Trends in Adjuvant External Beam Radiation Therapy for Nonanaplastic Thyroid Cancer in California, 2003-2017.

BACKGROUND: External beam radiation therapy (EBRT) is rarely used to treat patients with differentiated or medullary thyroid cancer. Although EBRT is generally administered to patients with high-risk or unresectable diseases, neither its indications for the use nor the associated outcomes are well-defined. We used a statewide cohort to assess the trends in EBRT use and postradiation outcomes in California. METHODS: A population-based study of patients within the California Cancer Registry who underwent EBRT after surgery for nonanaplastic thyroid cancer (2003-2017) was conducted. The primary outcome was the annual utilization rate of EBRT. The secondary outcomes included Kaplan-Meier analysis for cause-specific survival and identifying factors associated with improved survival after EBRT. RESULTS: Among the 57 607 patients with nonanaplastic thyroid cancer from 2003 to 2017, 344 (0.6%) patients received EBRT. EBRT was utilized in 0.4% of papillary, 1.1% of follicular, and 7.7% of medullary thyroid cancers in California. Overall, 99 (28.8%) patients treated with EBRT died of thyroid cancer. The 10-year cause-specific survival of all patients with thyroid cancer after EBRT was 61.5% (95% CI: 54.8%-69.1%) and that of patients without distant disease was 80.3% (95% CI: 73.5%-87.8%). The survival outcomes varied by tumor size, histology, disease stage, patient age at diagnosis, and the presence of extrathyroidal extension (P < .05). CONCLUSIONS: The use of adjuvant EBRT for nonanaplastic thyroid cancer remained stable and low in California from 2003 to 2017. The comparative efficacy of EBRT was not discernible in this study, but disease control appeared durable in select patients. Well-controlled observational studies and/or prospective studies are needed to better define which patients benefit from EBRT.

Clinical assessment of geometric distortion for a 0.35T MR-guided radiotherapy system.

PURPOSE: To estimate the overall spatial distortion on clinical patient images for a 0.35 T MR-guided radiotherapy system. METHODS: Ten patients with head-and-neck cancer underwent CT and MR simulations with identical immobilization. The MR images underwent the standard systematic distortion correction post-processing. The images were rigidly registered and landmark-based analysis was performed by an anatomical expert. Distortion was quantified using Euclidean distance between each landmark pair and tagged by tissue interface: bone-tissue, soft tissue, or air-tissue. For baseline comparisons, an anthropomorphic phantom was imaged and analyzed. RESULTS: The average spatial discrepancy between CT and MR landmarks was 1.15 ± 1.14 mm for the phantom and 1.46 ± 1.78 mm for patients. The error histogram peaked at 0-1 mm. 66% of the discrepancies were <2 mm and 51% <1 mm. In the patient data, statistically significant differences (p-values < 0.0001) were found between the different tissue interfaces with averages of 0.88 ± 1.24 mm, 2.01 ± 2.20 mm, and 1.41 ± 1.56 mm for the air/tissue, bone/tissue, and soft tissue, respectively. The distortion generally correlated with the in-plane radial distance from the image center along the longitudinal axis of the MR. CONCLUSION: Spatial distortion remains in the MR images after systematic distortion corrections. Although the average errors were relatively small, large distortions observed at bone/tissue interfaces emphasize the need for quantitative methods for assessing and correcting patient-specific spatial distortions.

Three differentiation states risk-stratify bladder cancer into distinct subtypes.

Current clinical judgment in bladder cancer (BC) relies primarily on pathological stage and grade. We investigated whether a molecular classification of tumor cell differentiation, based on a developmental biology approach, can provide additional prognostic information. Exploiting large preexisting gene-expression databases, we developed a biologically supervised computational model to predict markers that correspond with BC differentiation. To provide mechanistic insight, we assessed relative tumorigenicity and differentiation potential via xenotransplantation. We then correlated the prognostic utility of the identified markers to outcomes within gene expression and formalin-fixed paraffin-embedded (FFPE) tissue datasets. Our data indicate that BC can be subclassified into three subtypes, on the basis of their differentiation states: basal, intermediate, and differentiated, where only the most primitive tumor cell subpopulation within each subtype is capable of generating xenograft tumors and recapitulating downstream populations. We found that keratin 14 (KRT14) marks the most primitive differentiation state that precedes KRT5 and KRT20 expression. Furthermore, KRT14 expression is consistently associated with worse prognosis in both univariate and multivariate analyses. We identify here three distinct BC subtypes on the basis of their differentiation states, each harboring a unique tumor-initiating population.

