The addition of ifosfamide in this dose schedule to standard chemotherapy did not enhance EFS. The addition of MTP to chemotherapy might improve EFS, but additional clinical and laboratory investigation will be necessary to explain the interaction between ifosfamide and MTP.

Applications of mathematical modeling can improve outcome predictions of cancer therapy. Here we present a kinetic model incorporating effects of radiosensitivity, tumor repopulation, and dead-cell resolving on the analysis of tumor volume regression data of 80 cervical cancer patients (stages 1B2-IVA) who underwent radiation therapy. Regression rates and derived model parameters correlated significantly with clinical outcome (P < 0.001; median follow-up: 6.2 years). The 6-year local tumor control rate was 87% versus 54% using radiosensitivity (2-Gy surviving fraction S 2 < 0.70 vs. S 2 ≥ 0.70) as a predictor (P = 0.001) and 89% vs. 57% using dead-cell resolving time (T 1/2 < 22 days versus T 1/2 ≥ 22 days, P < 0.001). The 6-year disease-specific survival was 73% versus 41% with S 2 < 0.70 versus S 2 ≥ 0.70 (P = 0.025), and 87% vs. 52% with T 1/2 < 22 days versus T 1/2 ≥ 22 days (P = 0.002). Our approach illustrates the promise of volume-based tumor response modeling to improve early outcome predictions that can be used to enable personalized adaptive therapy. Cancer Res; 70(2); 463-70. ©2010 AACR.

Purpose-To assess the early predictive power of MRI perfusion and volume parameters, during early treatment of cervical cancer, for primary tumor control and disease-free-survival.Materials and Methods-Three MRI examinations were obtained in 101 patients before and during therapy (at 2-2.5 and 4-5 weeks) for serial dynamic contrast enhanced (DCE) perfusion MRI and 3-dimensional (3D) tumor volume measurement. Plateau Signal Intensity (SI) of the DCE curves for each tumor pixel of all 3 MRI examinations was generated, and pixel-SI distribution histograms were established to characterize the heterogeneous tumor. The degree and quantity of the poorlyperfused tumor subregions, which were represented by low-DCE pixels, was analyzed by using various lower percentiles of SI (SI%) from the pixel histogram. SI% ranged from SI2.5% to SI20% with increments of 2.5%. SI%, mean SI, and 3D-volume of the tumor were correlated with primary tumor control and disease-free-survival, using Student t-test, Kaplan-Meier analysis and log-rank test. The mean post-therapy follow-up time for outcome assessment was 6.8 years (range: 1.2-12.3 years).Results-Tumor volume, mean SI, and SI% showed significant prediction of the long-term clinical outcome, and this prediction was provided as early as 2-2.5 weeks into treatment. An SI5% of <2.05 and residual tumor volume of ≥30 cm 3 in the MRI obtained at 2-2.5 weeks of therapy provided the best prediction of unfavorable 8-year primary tumor control (73% vs. 100%, p=0.006) and diseasefree-survival rate (47% vs. 79%, p=0.001), respectively.Conclusions-Our results show that MRI parameters quantifying perfusion status and residual tumor volume provide very early prediction of primary tumor control and disease-free-survival. This functional imaging based outcome predictor can be obtained in the very early phase of cytotoxic therapy within 2-2.5 weeks of therapy start. The predictive capacity of these MRI parameters, indirectly reflecting the heterogeneous delivery pattern of cytotoxic agents, tumor oxygenation and the bulk of residual presumably therapy-resistant tumor, requires future study.

Most cervical cancers are not oval in shape pretherapy, and they become increasingly irregular during and after therapy because of nonconcentric tumor shrinkage. ROI-based volumetry, which can optimally measure irregular volumes, may provide better response assessment during treatment than diameter-based measurement.