Impact of Alternate b-Value Combinations and Metrics on the Predictive Performance and Repeatability of Diffusion-Weighted MRI in Breast Cancer Treatment: Results from the ECOG-ACRIN A6698 Trial

Savannah C. Partridge; Jon Steingrimsson; David C. Newitt; Jessica E. Gibbs; Helga S. Marques; Patrick J. Bolan; Michael A. Boss; Thomas L. Chenevert; Mark A. Rosen; Nola M. Hylton

doi:10.3390/tomography8020058

Impact of Alternate b-Value Combinations and Metrics on the Predictive Performance and Repeatability of Diffusion-Weighted MRI in Breast Cancer Treatment: Results from the ECOG-ACRIN A6698 Trial

Savannah C. Partridge, Jon Steingrimsson, David C. Newitt, Jessica E. Gibbs, Helga S. Marques, Patrick J. Bolan, Michael A. Boss, Thomas L. Chenevert, Mark A. Rosen, Nola M. Hylton

Research output: Contribution to journal › Article › peer-review

2 Scopus citations

Abstract

In diffusion-weighted MRI (DW-MRI), choice of b-value influences apparent diffusion coefficient (ADC) values by probing different aspects of the tissue microenvironment. As a secondary analysis of the multicenter ECOG-ACRIN A6698 trial, the purpose of this study was to investigate the impact of alternate b-value combinations on the performance and repeatability of tumor ADC as a predictive marker of breast cancer treatment response. The final analysis included 210 women who underwent standardized 4-b-value DW-MRI (b = 0/100/600/800 s/mm²) at multiple timepoints during neoadjuvant chemotherapy treatment and a subset (n = 71) who underwent test–retest scans. Centralized tumor ADC and perfusion fraction (f_p) measures were performed using variable b-value combinations. Prediction of pathologic complete response (pCR) based on the midtreatment/12-week percent change in each metric was estimated by area under the receiver operating characteristic curve (AUC). Repeatability was estimated by within-subject coefficient of variation (wCV). Results show that two-b-value ADC calculations provided non-inferior predictive value to four-b-value ADC calculations overall (AUCs = 0.60–0.61 versus AUC = 0.60) and for HR+/HER2− cancers where ADC was most predictive (AUCs = 0.75–0.78 versus AUC = 0.76), p < 0.05. Using two b-values (0/600 or 0/800 s/mm²) did not reduce ADC repeatability over the four-b-value calculation (wCVs = 4.9–5.2% versus 5.4%). The alternate metrics ADC_fast (b ≤ 100 s/mm²), ADC_slow (b ≥ 100 s/mm²), and f_p did not improve predictive performance (AUCs = 0.54–0.60, p = 0.08–0.81), and ADC_fast and f_p demonstrated the lowest repeatability (wCVs = 6.71% and 12.4%, respectively). In conclusion, breast tumor ADC calculated using a simple two-b-value approach can provide comparable predictive value and repeatability to full four-b-value measurements as a marker of treatment response.

Original language	English (US)
Pages (from-to)	701-717
Number of pages	17
Journal	Tomography
Volume	8
Issue number	2
DOIs	https://doi.org/10.3390/tomography8020058
State	Published - Mar 2022

Bibliographical note

Funding Information:
Funding: This research was supported by the National Cancer Institute (NCI) through the grants U01CA079778, U01CA080098, U10CA180820, and U10CA180794 (ECOG-ACRIN Cancer Research Group), U01CA225427 (N.M.H.), R01CA132870 (N.M.H. and D.C.N.), R01CA190299 (T.L.C.), P41EB027061 (P.J.B.), R01CA207290 (S.C.P.), and R01CA248192 (S.C.P.). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Funding Information:
This research was supported by the National Cancer Institute (NCI) through the grants U01CA079778, U01CA080098, U10CA180820, and U10CA180794 (ECOG-ACRIN Cancer Research Group), U01CA225427 (N.M.H.), R01CA132870 (N.M.H. and D.C.N.), R01CA190299 (T.L.C.), P41EB027061 (P.J.B.), R01CA207290 (S.C.P.), and R01CA248192 (S.C.P.). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.This study was conducted by the ECOG-ACRIN Cancer Research Group (Peter J. O’Dwyer and Mitchell D. Schnall). The authors would like to thank the women who participated in this trial and the ECOG-ACRIN 6698 Trial Team and I-SPY 2 Trial Investigators.

