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MRI Not Quite There for Lymph Node Diagnosis in Breast Cancer
Magnetic resonance imaging’s accuracy in detecting cancer in the lymph nodes of newly diagnosed breast cancer patients is nothing to sniff at – 80 percent with diffusion-weighted MRI and 85 percent with axial T1-weighted MRI, Canadian researchers have reported. But it’s not quite high enough to skip a lymph node dissection, according to a study published online Dec. 5 in the journal Radiology.
Magnetic resonance imaging’s accuracy in detecting cancer in the lymph nodes of newly diagnosed breast cancer patients is nothing to sniff at – 80 percent with diffusion-weighted MRI and 85 percent with axial T1-weighted MRI, Canadian researchers have reported. But it’s not quite high enough to skip a lymph node dissection, according to a study published online Dec. 5 in the journal Radiology.
University of Toronto researchers chose 61 women (average age 53) with invasive breast cancer to undergo preoperative breast MRI. Axial T1-weighted MRI without fat saturation and diffusion-weighted (DW) MR images were analyzed by two experienced radiologists uninformed of the pathology findings.
They found the sensitivity, specificity, and accuracy to be 88 percent, 82 percent, and 85 percent, respectively, for axial T1-weighted MR imaging and 84 percent, 77 percent, and 80 percent for diffusion-weighted (DW) imaging. Apparent diffusion coefficients (ADCs) were significantly lower in the malignant group.
The team concluded that unenhanced MRI techniques showed high accuracy in the preoperative evaluation of patients with invasive breast cancer, and that, while the results indicated reliable and reproducible assessment with DW imaging, “it is unlikely to be useful in clinical practice.”
Can AI Bolster Breast Cancer Detection in DBT Screening?
January 16th 2025In sequential breast cancer screening with digital breast tomosynthesis (DBT), true positive examinations had more than double the AI case score of true negative examinations and the highest positive AI score changes from previous exams, according to new research.
CT Study Reveals Key Indicators for Angiolymphatic Invasion in Non-Small Cell Lung Cancer
January 15th 2025In computed tomography (CT) scans for patients with solid non-small cell lung cancer (NSCLC) < 30 mm, emerging research suggests the lollipop sign is associated with a greater than fourfold likelihood of angiolymphatic invasion.
Can MRI-Based AI Enhance Risk Stratification in Prostate Cancer?
January 13th 2025Employing baseline MRI and clinical data, an emerging deep learning model was 32 percent more likely to predict the progression of low-risk prostate cancer (PCa) to clinically significant prostate cancer (csPCa), according to new research.