The CD47-signal regulatory protein alpha (SIRPa) interaction is a therapeutic target for human solid tumors.

CD47, a "don't eat me" signal for phagocytic cells, is expressed on the surface of all human solid tumor cells. Analysis of patient tumor and matched adjacent normal (nontumor) tissue revealed that CD47 is overexpressed on cancer cells. CD47 mRNA expression levels correlated with a decreased probability of survival for multiple types of cancer. CD47 is a ligand for SIRPα, a protein expressed on macrophages and dendritic cells. In vitro, blockade of CD47 signaling using targeted monoclonal antibodies enabled macrophage phagocytosis of tumor cells that were otherwise protected. Administration of anti-CD47 antibodies inhibited tumor growth in orthotopic immunodeficient mouse xenotransplantation models established with patient tumor cells and increased the survival of the mice over time. Anti-CD47 antibody therapy initiated on larger tumors inhibited tumor growth and prevented or treated metastasis, but initiation of the therapy on smaller tumors was potentially curative. The safety and efficacy of targeting CD47 was further tested and validated in immune competent hosts using an orthotopic mouse breast cancer model. These results suggest all human solid tumor cells require CD47 expression to suppress phagocytic innate immune surveillance and elimination. These data, taken together with similar findings with other human neoplasms, show that CD47 is a commonly expressed molecule on all cancers, its function to block phagocytosis is known, and blockade of its function leads to tumor cell phagocytosis and elimination. CD47 is therefore a validated target for cancer therapies.

MUsculo-Skeleton-Aware (MUSA) deep learning for anatomically guided head-and-neck CT deformable registration.

Deep-learning-based deformable image registration (DL-DIR) has demonstrated improved accuracy compared to time-consuming non-DL methods across various anatomical sites. However, DL-DIR is still challenging in heterogeneous tissue regions with large deformation. In fact, several state-of-the-art DL-DIR methods fail to capture the large, anatomically plausible deformation when tested on head-and-neck computed tomography (CT) images. These results allude to the possibility that such complex head-and-neck deformation may be beyond the capacity of a single network structure or a homogeneous smoothness regularization. To address the challenge of combined multi-scale musculoskeletal motion and soft tissue deformation in the head-and-neck region, we propose a MUsculo-Skeleton-Aware (MUSA) framework to anatomically guide DL-DIR by leveraging the explicit multiresolution strategy and the inhomogeneous deformation constraints between the bony structures and soft tissue. The proposed method decomposes the complex deformation into a bulk posture change and residual fine deformation. It can accommodate both inter- and intra- subject registration. Our results show that the MUSA framework can consistently improve registration accuracy and, more importantly, the plausibility of deformation for various network architectures. The code will be publicly available at https://github.com/HengjieLiu/DIR-MUSA.

A survival prediction model via interpretable machine learning for patients with oropharyngeal cancer following radiotherapy.

PURPOSE: To explore interpretable machine learning (ML) methods, with the hope of adding more prognosis value, for predicting survival for patients with Oropharyngeal-Cancer (OPC). METHODS: A cohort of 427 OPC patients (Training 341, Test 86) from TCIA database was analyzed. Radiomic features of gross-tumor-volume (GTV) extracted from planning CT using Pyradiomics, and HPV p16 status, etc. patient characteristics were considered as potential predictors. A multi-level dimension reduction algorithm consisting of Least-Absolute-Selection-Operator (Lasso) and Sequential-Floating-Backward-Selection (SFBS) was proposed to effectively remove redundant/irrelevant features. The interpretable model was constructed by quantifying the contribution of each feature to the Extreme-Gradient-Boosting (XGBoost) decision by Shapley-Additive-exPlanations (SHAP) algorithm. RESULTS: The Lasso-SFBS algorithm proposed in this study finally selected 14 features, and our prediction model achieved an area-under-ROC-curve (AUC) of 0.85 on the test dataset based on this feature set. The ranking of the contribution values calculated by SHAP shows that the top predictors that were most correlated with survival were ECOG performance status, wavelet-LLH_firstorder_Mean, chemotherapy, wavelet-LHL_glcm_InverseVariance, tumor size. Those patients who had chemotherapy, with positive HPV p16 status, and lower ECOG performance status, tended to have higher SHAP scores and longer survival; who had an older age at diagnosis, heavy drinking and smoking pack year history, tended to lower SHAP scores and shorter survival. CONCLUSION: We demonstrated predictive values of combined patient characteristics and imaging features for the overall survival of OPC patients. The multi-level dimension reduction algorithm can reliably identify the most plausible predictors that are mostly associated with overall survival. The interpretable patient-specific survival prediction model, capturing correlations of each predictor and clinical outcome, was developed to facilitate clinical decision-making for personalized treatment.

