Evidence map›Paper›PMID 42576620›Full record

ArticleJournal of magnetic resonance imaging : JMRI2026

Application of MR Cytometry in Predicting Pathologic Complete Response to Neoadjuvant Chemotherapy in Breast Cancer: A Comparative Study.

Jie Ding, Diwei Shi, Shiyun Sun, Jinlong Zheng, Wentao Yang, Caixia Fu, Dazhi Chen, Junzhong Xu, Hua Guo, Chao You and 1 more

Abstract readComparative Study
In one paragraph

Article in Journal of magnetic resonance imaging : JMRI, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Jie DingMedical Imaging Center, People's Hospital of Ningxia Hui Autonomous Region, Yinchuan, China.
Diwei ShiResearch Institute of Tsinghua University in Shenzhen, Shenzhen, China.ORCID https://orcid.org/0000-0001-8261-4943
Shiyun SunDepartment of Radiology, Fudan University Cancer Center, Shanghai, China.ORCID https://orcid.org/0000-0003-1649-6744
Jinlong ZhengDepartment of Radiology, Fudan University Cancer Center, Shanghai, China.
Wentao YangDepartment of Pathology, Fudan University Shanghai Cancer Center, Shanghai, China.
Caixia FuMR Application Development, Siemens Shenzhen Magnetic Resonance Ltd, Shenzhen, China.
Dazhi ChenMedical Imaging Center, People's Hospital of Ningxia Hui Autonomous Region, Yinchuan, China.
Junzhong XuVanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee, USA.ORCID https://orcid.org/0000-0001-7895-4232
Hua GuoCenter for Biomedical Imaging Research, School of Biomedical Engineering, Tsinghua University, Beijing, China.
Chao YouDepartment of Radiology, Fudan University Cancer Center, Shanghai, China.ORCID https://orcid.org/0000-0001-9420-1919
Yajia GuDepartment of Radiology, Fudan University Cancer Center, Shanghai, China.

Funding

National Science Foundation of China NSFC82430061: NSFC62401329: NSFC82271957Science and Natural Science Foundation of NIngxia 2026AAC030583Science and Technology Innovation Action Plan of Shanghai Medical Innovation Research Project 23Y11903300Shanghai Explorer Program 24TS1411300Special Research Fund for Clinical Studies of Innovative Drugs after Market Launch WKZX2024Cx103301
6 · The paper itself

Abstract

backgroundMR cytometry imaging is developed to characterize in vivo microstructures. Its clinical value in predicting pathological complete response (pCR) after neoadjuvant chemotherapy (NAC) for breast cancer remains unknown. PURPOSE: To implement MR cytometry to predict pCR for breast cancer and compare the performance of different quantitative models (IMPULSED, JOINT, and EXCHANGE). STUDY TYPE: Prospective. SUBJECT: 209 female patients from center A (50.32 ± 11.06 years) and B (48.05 ± 11.30 years). FIELD STRENGTH/SEQUENCE: 3 T; pulsed gradient spin-echo diffusion-weighted imaging (DWI) and oscillating gradient spin-echo DWI of 17/33 Hz (center A) or 25/50 Hz (center B). ASSESSMENT: Tumor regions were manually delineated. Time-dependent apparent diffusion coefficients (ADC) and model-derived microstructural parameters (including cell diameter, intracellular volume fraction, cellularity, extracellular diffusivity, and water exchange rate constant) were calculated before and after NAC. Four multivariate logistic regression models, that is, time-dependent ADCs, IMPULSED, JOINT, and EXCHANGE, were constructed to predict pCR; performance of combining MR cytometry with ADCs, that is, IMPULSED-ADC, JOINT-ADC, and EXCHANGE-ADC, was also evaluated. STATISTICAL TESTS: Wilcoxon test, Mann-Whitney U test, Logistic regression analysis, DeLong's test, and Pearson correlation analysis, with statistical significance set at p < 0.05.

resultsChanges in intracellular volume fraction, cellularity, and water exchange rate constant before and after NAC exhibited significant differences between pCR and non-pCR groups. The regression models of time-dependent ADCs, IMPULSED, JOINT, and EXCHANGE yielded AUCs of 0.709, 0.716, 0.747, and 0.745 in predicting pCR for center A and 0.777, 0.809, 0.846, and 0.864 for center B; the combined models of IMPULSED-ADC, JOINT-ADC, and EXCHANGE-ADC improved AUCs to 0.737, 0.761, and 0.758 for center A and 0.818, 0.860, and 0.868 for center B. DATA

conclusionJOINT and EXCHANGE, which incorporate transcytolemmal water exchange, outperformed impermeable IMPULSED in predicting NAC for breast cancer, and predictive performance can be further improved by combining MR cytometry parameters with time-dependent ADCs. EVIDENCE LEVEL: 2. TECHNICAL EFFICACY: Stage 2.

Indexed as

Breast NeoplasmsMagnetic Resonance ImagingNeoadjuvant TherapyAdultBreastDiffusion Magnetic Resonance ImagingFemaleHumansMiddle AgedPathologic Complete ResponseProspective StudiesTreatment Outcomebreast cancerdiffusion magnetic resonance imagingMR cytometrypathological complete responsetranscytolemmal water exchange

Identifiers

PMID42576620
PMCPMC13667338

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.