# Comparison of postprocessing metrics in multimetabolic APT-weighted CEST and 2-deoxy-D-glucose-CEST-MRI for differentiating breast cancer subtypes in a murine model

## TL;DR

This study compares advanced MRI metrics for identifying breast cancer types in mice, showing that newer methods outperform traditional ones.

## Contribution

The paper introduces the use of MTRREX and AREX as superior postprocessing metrics for metabolic CEST-MRI in breast cancer subtyping.

## Key findings

- MTRREX and AREX effectively differentiated Luminal A from HER2+ and triple-negative tumors in APTw-CEST.
- AREX distinguished Luminal A from HER2+ tumors in 2-deoxy-D-glucose-CEST.
- MTRasym failed to separate tumor subtypes in CEST-MRI.

## Abstract

Chemical exchange saturation transfer (CEST)-magnetic resonance imaging (MRI), particularly amide proton transfer-weighted (APTw)-CEST and 2-deoxy-D-glucose-CEST, holds promise for noninvasive molecular breast cancer (BC) characterization. However, quantification remains challenging due to field inhomogeneities, overlapping exchange pools, and the limited robustness of conventional metrics such as the magnetization transfer ratio asymmetry (MTRasym). This study evaluates four CEST postprocessing metrics—MTRasym, Lorentzian amplitudes, MTR relaxation exchange (MTRREX), and apparent exchange-dependent relaxation (AREX)—for their diagnostic performance in differentiating BC subtypes using endogenous APTw-CEST and exogenous 2-deoxy-D-glucose-CEST in a murine BC xenograft model of Luminal A, human epidermal growth factor receptor 2 (HER2)+, and triple-negative tumors.

Metabolic CEST-MRI was performed in vitro on protein and 2-deoxy-D-glucose phantoms and in vivo in a murine BC model. Imaging was conducted at 9.4 T with 120 frequency offsets from +6 to -6 ppm. MTRREX and AREX were derived via Lorentzian fitting using tailored five-pool models. Statistical comparisons across subtypes were performed per metric.

In APTw-CEST, MTRREX and AREX significantly distinguished Luminal A from HER2+ (p ≤ 0.027) and Luminal A from triple-negative (p ≤ 0.006) tumors. Lorentzian amplitudes differentiated Luminal A from triple-negative (p = 0.019), while MTRasym showed no separation. In 2-deoxy-D-glucose-CEST, only AREX distinguished Luminal A from HER2+ tumors (p = 0.017).

Advanced metrics, particularly MTRREX and AREX, improve metabolic CEST-MRI for BC subtyping in a murine preclinical model, while MTRasym is inadequate for this purpose.

Our findings underscore the importance of applying advanced postprocessing metrics to metabolic CEST-MRI for improved noninvasive BC characterization in a murine preclinical model.

Advanced multimetabolic APTw-CEST and 2-deoxy-D-glucose-CEST postprocessing metrics allowed adequate preclinical murine BC subtyping.AREX showed potential for 2-deoxy-D-glucose-CEST in tumor characterization; however, APTw-CEST remains superior.MTRasym failed to distinguish between tumor subtypes in CEST-MRI.

Advanced multimetabolic APTw-CEST and 2-deoxy-D-glucose-CEST postprocessing metrics allowed adequate preclinical murine BC subtyping.

AREX showed potential for 2-deoxy-D-glucose-CEST in tumor characterization; however, APTw-CEST remains superior.

MTRasym failed to distinguish between tumor subtypes in CEST-MRI.