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Multi-site clinical evaluation of DW-MRI as a treatment response metric for breast cancer patients undergoing neoadjuvant chemotherapy.

Galbán CJ, Ma B, Malyarenko D, Pickles MD, Heist K, Henry NL, Schott AF, Neal CH, Hylton NM, Rehemtulla A, Johnson TD, Meyer CR, Chenevert TL, Turnbull LW, Ross BD - PLoS ONE (2015)

Bottom Line: Mean tumor apparent diffusion coefficient (ADC) values generated from patient test-retest examinations were found to be very reproducible (/ΔADC/<0.1x10-3mm2/s).Receiver operating characteristic analysis identified the PRM metric to be predictive of outcome at the 8-11 (AUC = 0.964, p = 0.01) and 35 day (AUC = 0.770, p = 0.05) time points (p<.05) while whole-tumor ADC changes where significant at the later 35 day time interval (AUC = 0.825, p = 0.02).In addition, we provide experimental evidence supporting the use of sensitive analytical tools, such as PRM, for evaluating ADC measurements.

View Article: PubMed Central - PubMed

Affiliation: Departments of Radiology, University of Michigan, Ann Arbor, Michigan, United States of America.

ABSTRACT

Purpose: To evaluate diffusion weighted MRI (DW-MR) as a response metric for assessment of neoadjuvant chemotherapy (NAC) in patients with primary breast cancer using prospective multi-center trials which provided MR scans along with clinical outcome information.

Materials and methods: A total of 39 patients with locally advanced breast cancer accrued from three different prospective clinical trials underwent DW-MR examination prior to and at 3-7 days (Hull University), 8-11 days (University of Michigan) and 35 days (NeoCOMICE) post-treatment initiation. Thirteen patients, 12 of which participated in treatment response study, from UM underwent short interval (<1hr) MRI examinations, referred to as "test-retest" for examination of repeatability. To further evaluate stability in ADC measurements, a thermally controlled diffusion phantom was used to assess repeatability of diffusion measurements. MRI sequences included contrast-enhanced T1-weighted, when appropriate, and DW images acquired at b-values of 0 and 800 s/mm2. Histogram analysis and a voxel-based analytical technique, the Parametric Response Map (PRM), were used to derive diffusion response metrics for assessment of treatment response prediction.

Results: Mean tumor apparent diffusion coefficient (ADC) values generated from patient test-retest examinations were found to be very reproducible (/ΔADC/<0.1x10-3mm2/s). This data was used to calculate the 95% CI from the linear fit of tumor voxel ADC pairs of co-registered examinations (±0.45x10-3mm2/s) for PRM analysis of treatment response. Receiver operating characteristic analysis identified the PRM metric to be predictive of outcome at the 8-11 (AUC = 0.964, p = 0.01) and 35 day (AUC = 0.770, p = 0.05) time points (p<.05) while whole-tumor ADC changes where significant at the later 35 day time interval (AUC = 0.825, p = 0.02).

Conclusion: This study demonstrates the feasibility of performing a prospective analysis of DW-MRI as a predictive biomarker of NAC in breast cancer patients. In addition, we provide experimental evidence supporting the use of sensitive analytical tools, such as PRM, for evaluating ADC measurements.

No MeSH data available.


Related in: MedlinePlus

Evaluation of PRMADC as a response metric.Parametric response maps (A) and (C) and corresponding scatter plots (B) and (D) of post- versus pre-treatment ADC values are presented for a representative non-responder (top row) and responder (bottom row). The joint density histogram from the non-responder demonstrated a negligible shift resulting in a PRMADC+, i.e., the relative tumor volume with significantly increasing ADC values, of 1.8%. In contrast, a substantial shift in the histogram was observed for the responder (PRMADC+ of 12.8%).
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pone.0122151.g005: Evaluation of PRMADC as a response metric.Parametric response maps (A) and (C) and corresponding scatter plots (B) and (D) of post- versus pre-treatment ADC values are presented for a representative non-responder (top row) and responder (bottom row). The joint density histogram from the non-responder demonstrated a negligible shift resulting in a PRMADC+, i.e., the relative tumor volume with significantly increasing ADC values, of 1.8%. In contrast, a substantial shift in the histogram was observed for the responder (PRMADC+ of 12.8%).

Mentions: Application of the PRM technique on serial ADC maps identified substantially less tumor volume with increasing ADC values mid-treatment in the SD patient as compared to the CR patient (Fig 5). For the SD patient, only 1.8% of the tumor volume was found to generate increasing ADC values that were beyond the 95% confidence interval (±0.45x10-3mm2/s). This suggests that a large segment of the tumor volume was unresponsive to the therapeutic intervention. For the CR patient, up to 12.8% of the tumor was designated by PRM as demonstrating an increase in ADC beyond the 0.45x10-3mm2/s threshold. Responsive tissue within the tumor is clearly identified with the PRMADC map as red voxels, suggestive of a reduction in tumor cellularity in response to an effective therapy. Increasing values in PRMADC+ has been shown to correlate with cell kill in preclinical models of brain tumors and metastatic cancer to the bone [27,36].