Germline biomarkers predict toxicity to anti-PD1/PDL1 checkpoint therapy.

BACKGROUND: There is great interest in finding ways to identify patients who will develop toxicity to cancer therapies. This has become especially pressing in the era of immune therapy, where toxicity can be long-lasting and life-altering, and primarily comes in the form of immune-related adverse effects (irAEs). Treatment with the first drugs in this class, anti-programmed death 1 (anti-PD1)/programmed death-ligand 1 (PDL1) checkpoint therapies, results in grade 2 or higher irAEs in up to 25%-30% of patients, which occur most commonly within the first 6 months of treatment and can include arthralgias, rash, pruritus, pneumonitis, diarrhea and/or colitis, hepatitis, and endocrinopathies. We tested the hypothesis that germline microRNA pathway functional variants, known to predict altered systemic stress responses to cancer therapies, would predict irAEs in patients across cancer types. METHODS: MicroRNA pathway variants were evaluated for an association with grade 2 or higher toxicity using four classifiers on 62 patients with melanoma, and then the panel's performance was validated on 99 patients with other cancer types. Trained classifiers included classification trees, LASSO-regularized logistic regression, boosted trees, and random forests. Final performance measures were reported on the training set using leave-one-out cross validation and validated on held-out samples. The predicted probability of toxicity was evaluated for its association, if any, with response categories to anti-PD1/PDL1 therapy in the melanoma cohort. RESULTS: A biomarker panel was identified that predicts toxicity with 80% accuracy (F1=0.76, area under the curve (AUC)=0.82) in the melanoma training cohort and 77.6% accuracy (F1=0.621, AUC=0.778) in the pan-cancer validation cohort. In the melanoma cohort, the predictive probability of toxicity was not associated with response categories to anti-PD1/PDL1 therapy (p=0.70). In the same cohort, the most significant biomarker of toxicity in RAC1, predicting a greater than ninefold increased risk of toxicity (p<0.001), was also not associated with response to anti-PD1/PDL1 therapy (p=0.151). CONCLUSIONS: A germline microRNA-based biomarker signature predicts grade 2 and higher irAEs to anti-PD1/PDL1 therapy, regardless of tumor type, in a pan-cancer manner. These findings represent an important step toward personalizing checkpoint therapy, the use of which is growing rapidly.

A Prospective Phase II Study of Automated Non-Coplanar VMAT for Recurrent Head and Neck Cancer: Initial Report of Feasibility, Safety, and Patient-Reported Outcomes.

This study reports the initial results for the first 15 patients on a prospective phase II clinical trial exploring the safety, feasibility, and efficacy of the HyperArc technique for recurrent head and neck cancer treatment. Eligible patients were simulated and planned with both conventional VMAT and HyperArc techniques and the plan with superior dosimetry was selected for treatment. Dosimetry, delivery feasibility and safety, treatment-related toxicity, and patient-reported quality of life (QOL) were all evaluated. HyperArc was chosen over conventional VMAT for all 15 patients and enabled statistically significant increases in dose conformity (R50% reduced by 1.2 ± 2.1, p < 0.05) and mean PTV and GTV doses (by 15.7 ± 4.9 Gy, p < 0.01 and 17.1 ± 6.0 Gy, p < 0.01, respectively). The average HyperArc delivery was 2.8 min longer than conventional VMAT (p < 0.01), and the mean intrafraction motion was ≤ 0.5 ± 0.4 mm and ≤0.3 ± 0.1°. With a median follow-up of 12 months, treatment-related toxicity was minimal (only one grade 3 acute toxicity above baseline) and patient-reported QOL metrics were favorable. HyperArc enabled superior dosimetry and significant target dose escalation compared to conventional VMAT planning, and treatment delivery was feasible, safe, and well-tolerated by patients.

Using neural networks to extend cropped medical images for deformable registration among images with differing scan extents.

