Hualin Zhang

Predicting Control of Primary Tumor and Survival by DCE MRI During Early Therapy in Cervical Cancer

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 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 poorly-perfused 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 3-dimensional 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: 0.2–9.4 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 to 2.5 weeks into treatment. An SI5% of <2.05 and residual tumor volume of ≥30 cm3 in the MRI obtained at 2 to 2.5 weeks of therapy provided the best prediction of unfavorable 8-year primary tumor control (73% vs. 100%, P = 0.006) and disease-free-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 to 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.

Longitudinal Changes in Tumor Perfusion Pattern during the Radiation Therapy Course and its Clinical Impact in Cervical Cancer

PURPOSEnTo study the temporal changes of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) perfusion patterns during the radiation therapy (RT) course and their influence on local control and survival in cervical cancer.nnnMETHODS AND MATERIALSnDCE-MRI was performed in 98 patients with Stage IB(2)-IVA cervical cancer before RT (pre-RT) and during early RT (20-25 Gy) and mid-RT (45-50 Gy). Signal intensity (SI) from the DCE-MRI time-SI curve was derived for each tumor voxel. The poorly perfused low-DCE tumor subregions were quantified as lower 10th percentiles of SI (SI10). Local control, disease-specific survival, and overall survival were correlated with DCE parameters at pre-RT, early RT, and mid-RT. Median follow-up was 4.9 (range, 0.2-9.0) years.nnnRESULTSnPatients (16/98) with initial pre-RT high DCE (SI10 >or=2.1) had 100% 5-year local control, 81% disease-specific survival, and 81% overall survival, compared with only 79%, 61%, and 55%, respectively, in patients with pre-RT low DCE. Conversion from pre-RT low DCE to high DCE in early RT (28/82 patients) was associated with higher local control, disease-specific survival, and overall survival (93%, 74%, and 67%, respectively). In comparison with all other groups, outcome was worst in patients with persistently low DCE from pre-RT throughout the mid-RT phase (66%, 44%, and 43%; p = 0.003, 0.003, and 0.020; respectively).nnnCONCLUSIONnLongitudinal tumor perfusion changes during RT correlate with treatment outcome. Persistently low perfusion in pre-RT, early RT, and mid-RT indicates a high risk of treatment failure, whereas outcome is favorable in patients with initially high perfusion or subsequent improvements of initially low perfusion. These findings likely reflect reoxygenation and may have potential for noninvasive monitoring of intra-treatment radio-responsiveness and for guiding adaptive therapy.

Predicting outcomes in cervical cancer: a kinetic model of tumor regression during radiation therapy.

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) > or = 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) > or = 22 days, P < 0.001). The 6-year disease-specific survival was 73% versus 41% with S(2) < 0.70 versus S(2) > or = 0.70 (P = 0.025), and 87% vs. 52% with T(1/2) < 22 days versus T(1/2) > or = 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.

When tumor repopulation starts? The onset time of prostate cancer during radiation therapy.

Abstract Purpose. To analyze published clinical data and provide a preliminary estimate of tumor repopulation rate and its onset time during radiation therapy for prostate cancer. Methods. Data on prostate cancer treated with external beam radiotherapy (EBRT) by Perez et al. (2004), Amdur et al. (1990) and Lai et al. (1991) were analyzed in this study. The stage-combined pelvic control rate from Perez et al. was calculated to be 0.95±0.01, 0.87±0.02, and 0.72±0.04 for patients treated ≤7 weeks, 7.1–9 weeks, and >9 weeks respectively. Based on the Linear-Quadratic model, extended to account for tumor repopulation, the least χ2 method was used to fit the clinical data and derive the onset time (Tk) and effective doubling time (Td) for prostate cancer. Similar analysis was performed for the other two datasets. Results. Best fit was achieved with onset time Tk=34±7 days and doubling time Td=12±2 days. These parameters were independent of the choice of the α/β values currently published in the literature. Analyses of the other two datasets showed Tk=42±7 days with Td=9 ± 3 days, and Tk=34±6 days with Td=34±5 days, respectively. Tk was found to be dependent on tumor stage. Conclusions. Consistent values for onset time Tk were obtained from different datasets, while the range of doubling time Td was large. Tumor repopulation starts no later than 58 days (at 90% confidence level) in the course of EBRT for prostate cancer.

