Abstract
Ideally, Neoadjuvant chemotherapy (NAC) assessment should predict pathologic complete response (pCR), a surrogate clinical endpoint for 5-year survival, as early as possible during typical 3-to 6-month breast cancer treatments. We introduce and demonstrate an approach for predicting pCR within 10 days of initiating NAC. The method uses a bedside diffuse optical spectroscopic imaging (DOSI) technology and logistic regression modeling. Tumor and normal tissue physiological properties were measured longitudinally throughout the course of NAC in 33 patients enrolled in the American College of Radiology Imaging Network multicenter breast cancer DOSI trial (ACRIN-6691). An image analysis scheme, employing z-score normalization to healthy tissue, produced models with robust predictions. Notably, logistic regression based on z-score normalization using only tissue oxygen saturation (S t O 2 ) measured within 10 days of the initial therapy dose was found to be a significant predictor of pCR (AUC = 0.92; 95% CI: 0.82 to 1). This observation suggests that patients who show rapid convergence of tumor tissue S t O 2 to surrounding tissue S t O 2 are more likely to achieve pCR. This early predictor of pCR occurs prior to reductions in tumor size and could enable dynamic feedback for optimization of chemotherapy strategies in breast cancer.
| Original language | English (US) |
|---|---|
| Article number | 021202 |
| Journal | Journal of biomedical optics |
| Volume | 24 |
| Issue number | 2 |
| DOIs | |
| State | Published - Jan 1 2019 |
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Keywords
- Biomedical Optics
- Breast Cancer
- Diffuse Optical Spectroscopy
- Neoadjuvant Chemotherapy
- Therapy Monitoring
- Translational Imaging
ASJC Scopus subject areas
- Electronic, Optical and Magnetic Materials
- Biomaterials
- Atomic and Molecular Physics, and Optics
- Biomedical Engineering
Cite this
Tissue oxygen saturation predicts response to breast cancer neoadjuvant chemotherapy within 10 days of treatment. / Cochran, Jeffrey M.; Busch, David R.; Leproux, Anaïs; Zhang, Zheng; O'Sullivan, Thomas D.; Cerussi, Albert E.; Carpenter, Philip M.; Mehta, Rita S.; Roblyer, Darren; Yang, Wei; Paulsen, Keith D.; Pogue, Brian; Jiang, Shudong; Kaufman, Peter A.; Chung, So Hyun; Schnall, Mitchell; Snyder, Bradley S.; Hylton, Nola; Carp, Stefan A.; Isakoff, Steven J.; Mankoff, David; Tromberg, Bruce J.; Yodha, Arjun G.
In: Journal of biomedical optics, Vol. 24, No. 2, 021202, 01.01.2019.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Tissue oxygen saturation predicts response to breast cancer neoadjuvant chemotherapy within 10 days of treatment
AU - Cochran, Jeffrey M.
AU - Busch, David R.
AU - Leproux, Anaïs
AU - Zhang, Zheng
AU - O'Sullivan, Thomas D.
AU - Cerussi, Albert E.
AU - Carpenter, Philip M.
AU - Mehta, Rita S.
AU - Roblyer, Darren
AU - Yang, Wei
AU - Paulsen, Keith D.
AU - Pogue, Brian
AU - Jiang, Shudong
AU - Kaufman, Peter A.
AU - Chung, So Hyun
AU - Schnall, Mitchell
AU - Snyder, Bradley S.
AU - Hylton, Nola
AU - Carp, Stefan A.
AU - Isakoff, Steven J.
AU - Mankoff, David
AU - Tromberg, Bruce J.
AU - Yodha, Arjun G.
PY - 2019/1/1
Y1 - 2019/1/1
N2 - Ideally, Neoadjuvant chemotherapy (NAC) assessment should predict pathologic complete response (pCR), a surrogate clinical endpoint for 5-year survival, as early as possible during typical 3-to 6-month breast cancer treatments. We introduce and demonstrate an approach for predicting pCR within 10 days of initiating NAC. The method uses a bedside diffuse optical spectroscopic imaging (DOSI) technology and logistic regression modeling. Tumor and normal tissue physiological properties were measured longitudinally throughout the course of NAC in 33 patients enrolled in the American College of Radiology Imaging Network multicenter breast cancer DOSI trial (ACRIN-6691). An image analysis scheme, employing z-score normalization to healthy tissue, produced models with robust predictions. Notably, logistic regression based on z-score normalization using only tissue oxygen saturation (S t O 2 ) measured within 10 days of the initial therapy dose was found to be a significant predictor of pCR (AUC = 0.92; 95% CI: 0.82 to 1). This observation suggests that patients who show rapid convergence of tumor tissue S t O 2 to surrounding tissue S t O 2 are more likely to achieve pCR. This early predictor of pCR occurs prior to reductions in tumor size and could enable dynamic feedback for optimization of chemotherapy strategies in breast cancer.
AB - Ideally, Neoadjuvant chemotherapy (NAC) assessment should predict pathologic complete response (pCR), a surrogate clinical endpoint for 5-year survival, as early as possible during typical 3-to 6-month breast cancer treatments. We introduce and demonstrate an approach for predicting pCR within 10 days of initiating NAC. The method uses a bedside diffuse optical spectroscopic imaging (DOSI) technology and logistic regression modeling. Tumor and normal tissue physiological properties were measured longitudinally throughout the course of NAC in 33 patients enrolled in the American College of Radiology Imaging Network multicenter breast cancer DOSI trial (ACRIN-6691). An image analysis scheme, employing z-score normalization to healthy tissue, produced models with robust predictions. Notably, logistic regression based on z-score normalization using only tissue oxygen saturation (S t O 2 ) measured within 10 days of the initial therapy dose was found to be a significant predictor of pCR (AUC = 0.92; 95% CI: 0.82 to 1). This observation suggests that patients who show rapid convergence of tumor tissue S t O 2 to surrounding tissue S t O 2 are more likely to achieve pCR. This early predictor of pCR occurs prior to reductions in tumor size and could enable dynamic feedback for optimization of chemotherapy strategies in breast cancer.
KW - Biomedical Optics
KW - Breast Cancer
KW - Diffuse Optical Spectroscopy
KW - Neoadjuvant Chemotherapy
KW - Therapy Monitoring
KW - Translational Imaging
UR - http://www.scopus.com/inward/record.url?scp=85055074253&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85055074253&partnerID=8YFLogxK
U2 - 10.1117/1.JBO.24.2.021202
DO - 10.1117/1.JBO.24.2.021202
M3 - Article
C2 - 30338678
AN - SCOPUS:85055074253
VL - 24
JO - Journal of Biomedical Optics
JF - Journal of Biomedical Optics
SN - 1083-3668
IS - 2
M1 - 021202
ER -