PURPOSE: Missing or discrepant imaging volume is a common challenge in deformable image registration (DIR). To minimize the adverse impact, we train a neural network to synthesize cropped portions of head and neck CT's and then test its use in DIR. METHODS: Using a training dataset of 409 head and neck CT's, we trained a generative adversarial network to take in a cropped 3D image and output an image with synthesized anatomy in the cropped region. The network used a 3D U-Net generator along with Visual Geometry Group (VGG) deep feature losses. To test our technique, for each of the 53 test volumes, we used Elastix to deformably register combinations of a randomly cropped, full, and synthetically full volume to a single cropped, full, and synthetically full target volume. We additionally tested our method's robustness to crop extent by progressively increasing the amount of cropping, synthesizing the missing anatomy using our network, and then performing the same registration combinations. Registration performance was measured using 95% Hausdorff distance across 16 contours. RESULTS: We successfully trained a network to synthesize missing anatomy in superiorly and inferiorly cropped images. The network can estimate large regions in an incomplete image, far from the cropping boundary. Registration using our estimated full images was not significantly different from registration using the original full images. The average contour matching error for full image registration was 9.9 mm, whereas our method was 11.6, 12.1, and 13.6 mm for synthesized-to-full, full-to-synthesized, and synthesized-to-synthesized registrations, respectively. In comparison, registration using the cropped images had errors of 31.7 mm and higher. Plotting the registered image contour error as a function of initial preregistered error shows that our method is robust to registration difficulty. Synthesized-to-full registration was statistically independent of cropping extent up to 18.7 cm superiorly cropped. Synthesized-to-synthesized registration was nearly independent, with a -0.04 mm of change in average contour error for every additional millimeter of cropping. CONCLUSIONS: Different or inadequate in scan extent is a major cause of DIR inaccuracies. We address this challenge by training a neural network to complete cropped 3D images. We show that with image completion, the source of DIR inaccuracy is eliminated, and the method is robust to varying crop extent.

Automated Non-Coplanar VMAT for Dose Escalation in Recurrent Head and Neck Cancer Patients.

This study evaluates the potential for tumor dose escalation in recurrent head and neck cancer (rHNC) patients with automated non-coplanar volumetric modulated arc therapy (VMAT) stereotactic body radiation therapy (SBRT) planning (HyperArc). Twenty rHNC patients are planned with conventional VMAT SBRT to 40 Gy while minimizing organ-at-risk (OAR) doses. They are then re-planned with the HyperArc technique to match these minimal OAR doses while escalating the target dose as high as possible. Then, we compare the dosimetry, tumor control probability (TCP), and normal tissue complication probability (NTCP) for the two plan types. Our results show that the HyperArc technique significantly increases the mean planning target volume (PTV) and gross tumor volume (GTV) doses by 10.8 ± 4.4 Gy (25%) and 11.5 ± 5.1 Gy (26%) on average, respectively. There are no clinically significant differences in OAR doses, with maximum dose differences of <2 Gy on average. The average TCP is 23% (± 21%) higher for HyperArc than conventional plans, with no significant differences in NTCP for the brainstem, cord, mandible, or larynx. HyperArc can achieve significant tumor dose escalation while maintaining minimal OAR doses in the head and neck-potentially enabling improved local control for rHNC SBRT patients without increased risk of treatment-related toxicities.

Lymphotoxin is required for maintaining physiological levels of serum IgE that minimizes Th1-mediated airway inflammation.

Although elevated levels of IgE in asthmatic patients are strongly associated with lung infiltration by activated T helper (Th) 2 cells, the physiological role of immunoglobulin E (IgE) in the airway remains largely undefined. Lymphotoxin-deficient alpha (LTalpha-/-) mice exhibit increased airway inflammation, paradoxically accompanied by diminished levels of IgE and reduced airway hyperresponsiveness in response to both environmental and induced antigen challenge. The severe lung inflammation in LTalpha-/- mice is Th1 in nature and can be alleviated by IgE reconstitution. Conversely, depletion of IgE in wild-type mice recapitulates the lung pathologies of LTalpha-/- mice. Therefore, this work has revealed that lymphotoxin is essential for IgE production, and a physiological role of IgE in the airway may consist of maintaining the balance of Th1 and Th2 responses to prevent aberrant inflammation.

A novel anthropomorphic multimodality phantom for MRI-based radiotherapy quality assurance testing.