Funding Information:
Conflicts of Interest: S.C.P. reports research support from General Electric Healthcare to institution and research support from Philips Healthcare to institution, outside the submitted work. D.C.N. reports research support from Kheiron Medical Technology to institution, outside the submitted work. N.M.H. reports research support from Kheiron Medical Technology to institution and research support from GE Healthcare to institution, outside the submitted work. T.L.C. is a coinventor on intellectual property assigned to and managed by the University of Michigan licensed by Imbio for histogram and fDM analysis. All other authors declare no conflict of interest.

Publisher Copyright:
© 2022 by the authors. Licensee MDPI, Basel, Switzerland.

Keywords

Apparent diffusion coefficient (ADC)
Breast cancer
Diffusion-weighted MRI (DW-MRI)
Quantitative imaging biomarker alliance (QIBA)
Repeatability
Reproducibility
Treatment response
Breast Neoplasms/diagnostic imaging
Humans
Tumor Microenvironment
Benchmarking
Female
ROC Curve
Diffusion Magnetic Resonance Imaging/methods
Neoadjuvant Therapy/methods

Center for Magnetic Resonance Research (CMRR) tags

BI
CTR
P41

PubMed: MeSH publication types

Multicenter Study
Journal Article
Research Support, N.I.H., Extramural

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.3390/tomography8020058

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Partridge, S. C., Steingrimsson, J., Newitt, D. C., Gibbs, J. E., Marques, H. S., Bolan, P. J., Boss, M. A., Chenevert, T. L., Rosen, M. A., & Hylton, N. M. (2022). Impact of Alternate b-Value Combinations and Metrics on the Predictive Performance and Repeatability of Diffusion-Weighted MRI in Breast Cancer Treatment: Results from the ECOG-ACRIN A6698 Trial. Tomography, 8(2), 701-717. https://doi.org/10.3390/tomography8020058

Impact of Alternate b-Value Combinations and Metrics on the Predictive Performance and Repeatability of Diffusion-Weighted MRI in Breast Cancer Treatment: Results from the ECOG-ACRIN A6698 Trial. / Partridge, Savannah C.; Steingrimsson, Jon; Newitt, David C. et al.
In: Tomography, Vol. 8, No. 2, 03.2022, p. 701-717.

Research output: Contribution to journal › Article › peer-review

Partridge, SC, Steingrimsson, J, Newitt, DC, Gibbs, JE, Marques, HS, Bolan, PJ, Boss, MA, Chenevert, TL, Rosen, MA & Hylton, NM 2022, 'Impact of Alternate b-Value Combinations and Metrics on the Predictive Performance and Repeatability of Diffusion-Weighted MRI in Breast Cancer Treatment: Results from the ECOG-ACRIN A6698 Trial', Tomography, vol. 8, no. 2, pp. 701-717. https://doi.org/10.3390/tomography8020058

