Radiology. Imaging cancer最新文献

Ongoing discoveries in cancer genomics and epigenomics have revolutionized clinical oncology and precision health care. This knowledge provides unprecedented insights into tumor biology and heterogeneity within a single tumor, among primary and metastatic lesions, and among patients with the same histologic type of cancer. Large-scale genomic sequencing studies also sparked the development of new tumor classifications, biomarkers, and targeted therapies. Because of the central role of imaging in cancer diagnosis and therapy, radiologists need to be familiar with the basic concepts of genomics, which are now becoming the new norm in oncologic clinical practice. By incorporating these concepts into clinical practice, radiologists can make their imaging interpretations more meaningful and specific, facilitate multidisciplinary clinical dialogue and interventions, and provide better patient-centric care. This review article highlights basic concepts of genomics and epigenomics, reviews the most common genetic alterations in cancer, and discusses the implications of these concepts on imaging by organ system in a case-based manner. This information will help stimulate new innovations in imaging research, accelerate the development and validation of new imaging biomarkers, and motivate efforts to bring new molecular and functional imaging methods to clinical radiology. Keywords: Oncology, Cancer Genomics, Epignomics, Radiogenomics, Imaging Markers Supplemental material is available for this article. © RSNA, 2023.

Purpose To evaluate the feasibility of liver MR fingerprinting (MRF) for quantitative characterization and diagnosis of focal liver lesions. Materials and Methods This single-site, prospective study included 89 participants (mean age, 62 years ± 15 [SD]; 45 women, 44 men) with various focal liver lesions who underwent MRI between October 2021 and August 2022. The participants underwent routine clinical MRI, non-contrast-enhanced liver MRF, and reference quantitative MRI with a 1.5-T MRI scanner. The bias and repeatability of the MRF measurements were assessed using linear regression, Bland-Altman plots, and coefficients of variation. The diagnostic capability of MRF-derived T1, T2, T2*, proton density fat fraction (PDFF), and a combination of these metrics to distinguish benign from malignant lesions was analyzed according to the area under the receiver operating characteristic curve (AUC). Results Liver MRF measurements showed moderate to high agreement with reference measurements (intraclass correlation = 0.94, 0.77, 0.45, and 0.61 for T1, T2, T2*, and PDFF, respectively), with underestimation of T2 values (mean bias in lesion = -0.5%, -29%, 5.8%, and -8.2% for T1, T2, T2*, and PDFF, respectively). The median coefficients of variation for repeatability of T1, T2, and T2* values were 2.5% (IQR, 3.6%), 3.1% (IQR, 5.6%), and 6.6% (IQR, 13.9%), respectively. After considering multicollinearity, a combination of MRF measurements showed a high diagnostic performance in differentiating benign from malignant lesions (AUC = 0.92 [95% CI: 0.86, 0.98]). Conclusion Liver MRF enabled the quantitative characterization of various focal liver lesions in a single breath-hold acquisition. Keywords: MR Imaging, Abdomen/GI, Liver, Imaging Sequences, Technical Aspects, Tissue Characterization, Technology Assessment, Diagnosis, Liver Lesions, MR Fingerprinting, Quantitative Characterization Supplemental material is available for this article. © RSNA, 2023.