PURPOSE: Increased utilization of magnetic resonance imaging (MRI) in radiotherapy has caused a growing need for phantoms that provide tissue-like contrast in both computed tomography (CT) and MRI images. Such phantoms can be used to compare MRI-based processes with CT-based clinical standards. Here, we develop and demonstrate the clinical utility of a three-dimensional (3D)-printed anthropomorphic pelvis phantom containing materials capable of T1 , T2 , and electron density matching for a clinically relevant set of soft tissues and bone. METHODS: The phantom design was based on a male pelvic anatomy template with thin boundaries separating tissue types. Slots were included to allow insertion of various dosimeters. The phantom structure was created using a 3D printer. The tissue compartments were filled with carrageenan-based materials designed to match the T1 and T2 relaxation times and electron densities of the corresponding tissues. CT and MRI images of the phantom were acquired and used to compare phantom T1 and T2 relaxation times and electron densities to literature-reported values for human tissue. To demonstrate clinical utility, the phantom was used for end-to-end testing of an MRI-only treatment simulation and planning workflow. Based on a T2 -weighted MRI image, synthetic CT (sCT) images were created using a statistical decomposition algorithm (MRIPlanner, Spectronic Research AB, Sweden) and used for dose calculation of volumetric-modulated arc therapy (VMAT) and seven-field intensity-modulated radiation therapy (IMRT) prostate plans. The plans were delivered on a Truebeam STX (Varian Medical Systems, Palo Alto, CA), with film and a 0.3 cc ion chamber used to measure the delivered dose. Doses calculated on the CT and sCTs were compared using common dose volume histogram metrics. RESULTS: T1 and T2 relaxation time and electron density measurements for the muscle, prostate, and bone agreed well with literature-reported in vivo measurements. Film analysis resulted in a 99.7% gamma pass rate (3.0%, 3.0 mm) for both plans. The ion chamber-measured dose discrepancies at the isocenter were 0.36% and 1.67% for the IMRT and VMAT plans, respectively. The differences in PTV D98% and D95% between plans calculated on the CT and 1.5T/3.0 T-derived sCT images were under 3%. CONCLUSION: The developed phantom provides tissue-like contrast on MRI and CT and can be used to validate MRI-based processes through comparison with standard CT-based processes.

Analysis of Geometric Performance and Dosimetric Impact of Using Automatic Contour Segmentation for Radiotherapy Planning.

Purpose: To analyze geometric discrepancy and dosimetric impact in using contours generated by auto-segmentation (AS) against manually segmented (MS) clinical contours. Methods: A 48-subject prostate atlas was created and another 15 patients were used for testing. Contours were generated using a commercial atlas-based segmentation tool and compared to their clinical MS counterparts. The geometric correlation was evaluated using the Dice similarity coefficient (DSC) and Hausdorff distance (HD). Dosimetric relevance was evaluated for a subset of patients by assessing the DVH differences derived by optimizing plan dose using the AS and MS contours, respectively, and evaluating with respect to each. A paired t-test was employed for statistical comparison. The discrepancy in plan quality with respect to clinical dosimetric endpoints was evaluated. The analysis was repeated for head/neck (HN) with a 31-subject atlas and 15 test cases. Results: Dice agreement between AS and MS differed significantly across structures: from (L:0.92/R: 0.91) for the femoral heads to seminal vesical of 0.38 in the prostate cohort, and from 0.98 for the brain, to 0.36 for the chiasm of the HN group. Despite the geometric disagreement, the paired t-tests showed the lack of statistical evidence for systematic differences in dosimetric plan quality yielded by the AS and MS approach for the prostate cohort. In HN cases, statistically significant differences in dosimetric endpoints were observed in structures with small volumes or elongated shapes such as cord (p = 0.01) and esophagus (p = 0.04). The largest absolute dose difference of 11 Gy was seen in the mean pharynx dose. Conclusion: Varying AS performance among structures suggests a differential approach of using AS on a subset of structures and focus MS on the rest. The discrepancy between geometric and dosimetric-end-point driven evaluation also indicates the clinical utility of AS contours in optimization and evaluating plan quality despite of suboptimal geometrical accuracy.

Clinical Development and Evaluation of Megavoltage Topogram for Fast Patient Alignment on Helical Tomotherapy.

