Quantitative Predictors of Response to Neoadjuvant Chemotherapy on Dynamic Contrast-enhanced 3T Breast MRI
© Society of Breast Imaging 2022. All rights reserved. For permissions, please e-mail: journals.permissionsoup.com..
OBJECTIVE: To assess whether changes in quantitative parameters on breast MRI better predict pathologic complete response (pCR) to neoadjuvant chemotherapy (NAC) in breast cancer than change in volume.
METHODS: This IRB-approved retrospective study included women with newly diagnosed breast cancer who underwent 3T MRI before and during NAC from January 2013 to December 2019 and underwent surgery at our institution. Clinical data such as age, histologic diagnosis and grade, biomarker status, clinical stage, maximum index cancer dimension and volume, and surgical pathology (presence or absence of in-breast pCR) were collected. Quantitative parameters were calculated using software. Correlations between clinical features and MRI quantitative measures in pCR and non-pCR groups were assessed using univariate and multivariate logistic regression.
RESULTS: A total of 182 women with a mean age of 52 years (range, 26-79 years) and 187 cancers were included. Approximately 45% (85/182) of women had pCR at surgery. Stepwise multivariate regression analysis showed statistical significance for changes in quantitative parameters (increase in time to peak and decreases in peak enhancement, wash out, and Kep [efflux rate constant]) for predicting pCR. These variables in combination predicted pCR with 81.2% accuracy and an area under the curve (AUC) of 0.878. The AUCs of change in index cancer volume and maximum dimension were 0.767 and 0.613, respectively.
CONCLUSION: Absolute changes in quantitative MRI parameters between pre-NAC MRI and intra-NAC MRI could help predict pCR with excellent accuracy, which was greater than changes in index cancer volume and maximum dimension.
Medienart: |
E-Artikel |
---|
Erscheinungsjahr: |
2022 |
---|---|
Erschienen: |
2022 |
Enthalten in: |
Zur Gesamtaufnahme - volume:4 |
---|---|
Enthalten in: |
Journal of breast imaging - 4(2022), 2 vom: 15. Apr., Seite 168-176 |
Sprache: |
Englisch |
---|
Beteiligte Personen: |
Murakami, Wakana [VerfasserIn] |
---|
Links: |
---|
Themen: |
Breast cancer |
---|
Anmerkungen: |
Date Revised 29.02.2024 published: Print Citation Status PubMed-not-MEDLINE |
---|
doi: |
10.1093/jbi/wbab095 |
---|
funding: |
|
---|---|
Förderinstitution / Projekttitel: |
|
PPN (Katalog-ID): |
NLM369123271 |
---|
LEADER | 01000naa a22002652 4500 | ||
---|---|---|---|
001 | NLM369123271 | ||
003 | DE-627 | ||
005 | 20240301233110.0 | ||
007 | cr uuu---uuuuu | ||
008 | 240301s2022 xx |||||o 00| ||eng c | ||
024 | 7 | |a 10.1093/jbi/wbab095 |2 doi | |
028 | 5 | 2 | |a pubmed24n1313.xml |
035 | |a (DE-627)NLM369123271 | ||
035 | |a (NLM)38422427 | ||
040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
041 | |a eng | ||
100 | 1 | |a Murakami, Wakana |e verfasserin |4 aut | |
245 | 1 | 0 | |a Quantitative Predictors of Response to Neoadjuvant Chemotherapy on Dynamic Contrast-enhanced 3T Breast MRI |
264 | 1 | |c 2022 | |
336 | |a Text |b txt |2 rdacontent | ||
337 | |a ƒaComputermedien |b c |2 rdamedia | ||
338 | |a ƒa Online-Ressource |b cr |2 rdacarrier | ||
500 | |a Date Revised 29.02.2024 | ||
500 | |a published: Print | ||
500 | |a Citation Status PubMed-not-MEDLINE | ||
520 | |a © Society of Breast Imaging 2022. All rights reserved. For permissions, please e-mail: journals.permissionsoup.com. | ||
520 | |a OBJECTIVE: To assess whether changes in quantitative parameters on breast MRI better predict pathologic complete response (pCR) to neoadjuvant chemotherapy (NAC) in breast cancer than change in volume | ||
520 | |a METHODS: This IRB-approved retrospective study included women with newly diagnosed breast cancer who underwent 3T MRI before and during NAC from January 2013 to December 2019 and underwent surgery at our institution. Clinical data such as age, histologic diagnosis and grade, biomarker status, clinical stage, maximum index cancer dimension and volume, and surgical pathology (presence or absence of in-breast pCR) were collected. Quantitative parameters were calculated using software. Correlations between clinical features and MRI quantitative measures in pCR and non-pCR groups were assessed using univariate and multivariate logistic regression | ||
520 | |a RESULTS: A total of 182 women with a mean age of 52 years (range, 26-79 years) and 187 cancers were included. Approximately 45% (85/182) of women had pCR at surgery. Stepwise multivariate regression analysis showed statistical significance for changes in quantitative parameters (increase in time to peak and decreases in peak enhancement, wash out, and Kep [efflux rate constant]) for predicting pCR. These variables in combination predicted pCR with 81.2% accuracy and an area under the curve (AUC) of 0.878. The AUCs of change in index cancer volume and maximum dimension were 0.767 and 0.613, respectively | ||
520 | |a CONCLUSION: Absolute changes in quantitative MRI parameters between pre-NAC MRI and intra-NAC MRI could help predict pCR with excellent accuracy, which was greater than changes in index cancer volume and maximum dimension | ||
650 | 4 | |a Journal Article | |
650 | 4 | |a MRI | |
650 | 4 | |a breast cancer | |
650 | 4 | |a neoadjuvant chemotherapy | |
650 | 4 | |a pathologic complete response | |
650 | 4 | |a quantitative analysis | |
700 | 1 | |a Won Choi, Hyung |e verfasserin |4 aut | |
700 | 1 | |a Joines, Melissa M |e verfasserin |4 aut | |
700 | 1 | |a Hoyt, Anne |e verfasserin |4 aut | |
700 | 1 | |a Doepke, Laura |e verfasserin |4 aut | |
700 | 1 | |a McCann, Kelly E |e verfasserin |4 aut | |
700 | 1 | |a Salamon, Noriko |e verfasserin |4 aut | |
700 | 1 | |a Sayre, James |e verfasserin |4 aut | |
700 | 1 | |a Lee-Felker, Stephanie |e verfasserin |4 aut | |
773 | 0 | 8 | |i Enthalten in |t Journal of breast imaging |d 2019 |g 4(2022), 2 vom: 15. Apr., Seite 168-176 |w (DE-627)NLM300337108 |x 2631-6129 |7 nnns |
773 | 1 | 8 | |g volume:4 |g year:2022 |g number:2 |g day:15 |g month:04 |g pages:168-176 |
856 | 4 | 0 | |u http://dx.doi.org/10.1093/jbi/wbab095 |3 Volltext |
912 | |a GBV_USEFLAG_A | ||
912 | |a GBV_NLM | ||
951 | |a AR | ||
952 | |d 4 |j 2022 |e 2 |b 15 |c 04 |h 168-176 |