Quantitative metrics of mean apparent propagator magnetic resonance imaging in the diagnosis of axillary lymph node metastasis in breast cancer
Year: 2025
Type: article
Study design: Observational Study
Abstract: Background: The diagnosis of axillary lymph nodes (ALNs) status using only morphological criteria or conventional apparent diffusion coefficient (ADC) value is not sufficiently accurate. Mean apparent propagator (MAP) magnetic resonance imaging (MRI) offers the potential for discriminating metastatic and nonmetastatic ALNs. Therefore, our aim was to evaluate the diagnostic performance of MAP-MRI quantitative metrics in discriminating between metastatic and nonmetastatic ALNs in breast cancer patients. Methods: This prospective study enrolled 145 participants (mean age, 49±10 years) with breast cancer from December 2021 to February 2023 who underwent diffusion spectrum imaging and conventional MRI. All participants received ultrasound (US)-guided ALN biopsy or sentinel lymph node biopsy (SLNB) and were divided into metastatic (n=53) and nonmetastatic (n=92) ALN groups based on pathology. The MAP-MRI metrics derived from diffusion spectrum imaging and the ADC value derived from conventional diffusion-weighted imaging (DWI) were measured. The MRI morphologic features of all target ALNs were assessed. The area under the receiver operating characteristic curve (AUC), sensitivity, specificity, and accuracy were calculated to evaluate diagnostic performance. Results: Six diffusion MRI metrics, namely, the MAP_non-Gaussianity (NG), MAP_axial non-Gaussianity (NGAx), MAP_radial non-Gaussianity (NGRad), MAP_return-to-origin probability (RTOP), MAP_return-to-axis probability (RTAP), and MAP_return-to-plane probability (RTPP), were significantly lower in the metastatic ALN group (P=0.03 to P<0.001), whereas the MAP_ mean squared diffusion (MSD) and MAP_q-space inverse variance (QIV) were significantly higher in the metastatic ALN group (P=0.01 and P<0.001, respectively). The eight MAP-MRI metrics had AUCs ranging from 0.61 to 0.89, sensitivity from 57% to 100%, specificity from 46% to 83%, and accuracy from 57% to 79%. Among them, MAP_NG yielded the highest diagnostic performance with an AUC of 0.89 and was significantly higher than that of DWI_ADC (AUC, 0.89 vs. 0.79, P=0.02) and MRI morphologic criteria (AUC, 0.89 vs. 0.70, P<0.001). Conclusions: The MAP-MRI metric has superior performance to the ADC value and MRI morphologic assessment in identifying metastatic ALN in breast cancer patients for optimizing the diagnostic work-up.
Language: English
Topic: MRI in cancer diagnosis
Subfield: Radiology, Nuclear Medicine and Imaging
Field: Medicine
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W4415655979
FWCI:
Cites:
Cited by:
Related to: