Three-dimensional dose accumulation in pseudo-split-field IMRT and brachytherapy for locally advanced cervical cancer

Development and performance assessment of an advanced Lucas-Kanade algorithm for dose mapping of cervical cancer external radiotherapy and brachytherapy plans

PURPOSE

The aim of this study was to verify the possibility of summing the dose distributions of combined radiotherapeutic treatment of cervical cancer using the extended Lucas-Kanade algorithm for deformable image registration.

MATERIALS AND METHODS

First, a deformable registration of planning computed tomography images for the external radiotherapy and brachytherapy treatment of 10 patients with different parameter settings of the Lucas-Kanade algorithm was performed. By evaluating the registered data using landmarks distance, root mean square error of Hounsfield units and 2D gamma analysis, the optimal parameter values were found. Next, with another group of 10 patients, the accuracy of the dose mapping of the optimized Lucas-Kanade algorithm was assessed and compared with Horn-Schunck and modified Demons algorithms using dose differences at landmarks.

RESULTS

The best results of the Lucas-Kanade deformable registration were achieved for two pyramid levels in combination with a window size of 3 voxels. With this registration setting, the average landmarks distance was 2.35 mm, the RMSE was the smallest and the average gamma score reached a value of 86.7%. The mean dose difference at the landmarks after mapping the external radiotherapy and brachytherapy dose distributions was 1.33 Gy. A statistically significant difference was observed on comparing the Lucas-Kanade method with the Horn-Schunck and Demons algorithms, where after the deformable registration, the average difference in dose was 1.60 Gy (P-value: 0.0055) and 1.69 Gy (P-value: 0.0012), respectively.

CONCLUSION

Lucas-Kanade deformable registration can lead to a more accurate model of dose accumulation and provide a more realistic idea of the dose distribution.

Concurrent chemoradiation for cervical cancer: Comparison of LDR and HDR brachytherapy

PURPOSE

To compare clinical outcomes between low-dose-rate (LDR) brachytherapy and high-dose-rate (HDR) brachytherapy for cervical cancer patients.

METHODS AND MATERIALS

All consecutive newly diagnosed cervical cancer patients undergoing pretreatment 18-fluorodeoxyglucose positron emission tomography imaging and treated with curative-intent definitive chemoradiation from 1997 to 2016 at a U.S. academic center were included. Brachytherapy boost was LDR or HDR 2D treatment planning from 1997 to 2005 and HDR with MR-based 3D planning from 2005 to 2016. Local control (LC), cancer-specific survival (CSS), and late bowel/bladder complications were evaluated.

RESULTS

Tumor stages were International Federation of Gynecology and Obstetrics IB1-IIB (n = 457; 75%) and III-IVA (n = 152; 25%). Brachytherapy was LDR for 104 patients and HDR for 505 patients. Concurrent weekly cisplatin was administered to 536 patients (88%). With median followup of 9.4 years, there was no difference in LC (p = 0.24) or CSS (p = 0.50) between LDR and HDR brachytherapy. Cox multivariable regression showed that only International Federation of Gynecology and Obstetrics stage III-IVA (HR=2.4, p = 0.004) was associated with worse LC. A propensity-matched cohort (90 LDR vs. 90 HDR) was created, and the 5-year LC rates were 88% LDR and 82% HDR, p = 0.26; 5-year CSS rates were 66% LDR and 58% HDR, p = 0.19; 5-year grade ≥3 bowel/bladder toxicities were 23% LDR and 16% HDR, p = 0.44. For all patients, the 5-year late toxicity in stage III-IVA patients was higher with LDR 47% vs. HDR 15%, p = 0.03, with no difference in LC, 86% and 75%, respectively (p = 0.09).

CONCLUSIONS

There was no difference in LC with either LDR or HDR brachytherapy. The late complication rate was reduced with HDR and 3D-planned brachytherapy compared to LDR and 2D-planned brachytherapy.

Computerized triplet beam orientation optimization for MRI-guided Co-60 radiotherapy

PURPOSE

Magnetic resonance imaging (MRI)-guided Co-60 provides daily and intrafractional MRI soft tissue imaging for improved target and critical organ tracking. To increase delivery efficiency, the system uses three Co-60 sources at 120° apart, allowing up to 600 cGy combined dose rate at isocenter. Despite the potential tripling in output, creating a delivery plan that uses all three sources is considerably unintuitive. Here, the authors computerize the triplet orientation optimization using column generation, an approach that was demonstrated effective in integrated beam orientation and fluence optimization for noncoplanar therapies. To achieve a better plan quality without increasing the treatment time, the authors then solve a fluence map optimization (FMO) problem while regularizing the fluence maps to reduce the number of deliverable MLC segments.