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title = "Impact of Alternate b-Value Combinations and Metrics on the Predictive Performance and Repeatability of Diffusion-Weighted MRI in Breast Cancer Treatment: Results from the ECOG-ACRIN A6698 Trial",

abstract = "In diffusion-weighted MRI (DW-MRI), choice of b-value influences apparent diffusion coefficient (ADC) values by probing different aspects of the tissue microenvironment. As a secondary analysis of the multicenter ECOG-ACRIN A6698 trial, the purpose of this study was to investigate the impact of alternate b-value combinations on the performance and repeatability of tumor ADC as a predictive marker of breast cancer treatment response. The final analysis included 210 women who underwent standardized 4-b-value DW-MRI (b = 0/100/600/800 s/mm2) at multiple timepoints during neoadjuvant chemotherapy treatment and a subset (n = 71) who underwent test–retest scans. Centralized tumor ADC and perfusion fraction (fp) measures were performed using variable b-value combinations. Prediction of pathologic complete response (pCR) based on the midtreatment/12-week percent change in each metric was estimated by area under the receiver operating characteristic curve (AUC). Repeatability was estimated by within-subject coefficient of variation (wCV). Results show that two-b-value ADC calculations provided non-inferior predictive value to four-b-value ADC calculations overall (AUCs = 0.60–0.61 versus AUC = 0.60) and for HR+/HER2− cancers where ADC was most predictive (AUCs = 0.75–0.78 versus AUC = 0.76), p < 0.05. Using two b-values (0/600 or 0/800 s/mm2) did not reduce ADC repeatability over the four-b-value calculation (wCVs = 4.9–5.2% versus 5.4%). The alternate metrics ADCfast (b ≤ 100 s/mm2), ADCslow (b ≥ 100 s/mm2), and fp did not improve predictive performance (AUCs = 0.54–0.60, p = 0.08–0.81), and ADCfast and fp demonstrated the lowest repeatability (wCVs = 6.71% and 12.4%, respectively). In conclusion, breast tumor ADC calculated using a simple two-b-value approach can provide comparable predictive value and repeatability to full four-b-value measurements as a marker of treatment response.",

keywords = "Apparent diffusion coefficient (ADC), Breast cancer, Diffusion-weighted MRI (DW-MRI), Quantitative imaging biomarker alliance (QIBA), Repeatability, Reproducibility, Treatment response, Breast Neoplasms/diagnostic imaging, Humans, Tumor Microenvironment, Benchmarking, Female, ROC Curve, Diffusion Magnetic Resonance Imaging/methods, Neoadjuvant Therapy/methods",

author = "Partridge, {Savannah C.} and Jon Steingrimsson and Newitt, {David C.} and Gibbs, {Jessica E.} and Marques, {Helga S.} and Bolan, {Patrick J.} and Boss, {Michael A.} and Chenevert, {Thomas L.} and Rosen, {Mark A.} and Hylton, {Nola M.}",

note = "Funding Information: Funding: This research was supported by the National Cancer Institute (NCI) through the grants U01CA079778, U01CA080098, U10CA180820, and U10CA180794 (ECOG-ACRIN Cancer Research Group), U01CA225427 (N.M.H.), R01CA132870 (N.M.H. and D.C.N.), R01CA190299 (T.L.C.), P41EB027061 (P.J.B.), R01CA207290 (S.C.P.), and R01CA248192 (S.C.P.). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Funding Information: This research was supported by the National Cancer Institute (NCI) through the grants U01CA079778, U01CA080098, U10CA180820, and U10CA180794 (ECOG-ACRIN Cancer Research Group), U01CA225427 (N.M.H.), R01CA132870 (N.M.H. and D.C.N.), R01CA190299 (T.L.C.), P41EB027061 (P.J.B.), R01CA207290 (S.C.P.), and R01CA248192 (S.C.P.). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.This study was conducted by the ECOG-ACRIN Cancer Research Group (Peter J. O{\textquoteright}Dwyer and Mitchell D. Schnall). The authors would like to thank the women who participated in this trial and the ECOG-ACRIN 6698 Trial Team and I-SPY 2 Trial Investigators. Funding Information: Conflicts of Interest: S.C.P. reports research support from General Electric Healthcare to institution and research support from Philips Healthcare to institution, outside the submitted work. D.C.N. reports research support from Kheiron Medical Technology to institution, outside the submitted work. N.M.H. reports research support from Kheiron Medical Technology to institution and research support from GE Healthcare to institution, outside the submitted work. T.L.C. is a coinventor on intellectual property assigned to and managed by the University of Michigan licensed by Imbio for histogram and fDM analysis. All other authors declare no conflict of interest. Publisher Copyright: {\textcopyright} 2022 by the authors. Licensee MDPI, Basel, Switzerland.",

