A new method to reduce false positive results in breast MRI by evaluation of multiple spectral regions in proton MR-spectroscopy |
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Affiliation: | 1. Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, Vienna, Austria;2. Institute of Radiology, Department of Medical and Biological Sciences, University of Udine, P.le S. Maria della Misericordia, Udine, Italy;3. Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, Rämistrasse 100, Zurich, Switzerland;4. Department of Radiology, University Hospital Erlangen, Erlangen, Germany;1. Department of Radiology, University of Pittsburgh Medical Center, PA, United States;2. Department of Neurology, University of Pittsburgh Medical Center, PA, United States;1. Division of Medical Oncology, Mayo Clinic, Rochester, MN;2. Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN;3. OptumLabs, Cambridge, MA;4. Dana-Farber Cancer Institute, Boston, MA;5. American Cancer Society, Atlanta, GA;6. Wisconsin Surgical Outcomes Research Program, Department of Surgery, University of Wisconsin School of Medicine, Madison, WI;7. Division of Radiation Oncology, Mayo Clinic, Rochester, MN;8. Division of Hematology and Oncology, University of California Davis School of Medicine, Sacramento, CA;9. Cancer Outcomes, Public Policy and Effectiveness Research Center, Yale University, New Haven, CT;1. Department of Radiation Oncology, Dickson Building, Halifax, Canada;2. Cancer Centre of Southeastern Ontario, Kingston, Canada;3. Tom Baker Cancer Centre, Calgary, Canada;4. Centre Intégré de Santé et de Services Sociaux de Laval (CISSS Laval), Canada;5. Juravinski Cancer Centre, Hamilton, Canada;1. Department of Radiology, Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea;2. Department of Radiology, Research Institute of Radiology, Chung-Ang University Hospital, Seoul, Republic of Korea;3. Korea Electrotechnology Research Institute, Ansan, Republic of Korea;1. Graduate Program in Health Sciences, Federal University of Uberlandia, Uberlandia, Minas Gerais, Brazil;2. Nutrition Course, Medical Faculty, Federal University of Uberlandia, Uberlandia, Minas Gerais, Brazil;3. Department of Clinical Oncology, Clinic’s Hospital, Federal University of Uberlandia, Uberlandia, Minas Gerais, Brazil;4. Department of Clinical Oncology, Breast and Gynecology Division, Barretos Cancer Hospital, Barretos, São Paulo, Brazil |
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Abstract: | ObjectivesTo investigate whether the evaluation of multiple spectral regions can increase the diagnostic performance of 1H-MRS of the breast and reduce false positive findings.Methods93 patients (mean age 56 years, range 23–79) undergoing breast MRI for routine clinical indications on a 1.5 T scanner were eligible for this IRB-approved prospective study. Suspicious enhancing lesions ≥8 mm underwent single-voxel point-resolved 1H-MRS (PRESS, TR = 2000 ms, TE = 272 ms). Histology showed 69 malignant and 24 benign lesions. The Signal-to-Noise ratio of choline, olefinic acids and the water-to-methylene ratio were measured. The area under the ROC-curve (AUC) was used to evaluate single measurements. Combined diagnostic accuracy was explored using a 10-fold cross-validated Chi-squared automatic interaction detection (CHAID) analysis. Inter-reader agreement was evaluated in a subset of patients.ResultsA significant AUC for differentiation between benign and malignant lesions was identified for choline (0.733, P = 0.001), olefinic acids (0.769, P = 0.0001) and water-to-methylene ratio (0.704, P = 0.003). All three variables were included in a classification algorithm using CHAID methodology. Using this classification, 70.8% (17/24) false positive diagnoses in benign lesions would have been avoided. Inter-reader agreement was almost perfect.ConclusionsThe combined evaluation of multiple spectral regions can increase the diagnostic performance of 1H-MRS and potentially reduce false positive findings. |
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Keywords: | Breast neoplasms Magnetic resonance imaging Spectroscopy Lipid metabolism Choline |
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