Image quality and diagnostic value of diffusion-weighted breast magnetic resonance imaging: Comparison of acquired and computed images

• Published in: PloS one 2021-02, Vol.16 (2), p.e0247379-e0247379
• Main Authors: Ahn, Hye Shin, Kim, Sung Hun, Kim, Ji Youn, Park, Chang Suk, Grimm, Robert, Son, Yohan
• Format: Article
• Language: English
• Subjects: Biology and Life Sciences; Biopsy; Breast; Breast cancer; Computation; Datasets; Diagnostic systems; Diffusion; Diffusion coefficient; Image acquisition; Image quality; Lesions; Magnetic resonance; Magnetic resonance imaging; Malignancy; Mammography; Medical diagnosis; Medical imaging; Medical imaging equipment; Medical schools; Medicine; Medicine and Health Sciences; Methods; Quality management; Research and Analysis Methods
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0247379

To compare the image quality of acquired diffusion-weighted imaging (DWI) and computed DWI and evaluate the lesion detectability and likelihood of malignancy in these datasets. This prospective study was approved by our institutional review board. A total of 29 women (mean age, 43.5 years) underwent DWI between August 2018 and April 2019 for 32 breast cancers and 16 benign breast lesions. Three radiologists independently reviewed the acquired DWI with b-values of 1000 and 2000 s/mm2 (A-b1000 and A-b2000) and the computed DWI with a b-value of 2000 s/mm2 (C-b2000). Image quality was scored and compared between the three DWI datasets. Lesion detectability was recorded, and the lesion's likelihood for malignancy was scored using a five-point scale. The A-b1000 images were superior to the A-b2000 and C-b2000 images in chest distinction, fat suppression, and overall image quality. The A-b2000 and C-b2000 images showed comparable scores for all image quality parameters. C-b2000 showed the highest values for lesion detection among all readers, although there was no statistical difference in sensitivity, specificity, positive predictive value, negative predictive value, and accuracy between the DWI datasets. The malignancy scores of the DWI images were not significantly different among the three readers. A-b1000 DWI is suitable for breast lesion evaluations, considering its better image quality and comparable diagnostic values compared to that of A-b2000 and C-b2000 images. The additional use of computed high b-value DWI may have the potential to increase the detectability of breast masses.