year = "2022",

month = mar,

doi = "10.3390/tomography8020058",

language = "English (US)",

volume = "8",

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T1 - Impact of Alternate b-Value Combinations and Metrics on the Predictive Performance and Repeatability of Diffusion-Weighted MRI in Breast Cancer Treatment

T2 - Results from the ECOG-ACRIN A6698 Trial

AU - Partridge, Savannah C.

AU - Steingrimsson, Jon

AU - Newitt, David C.

AU - Gibbs, Jessica E.

AU - Marques, Helga S.

AU - Bolan, Patrick J.

AU - Boss, Michael A.

AU - Chenevert, Thomas L.

AU - Rosen, Mark A.

AU - Hylton, Nola M.

N1 - Funding Information: Funding: This research was supported by the National Cancer Institute (NCI) through the grants U01CA079778, U01CA080098, U10CA180820, and U10CA180794 (ECOG-ACRIN Cancer Research Group), U01CA225427 (N.M.H.), R01CA132870 (N.M.H. and D.C.N.), R01CA190299 (T.L.C.), P41EB027061 (P.J.B.), R01CA207290 (S.C.P.), and R01CA248192 (S.C.P.). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Funding Information: This research was supported by the National Cancer Institute (NCI) through the grants U01CA079778, U01CA080098, U10CA180820, and U10CA180794 (ECOG-ACRIN Cancer Research Group), U01CA225427 (N.M.H.), R01CA132870 (N.M.H. and D.C.N.), R01CA190299 (T.L.C.), P41EB027061 (P.J.B.), R01CA207290 (S.C.P.), and R01CA248192 (S.C.P.). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.This study was conducted by the ECOG-ACRIN Cancer Research Group (Peter J. O’Dwyer and Mitchell D. Schnall). The authors would like to thank the women who participated in this trial and the ECOG-ACRIN 6698 Trial Team and I-SPY 2 Trial Investigators. Funding Information: Conflicts of Interest: S.C.P. reports research support from General Electric Healthcare to institution and research support from Philips Healthcare to institution, outside the submitted work. D.C.N. reports research support from Kheiron Medical Technology to institution, outside the submitted work. N.M.H. reports research support from Kheiron Medical Technology to institution and research support from GE Healthcare to institution, outside the submitted work. T.L.C. is a coinventor on intellectual property assigned to and managed by the University of Michigan licensed by Imbio for histogram and fDM analysis. All other authors declare no conflict of interest. Publisher Copyright: © 2022 by the authors. Licensee MDPI, Basel, Switzerland.

PY - 2022/3

Y1 - 2022/3

N2 - In diffusion-weighted MRI (DW-MRI), choice of b-value influences apparent diffusion coefficient (ADC) values by probing different aspects of the tissue microenvironment. As a secondary analysis of the multicenter ECOG-ACRIN A6698 trial, the purpose of this study was to investigate the impact of alternate b-value combinations on the performance and repeatability of tumor ADC as a predictive marker of breast cancer treatment response. The final analysis included 210 women who underwent standardized 4-b-value DW-MRI (b = 0/100/600/800 s/mm2) at multiple timepoints during neoadjuvant chemotherapy treatment and a subset (n = 71) who underwent test–retest scans. Centralized tumor ADC and perfusion fraction (fp) measures were performed using variable b-value combinations. Prediction of pathologic complete response (pCR) based on the midtreatment/12-week percent change in each metric was estimated by area under the receiver operating characteristic curve (AUC). Repeatability was estimated by within-subject coefficient of variation (wCV). Results show that two-b-value ADC calculations provided non-inferior predictive value to four-b-value ADC calculations overall (AUCs = 0.60–0.61 versus AUC = 0.60) and for HR+/HER2− cancers where ADC was most predictive (AUCs = 0.75–0.78 versus AUC = 0.76), p < 0.05. Using two b-values (0/600 or 0/800 s/mm2) did not reduce ADC repeatability over the four-b-value calculation (wCVs = 4.9–5.2% versus 5.4%). The alternate metrics ADCfast (b ≤ 100 s/mm2), ADCslow (b ≥ 100 s/mm2), and fp did not improve predictive performance (AUCs = 0.54–0.60, p = 0.08–0.81), and ADCfast and fp demonstrated the lowest repeatability (wCVs = 6.71% and 12.4%, respectively). In conclusion, breast tumor ADC calculated using a simple two-b-value approach can provide comparable predictive value and repeatability to full four-b-value measurements as a marker of treatment response.

