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. 2016 Jan 23;9(1):8–17. doi: 10.1016/j.tranon.2015.11.016

Table 2.

Early Prediction of Pathologic Response (pCR vs. non-pCR)

MRI Metric
pCR
non-pCR

ULR C value
Mean ± SD Mean ± SD P value
V21% Ktrans(TM) − 64% ± 9% − 14% ± 41% .098 0.967
V21% kep(TM) − 77% ± 9% − 20% ± 44% .050 0.957
V21% Ktrans(SSM) − 71% ± 9% − 16% ± 50% .052 0.957
V21% τi 41% ± 26% − 11% ± 25% .018 0.946
V2 ve(SSM) 0.78 ± 0.10 0.60 ± 0.14 .073 0.897
V21% ve(TM) 80% ± 60% 35% ± 42% .026 0.880
V21% ve(SSM) 72% ± 41% 19% ± 28% .033 0.880
V2 ve(TM) 0.70 ± 0.37 0.29 ± 0.11 .018 0.864
V3 ve(TM) 0.63 ± 0.31 0.32 ± 0.15 .035 0.845
V3 ve(SSM) 0.81 ± 0.11 0.63 ± 0.15 .088 0.845
V1 τi (s) 0.53 ± 0.16 0.81 ± 0.26 .047 0.826
V31% ve(SSM) 80% ± 54% 27% ± 30% .041 0.810
V21% kep(SSM) − 77% ± 12% − 11% ± 94% .092 0.804
V31% ve(TM) 141% ± 115% 65% ± 85% .070 0.804
V31% RECIST LD − 35% ± 21% − 26% ± 20% .438 0.673
V21% RECIST LD − 15% ± 16% − 10% ± 11% .320 0.609

ULR: univariate logistic regression; SD: standard deviation; P value: two-sample t test; TM: Tofts model; SSM: Shutter-Speed model.