# Diffusion-weighted MRI Findings Predict Pathologic Response in Neoadjuvant Treatment of Breast Cancer: The ACRIN 6698 Multicenter Trial

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/diffusion-weighted-mri-findings-predict-pathologic-response-in-neoadjuvant/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Savannah C. Partridge,Zheng Zhang,David C. Newitt,Jessica Gibbs,Thomas L. Chenevert,Mark Rosen,Patrick J. Bolan,Helga S. Marques,Justin Romanoff,Lisa Cimino,Bonnie N. Joe,Heidi Umphrey,Haydee Ojeda‐Fournier,Başak E. Doğan,Karen Y. Oh,Hiroyuki Abé,Jennifer S. Drukteinis,Laura J. Esserman,Nola M. Hylton,For the ACRIN 6698 Trial Team and I-SPY 2 Trial Investigators |
| Citations | 289 |
| DOI | 10.1148/radiol.2018180273 |
| Fields | Medicine |
| Open Access | false |
| OA Status | closed |
| OpenAlex ID | https://openalex.org/W2890317046 |
| PMID | 30179110 |
| Type | article |
| Year | 2018 |

## Paper authors

- [Bonnie N. Joe](https://scholariq.org/researchers/bonnie-n-joe/)
- [Laura J. Esserman](https://scholariq.org/researchers/laura-j-esserman/)

## Paper primary topic

- [MRI in cancer diagnosis](https://scholariq.org/topics/mri-in-cancer-diagnosis/)

## Paper topics

- [MRI in cancer diagnosis](https://scholariq.org/topics/mri-in-cancer-diagnosis/)
- [Advanced Neuroimaging Techniques and Applications](https://scholariq.org/topics/advanced-neuroimaging-techniques-and-applications/)
- [Radiomics and Machine Learning in Medical Imaging](https://scholariq.org/topics/radiomics-and-machine-learning-in-medical-imaging/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.