Indoximod-based chemo-immunotherapy for pediatric brain tumors: A first-in-children phase I trial.

BACKGROUND: Recurrent brain tumors are the leading cause of cancer death in children. Indoleamine 2,3-dioxygenase (IDO) is a targetable metabolic checkpoint that, in preclinical models, inhibits anti-tumor immunity following chemotherapy. METHODS: We conducted a phase I trial (NCT02502708) of the oral IDO-pathway inhibitor indoximod in children with recurrent brain tumors or newly diagnosed diffuse intrinsic pontine glioma (DIPG). Separate dose-finding arms were performed for indoximod in combination with oral temozolomide (200 mg/m2/day x 5 days in 28-day cycles), or with palliative conformal radiation. Blood samples were collected at baseline and monthly for single-cell RNA-sequencing with paired single-cell T cell receptor sequencing. RESULTS: Eighty-one patients were treated with indoximod-based combination therapy. Median follow-up was 52 months (range 39-77 months). Maximum tolerated dose was not reached, and the pediatric dose of indoximod was determined as 19.2 mg/kg/dose, twice daily. Median overall survival was 13.3 months (n = 68, range 0.2-62.7) for all patients with recurrent disease and 14.4 months (n = 13, range 4.7-29.7) for DIPG. The subset of n = 26 patients who showed evidence of objective response (even a partial or mixed response) had over 3-fold longer median OS (25.2 months, range 5.4-61.9, p = 0.006) compared to n = 37 nonresponders (7.3 months, range 0.2-62.7). Four patients remain free of active disease longer than 36 months. Single-cell sequencing confirmed emergence of new circulating CD8 T cell clonotypes with late effector phenotype. CONCLUSIONS: Indoximod was well tolerated and could be safely combined with chemotherapy and radiation. Encouraging preliminary evidence of efficacy supports advancing to Phase II/III trials for pediatric brain tumors.

Evaluation of commercial devices for patient specific QA of stereotactic radiotherapy plans.

Stereotactic radiotherapy (SRT) methods have become common for the treatment of small tumors in various parts of the body. Small field dosimetry has a unique set of challenges when it comes to the pre-treatment validation of a radiotherapy plan that involves film dosimetry or high-resolution detectors. Comparison of commercial quality assurance (QA) devices to the film dosimetry method for pre-treatment evaluation of stereotactic radiosurgery (SRS), fractionated SRT, and stereotactic body radiation therapy treatment plans have been evaluated in this study. Forty stereotactic QA plans were measured using EBT-XD film, IBA Matrixx Resolution, SNC ArcCHECK, Varian aS1200 EPID, SNC SRS MapCHECK, and IBA myQA SRS. The results of the commercial devices are compared to the EBT-XD film dosimetry results for each gamma criteria. Treatment plan characteristics such as modulation factor and target volume were investigated for correlation with the passing rates. It was found that all detectors have greater than 95% passing rates at 3%/3 mm. Passing rates decrease rapidly for ArcCHECK and the Matrixx as criteria became more strict. In contrast, EBT-XD film, SNC SRS MapCHECK, and IBA myQA SRS passing rates do not decline as rapidly when compared to Matrix Resolution, ArcCHECK, and the EPID. EBT-XD film, SNC SRS MapCHECK, and IBA myQA SRS maintain greater than 90% passing rate at 2%/1 mm and greater than 80% at 1%/1 mm. Additionally, the ability of these devices to detect changes in dose distribution due to MLC positioning errors was investigated. Ten VMAT SBRT/SRS treatment plans were created with 6 MV FFF or 10 MV FFF beam energies using Eclipse 15.6. A MATLAB script was used to create two MLC positioning error scenarios from the original treatment plan. It was found that errors in MLC positioning were most reliably detected at 2%/1 mm for high-resolution detectors and that lower-resolution detectors did not consistently detect MLC positioning errors.

Quantitative cone-beam CT imaging in radiation therapy using planning CT as a prior: first patient studies.

PURPOSE: Quantitative cone-beam CT (CBCT) imaging is on increasing demand for high-performance image guided radiation therapy (IGRT). However, the current CBCT has poor image qualities mainly due to scatter contamination. Its current clinical application is therefore limited to patient setup based on only bony structures. To improve CBCT imaging for quantitative use, we recently proposed a correction method using planning CT (pCT) as the prior knowledge. Promising phantom results have been obtained on a tabletop CBCT system, using a correction scheme with rigid registration and without iterations. More challenges arise in clinical implementations of our method, especially because patients have large organ deformation in different scans. In this paper, we propose an improved framework to extend our method from bench to bedside by including several new components. METHODS: The basic principle of our correction algorithm is to estimate the primary signals of CBCT projections via forward projection on the pCT image, and then to obtain the low-frequency errors in CBCT raw projections by subtracting the estimated primary signals and low-pass filtering. We improve the algorithm by using deformable registration to minimize the geometry difference between the pCT and the CBCT images. Since the registration performance relies on the accuracy of the CBCT image, we design an optional iterative scheme to update the CBCT image used in the registration. Large correction errors result from the mismatched objects in the pCT and the CBCT scans. Another optional step of gas pocket and couch matching is added into the framework to reduce these effects. RESULTS: The proposed method is evaluated on four prostate patients, of which two cases are presented in detail to investigate the method performance for a large variety of patient geometry in clinical practice. The first patient has small anatomical changes from the planning to the treatment room. Our algorithm works well even without the optional iterations and the gas pocket and couch matching. The image correction on the second patient is more challenging due to the effects of gas pockets and attenuating couch. The improved framework with all new components is used to fully evaluate the correction performance. The enhanced image quality has been evaluated using mean CT number and spatial nonuniformity (SNU) error as well as contrast improvement factor. If the pCT image is considered as the ground truth, on the four patients, the overall mean CT number error is reduced from over 300 HU to below 16 HU in the selected regions of interest (ROIs), and the SNU error is suppressed from over 18% to below 2%. The average soft-tissue contrast is improved by an average factor of 2.6. CONCLUSIONS: We further improve our pCT-based CBCT correction algorithm for clinical use. Superior correction performance has been demonstrated on four patient studies. By providing quantitative CBCT images, our approach significantly increases the accuracy of advanced CBCT-based clinical applications for IGRT.