2-weighted MRI scans with gradient-weighted class activation mapping. The low-quality MRI scans (top row) show blurred structures and artifacts making zonal and capsule boundaries indistinguishable. On the same scans with gradient-weighted class activation map overlays (bottom row), red indicates regions that were most heavily weighted by the deep learning model toward the low-quality prediction.
MRI
AI framework could improve MRI quality control in prostate cancer
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Florida approves NBPAS as recognized board certification option
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NBPAS-certified physicians can now represent themselves as board certified in Florida physician advertising.
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The 10-year overall survival (OS) and cancer-specific survival (CSS) rates were 68.5% and 75.5%.
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Low-quality axial T2-weighted MRI scans with gradient-weighted class activation mapping. The low-quality MRI scans (top row) show blurred structures and artifacts making zonal and capsule boundaries indistinguishable. On the same scans with gradient-weighted class activation map overlays (bottom row), red indicates regions that were most heavily weighted by the deep learning model toward the low-quality prediction.
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Molecular imaging can provide whole-body visualization and quantitative assessment of PD-L1 expression.
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(A) Ga-68 NK224 PET/CT maximum intensity projection image (left), axial PET/CT images (center), and axial CT images (right) in a 43-year-old female participant with lung adenocarcinoma show lesions in the right cerebellum (blue arrow), right frontal lobe (red arrow), and sternum (green arrow) with low, intermediate, and high tracer uptake, respectively. Photomicrographs (scale bar, 100 μm) with hematoxylin-eosin (H&E) staining (center bottom) and programmed death ligand 1 (PD-L1) immunohistochemical (IHC) staining (right bottom) show high PD-L1 expression in the sternal lesion (tumor proportion score ≥ 50%).
AI fracture detection device validated across three European hospitals
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No differences in AI performance were observed across centers, and AI assistance was associated with higher reader sensitivity.
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Artificial intelligence (AI) assistance facilitates correct fracture identification in cases initially missed by human readers. A representative case is shown using anteroposterior radiographs in a 29-year-old male patient with wrist trauma (suspected nondisplaced transverse scaphoid fracture). The reader’s initial unaided assessment (top) resulted in a missed fracture, whereas with AI assistance (bottom), the fracture was correctly identified. The green box represents the fracture location as predicted by the AI tool, the blue box represents the reference standard annotation, and the red dots represent individual reader annotations.
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As survival after early-stage breast cancer improves, cardiovascular disease has emerged as an increasingly prominent competing risk in older women.
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Median report creation and turnaround times dropped to under one minute.
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