Multi-site clinical evaluation of DW-MRI as a treatment response metric for breast cancer patients undergoing neoadjuvant chemotherapy.

Galbán CJ, Ma B, Malyarenko D, Pickles MD, Heist K, Henry NL, Schott AF, Neal CH, Hylton NM, Rehemtulla A, Johnson TD, Meyer CR, Chenevert TL, Turnbull LW, Ross BD - PLoS ONE (2015)

Evaluation of PRMADC as a response metric.Parametric response maps (A) and (C) and corresponding scatter plots (B) and (D) of post- versus pre-treatment ADC values are presented for a representative non-responder (top row) and responder (bottom row). The joint density histogram from the non-responder demonstrated a negligible shift resulting in a PRMADC+, i.e., the relative tumor volume with significantly increasing ADC values, of 1.8%. In contrast, a substantial shift in the histogram was observed for the responder (PRMADC+ of 12.8%).
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4376686&req=5

pone.0122151.g005: Evaluation of PRMADC as a response metric.Parametric response maps (A) and (C) and corresponding scatter plots (B) and (D) of post- versus pre-treatment ADC values are presented for a representative non-responder (top row) and responder (bottom row). The joint density histogram from the non-responder demonstrated a negligible shift resulting in a PRMADC+, i.e., the relative tumor volume with significantly increasing ADC values, of 1.8%. In contrast, a substantial shift in the histogram was observed for the responder (PRMADC+ of 12.8%).
Mentions: Application of the PRM technique on serial ADC maps identified substantially less tumor volume with increasing ADC values mid-treatment in the SD patient as compared to the CR patient (Fig 5). For the SD patient, only 1.8% of the tumor volume was found to generate increasing ADC values that were beyond the 95% confidence interval (±0.45x10-3mm2/s). This suggests that a large segment of the tumor volume was unresponsive to the therapeutic intervention. For the CR patient, up to 12.8% of the tumor was designated by PRM as demonstrating an increase in ADC beyond the 0.45x10-3mm2/s threshold. Responsive tissue within the tumor is clearly identified with the PRMADC map as red voxels, suggestive of a reduction in tumor cellularity in response to an effective therapy. Increasing values in PRMADC+ has been shown to correlate with cell kill in preclinical models of brain tumors and metastatic cancer to the bone [27,36].

Bottom Line: Mean tumor apparent diffusion coefficient (ADC) values generated from patient test-retest examinations were found to be very reproducible (/ΔADC/<0.1x10-3mm2/s).Receiver operating characteristic analysis identified the PRM metric to be predictive of outcome at the 8-11 (AUC = 0.964, p = 0.01) and 35 day (AUC = 0.770, p = 0.05) time points (p<.05) while whole-tumor ADC changes where significant at the later 35 day time interval (AUC = 0.825, p = 0.02).In addition, we provide experimental evidence supporting the use of sensitive analytical tools, such as PRM, for evaluating ADC measurements.

View Article: PubMed Central - PubMed

Affiliation: Departments of Radiology, University of Michigan, Ann Arbor, Michigan, United States of America.

ABSTRACT

Purpose: To evaluate diffusion weighted MRI (DW-MR) as a response metric for assessment of neoadjuvant chemotherapy (NAC) in patients with primary breast cancer using prospective multi-center trials which provided MR scans along with clinical outcome information.

Materials and methods: A total of 39 patients with locally advanced breast cancer accrued from three different prospective clinical trials underwent DW-MR examination prior to and at 3-7 days (Hull University), 8-11 days (University of Michigan) and 35 days (NeoCOMICE) post-treatment initiation. Thirteen patients, 12 of which participated in treatment response study, from UM underwent short interval (<1hr) MRI examinations, referred to as "test-retest" for examination of repeatability. To further evaluate stability in ADC measurements, a thermally controlled diffusion phantom was used to assess repeatability of diffusion measurements. MRI sequences included contrast-enhanced T1-weighted, when appropriate, and DW images acquired at b-values of 0 and 800 s/mm2. Histogram analysis and a voxel-based analytical technique, the Parametric Response Map (PRM), were used to derive diffusion response metrics for assessment of treatment response prediction.

Results: Mean tumor apparent diffusion coefficient (ADC) values generated from patient test-retest examinations were found to be very reproducible (/ΔADC/<0.1x10-3mm2/s). This data was used to calculate the 95% CI from the linear fit of tumor voxel ADC pairs of co-registered examinations (±0.45x10-3mm2/s) for PRM analysis of treatment response. Receiver operating characteristic analysis identified the PRM metric to be predictive of outcome at the 8-11 (AUC = 0.964, p = 0.01) and 35 day (AUC = 0.770, p = 0.05) time points (p<.05) while whole-tumor ADC changes where significant at the later 35 day time interval (AUC = 0.825, p = 0.02).

Conclusion: This study demonstrates the feasibility of performing a prospective analysis of DW-MRI as a predictive biomarker of NAC in breast cancer patients. In addition, we provide experimental evidence supporting the use of sensitive analytical tools, such as PRM, for evaluating ADC measurements.

No MeSH data available.


Related in: MedlinePlus