A comprehensive dosimetric comparison between 131Cs and 125I brachytherapy sources for COMS eye plaque implant

PURPOSEnTo verify the dosimetric characteristics of (131)Cs source in the Collaborative Ocular Melanoma Study (COMS) eye plaque brachytherapy, to compare (131)Cs with (125)I in a sample implant, and to examine the accuracy of treatment planning system in dose calculation.nnnMETHODS AND MATERIALSnMonte Carlo (MC) technique was used to generate three-dimensional dose distributions of a 16-mm COMS eye plaque loaded with (131)Cs and (125)I brachytherapy sources separately. A spherical eyeball, 24.6mm in diameter, and an ellipsoidal tumor, 6mm in height and 12mm in diameter, were used to evaluate the doses delivered. The simulations were carried out both with and without the gold and gold alloy plaque. A water-equivalent seed carrier was used instead of the silastic insert designed for the traditional COMS eye plaque. The 13 sources involved were also individually simulated to evaluate the intersource effect. In addition, a treatment planning system was used to calculate the doses at the central axis for comparison with MC data.nnnRESULTSnThe gold plaque had significantly reduced the dose in the tumor volume; at the prescription point of this study, that is, 6mm from the edge of inner sclera, the gold plaque reduced the dose by about 7% for both types of (131)Cs and (125)I sources, but the gold alloy plaque reduced the dose only by 4% for both types of sources. The intersource effect reduced the dose by 2% for both types of sources. At the same prescription dose, the treatment with the gold plaque applicator tended to create more hot regions for either type of sources than were seen with the homogeneous water phantom. The doses of TPS agree with the MC.nnnCONCLUSIONnThe (131)Cs source is comparable to the (125)I source in the eye plaque brachytherapy. The TPS can provide accurate dose calculations for eye plaque implants with either type of sources.

Hypofractionation Regimens for Stereotactic Radiotherapy for Large Brain Tumors

PURPOSEnTo investigate equivalent regimens for hypofractionated stereotactic radiotherapy (HSRT) for brain tumor treatment and to provide dose-escalation guidance to maximize the tumor control within the normal brain tolerance.nnnMETHODS AND MATERIALSnThe linear-quadratic model, including the effect of nonuniform dose distributions, was used to evaluate the HSRT regimens. The alpha/beta ratio was estimated using the Gammaknife stereotactic radiosurgery (GKSRS) and whole-brain radiotherapy experience for large brain tumors. The HSRT regimens were derived using two methods: (1) an equivalent tumor control approach, which matches the whole-brain radiotherapy experience for many fractions and merges it with the GKSRS data for few fractions; and (2) a normal-tissue tolerance approach, which takes advantages of the dose conformity and fractionation of HSRT to approach the maximal dose tolerance of the normal brain.nnnRESULTSnA plausible alpha/beta ratio of 12 Gy for brain tumor and a volume parameter n of 0.23 for normal brain were derived from the GKSRS and whole-brain radiotherapy data. The HSRT prescription regimens for the isoeffect of tumor irradiation were calculated. The normal-brain equivalent uniform dose decreased as the number of fractions increased, because of the advantage of fractionation. The regimens for potential dose escalation of HSRT within the limits of normal-brain tolerance were derived.nnnCONCLUSIONSnThe designed hypofractionated regimens could be used as a preliminary guide for HSRT dose prescription for large brain tumors to mimic the GKSRS experience and for dose escalation trials. Clinical studies are necessary to further tune the model parameters and validate these regimens.

Outcome Prediction of Cervical Cancer: Kinetic Model of Tumor Regression during Radiation Therapy

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) > or = 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) > or = 22 days, P < 0.001). The 6-year disease-specific survival was 73% versus 41% with S(2) < 0.70 versus S(2) > or = 0.70 (P = 0.025), and 87% vs. 52% with T(1/2) < 22 days versus T(1/2) > or = 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.

Tumor imaging: radiation oncology perspective.

BACKGROUND Until 30 years ago, radiation oncology, previously known as therapeutic radiology, was one of the subspecialties of radiology. It was an era in which radiation therapy planning was performed using plain radiograph images and clinical setups. After the rapid growth and developments within the specialty, most radiation oncology divisions became independent departments. With the development of modern image-based treatment planning, diagnostic imaging has now become an integral part of radiation oncology. One of the most important factors impacting treatment outcome is the amount of radiation that can be safely be delivered to the tumor (target). This is often limited by the radiation tolerance of critical structures, such as the optic pathway, brainstem, spinal cord, and cochlea. To maximize the therapeutic ratio, accurate delineation of the target and the critical structures is necessary. With the advancement of imaging technology, the delineation of the target volumes and the critical structures for treatment planning has achieved millimeter spatial resolution. With advancements in technology, such as the multileaf collimation, 3-dimensional (3-D) radiation therapy, intensity-modulated radiation treatment (IMRT), and image-guided radiation therapy, the delivery of radiation dose is now at millimeter precision. Image-guided radiation therapy uses techniques to verify the location of the tumor or target volume before each treatment. With an increased accuracy in treatment delivery, radiation margins surrounding the target can be decreased, increasing the therapeutic ratio.

Predicting outcomes in cervical cancer

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) > or = 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) > or = 22 days, P < 0.001). The 6-year disease-specific survival was 73% versus 41% with S(2) < 0.70 versus S(2) > or = 0.70 (P = 0.025), and 87% vs. 52% with T(1/2) < 22 days versus T(1/2) > or = 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.

Fractionated Grid Therapy in Treating Cervical Cancer

Purpose: To evaluate the potential therapeutic advantage of external beam grid therapy in treating cervical cancers in comparison of conventional open field radiotherapy.