AB - In diffusion-weighted MRI (DW-MRI), choice of b-value influences apparent diffusion coefficient (ADC) values by probing different aspects of the tissue microenvironment. As a secondary analysis of the multicenter ECOG-ACRIN A6698 trial, the purpose of this study was to investigate the impact of alternate b-value combinations on the performance and repeatability of tumor ADC as a predictive marker of breast cancer treatment response. The final analysis included 210 women who underwent standardized 4-b-value DW-MRI (b = 0/100/600/800 s/mm2) at multiple timepoints during neoadjuvant chemotherapy treatment and a subset (n = 71) who underwent test–retest scans. Centralized tumor ADC and perfusion fraction (fp) measures were performed using variable b-value combinations. Prediction of pathologic complete response (pCR) based on the midtreatment/12-week percent change in each metric was estimated by area under the receiver operating characteristic curve (AUC). Repeatability was estimated by within-subject coefficient of variation (wCV). Results show that two-b-value ADC calculations provided non-inferior predictive value to four-b-value ADC calculations overall (AUCs = 0.60–0.61 versus AUC = 0.60) and for HR+/HER2− cancers where ADC was most predictive (AUCs = 0.75–0.78 versus AUC = 0.76), p < 0.05. Using two b-values (0/600 or 0/800 s/mm2) did not reduce ADC repeatability over the four-b-value calculation (wCVs = 4.9–5.2% versus 5.4%). The alternate metrics ADCfast (b ≤ 100 s/mm2), ADCslow (b ≥ 100 s/mm2), and fp did not improve predictive performance (AUCs = 0.54–0.60, p = 0.08–0.81), and ADCfast and fp demonstrated the lowest repeatability (wCVs = 6.71% and 12.4%, respectively). In conclusion, breast tumor ADC calculated using a simple two-b-value approach can provide comparable predictive value and repeatability to full four-b-value measurements as a marker of treatment response.

KW - Apparent diffusion coefficient (ADC)

KW - Breast cancer

KW - Diffusion-weighted MRI (DW-MRI)

KW - Quantitative imaging biomarker alliance (QIBA)

KW - Repeatability

KW - Reproducibility

KW - Treatment response

KW - Breast Neoplasms/diagnostic imaging

KW - Humans

KW - Tumor Microenvironment

KW - Benchmarking

KW - Female

KW - ROC Curve

KW - Diffusion Magnetic Resonance Imaging/methods

KW - Neoadjuvant Therapy/methods

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U2 - 10.3390/tomography8020058

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AN - SCOPUS:85126710970

SN - 2379-1381

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JO - Tomography

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ER -

Impact of Alternate b-Value Combinations and Metrics on the Predictive Performance and Repeatability of Diffusion-Weighted MRI in Breast Cancer Treatment: Results from the ECOG-ACRIN A6698 Trial

Abstract

Bibliographical note

Keywords

Center for Magnetic Resonance Research (CMRR) tags

PubMed: MeSH publication types

UN SDGs

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