METHODS

Three patients-one prostate, one lung, and one head and neck boost plan (H&N_Boost)-were evaluated in this study. For each patient, the beamlet doses were calculated using Monte Carlo, under a 0.35 T magnetic field, for 180 equally spaced coplanar beams grouped into 60 triplets. The beamlet size is 1.05 × 0.5 cm determined by the MLC leaf thickness and step size. The triplets were selected using the column generation algorithm. The FMO problem was formulated using an L2-norm dose fidelity term and an L1-norm anisotropic total variation regularization term, which allows controlling the number of MLC segments, and hence the treatment time, with minimal degradation to the dose. The authors' Fluence Regularization and Optimized Selection of Triplets (FROST) plans were compared against the clinical treatment plans (CLNs) produced by an experienced dosimetrist. PTV homogeneity, max dose, mean dose, D95, D98, and D99 were evaluated. OAR max and mean doses, as well as R50, defined as the ratio of the 50% isodose volume over the planning target volume were investigated.

RESULTS

The mean PTV D95, D98, and D99 differ by +0.04%, +0.07%, and +0.25% of the prescription dose between planning methods. The mean PTV homogeneity was virtually same with values at 0.8788 (FROST) and 0.8812 (CLN). R50 decreased by 0.67 comparing FROST to CLN. On average, FROST reduced D_max and D_mean of OARs by 7.30% and 6.08% of the prescription dose, respectively. The manual CLN planning processes required numerous trial and error runs. The FROST plans on the other hand required minimal human intervention.

CONCLUSIONS

Efficient delivery of MRI-guided Co-60 therapy needs the output of multiple sources yet suffers from unintuitive and laborious manual beam selection processes. Computerized triplet orientation optimization improves both planning efficiency and plan dosimetry. The novel fluence map regularization provides additional controls over the number of MLC segments and treatment time.

Accumulation of rectum dose-volume metrics for prostate external beam radiotherapy combined with brachytherapy: Evaluating deformably registered dose distribution addition using parameter-based addition

INTRODUCTION

To investigate the accuracy of deriving dose-volume histogram (DVH) parameters from deformably registered data by comparing values with the simple addition of DVHs from each phase of a combined external beam radiotherapy (EBRT)/high-dose-rate (HDR-BT) brachytherapy prostate treatment.

METHODS

Eighty-two patients received EBRT in 23 fractions of 2 Gy and HDR-BT TG43 in three fractions of 6.5 Gy. The HDR-BT CT was deformably registered to the EBRT CT. The rectum D_0.1cc , D_1cc , D_2cc and D_10cc were calculated in two ways. (i) Parameter-adding: the EBRT DVH parameters (or the EBRT prescription dose) were added to the unregistered HDR-BT DVH parameters. (ii) Distribution-adding: the parameters were extracted after the EBRT doses were 3D-summed with the registered HDR-BT doses. Resulting differences between the parameters were investigated.

RESULTS

The D_0.1cc , D_1cc and D_2cc from parameter-adding were 21.3% (P < 0.001), 6.3% (P < 0.001) and 3.5% (P < 0.001) smaller than those from distribution-adding. The D_10cc was 2.2% (P = 0.015) larger for distribution-adding.

CONCLUSION

Distribution-adding was confounded by unsystematic inter/intra-observer rectum-contouring errors and registration accuracy near the anterior rectal wall. Consequently, clinical use of distribution-adding to assess rectal doses requires careful contour and registration evaluation.

Clinical implementation of multisequence MRI-based adaptive intracavitary brachytherapy for cervix cancer

The purpose of this study was to describe the clinical implementation of a magnetic resonance image (MRI)-based approach for adaptive intracavitary brachytherapy (ICBT) of cervix cancer patients. Patients were implanted with titanium tandem and colpostats. MR imaging was performed on a 1.5-T Philips scanner using T2-weighted (T2W), proton-density weighted (PDW), and diffusion-weighted (DW) imaging sequences. Apparent diffusion coefficient (ADC) maps were generated from the DW images. All images were fused. T2W images were used for the definition of organs at risk (OARs) and dose points. ADC maps in conjunction with T2W images were used for target delineation. PDW images were used for applicator definition. Forward treatment planning was performed using standard source distribution rules normalized to Point A. Point doses and dose-volume parameters for the tumor and OARs were exported to an automated dose-tracking application. Brachytherapy doses were adapted for tumor shrinkage and OAR variations during the course of therapy. The MRI-based ICBT approach described here has been clinically implemented and is carried out for each brachytherapy fraction. Total procedure time from patient preparation to delivery of treatment is typically 2 hrs. Implementation of our tech-nique for structure delineation, applicator definition, dose tracking, and adaptation is demonstrated using treated patient examples. Based on published recommendations and our clinical experience in the radiation treatment of cervix cancer patients, we have refined our standard approach to ICBT by 1) incorporating a multisequence MRI technique for improved visualization of the target, OARs, and applicator, and by 2) implementing dose adaptation by use of automated dose tracking tools.