PURPOSE: To develop and evaluate a fast patient localization tool using megavoltage (MV)-topogram on helical tomotherapy. METHODS AND MATERIALS: Eighty-one MV-topogram pairs for 18 pelvis patients undergoing radiation were acquired weekly under an institutional review board-approved clinical trial. The MV-topogram imaging protocol requires 2 orthogonal acquisitions at static gantry angles of 0 degrees and 90 degrees for a programed scan length. A MATLAB based in-house software was developed to reconstruct the MV-topograms offline. Reference images (digitally reconstructed topograms, digitally reconstructed topograms) were generated using the planning computed tomography and tomotherapy geometry. The MV-topogram based alignment was determined by registering the MV-topograms to the digitally reconstructed topogram using bony landmark on commercial MIM software. The daily shifts in 3 translational directions determined from MV-topograms were compared with the megavoltage computed tomography (MVCT) based patient shifts. Linear-regression and two one-sided tests equivalence tests were performed to investigate the relation and equivalence between the 2 techniques. Seventy-eight MV-topogram pairs for 19 head and neck patients were included to validate the finding. RESULTS: The magnitudes of alignment differences of (MVCT - MV-topogram) (and standard deviations) were -0.3 ± 2.1, -0.8 ± 2.4, and 1.6 ± 1.7 mm for pelvis and 0.6 ± 1.2, 0.8 ± 4.2, 1.6 ± 2.6 mm for head and neck; the linear-regression coefficients between 2 imaging techniques were 1.18, 1.10, 0.94, and 0.86, 0.63, 0.38 in the lateral, longitudinal, vertical directions for pelvis and head and neck, respectively. The acquisition time for a pair of MV-topograms was up to 12.7 times less than MVCT scans (coarse scan mode) while covering longer longitudinal length. CONCLUSIONS: MV-topograms showed equivalent clinical performance to the standard MVCT with significantly less acquisition time for pelvis and H&N patients. The MV-topogram can be used as an alternative or complimentary tool for bony landmark-based patient alignment on tomotherapy.

NF-kappaB2 is required for the establishment of central tolerance through an Aire-dependent pathway.

NF-kappaB2-deficient mice have impaired T and B cell responses. We found, however, that in these mice there was severe infiltration of lymphocytes into multiple organs and increased activity of autoantibodies to peripheral tissue antigens in a manner similar to that of autoimmune regulator-deficient (Aire-deficient) mice. We further demonstrated that NF-kappaB2 was required for thymic Aire gene transcriptional regulation. The Nfkb2(-/-) thymus had distinct cortical and medullar structures, but reduced Aire and target gene expression of peripheral tissue antigens. Engraftment of Nfkb2(-/-) thymic stroma to nude mice recapitulated the autoimmune phenotype of the native Nfkb2(-/-) mice, confirming a key defect in central tolerance. Lymphotoxin beta receptor (LTbetaR) ligation-induced Aire gene expression was also largely abolished in the absence of NF-kappaB2. Thus NF-kappaB2 downstream of LTbetaR plays an important role in the regulation of central tolerance in an Aire-dependent manner.

Head and neck cancer reirradiation with interstitial high-dose-rate brachytherapy.

BACKGROUND: As high-dose-rate (HDR) brachytherapy can preferentially spare normal anatomic structures surrounding the radiation target, we report on our experience using this technique in head and neck cancer reirradiation. METHODS: Twenty patients received HDR brachytherapy reirradiation with curative or palliative intent from 2010-2015. Clinical and toxicity outcomes were recorded. Actuarial outcomes were calculated using Kaplan-Meier analysis. RESULTS: For curative treatment, actuarial 2-year rates of local control and overall survival (OS) were 73% and 56%, respectively. Palliatively, a 6-month local control rate of 65% was seen. Age >70 years was associated with poorer OS (P = .042). Prior salvage resection showed a trend toward improved local control and OS (P = .069 and P = .063, respectively). Thirty-three percent had grade 3 to 4 late toxicities. CONCLUSION: Curative-intent HDR brachytherapy reirradiation can provide excellent local control and encouraging OS. Given the late toxicity rates, patient selection is essential, with particular utility for younger patients or those treated with salvage resection.

A Prospective 4π Radiation Therapy Clinical Study in Recurrent High-Grade Glioma Patients.

PURPOSE: To evaluate the feasibility, safety, dosimetric benefits, delivery efficiency, and patient comfort in the clinical implementation of 4π radiation therapy. METHODS AND MATERIALS: Eleven patients with recurrent high-grade glioma were recruited for the trial. 4π plans integrating beam orientation and fluence-map optimization were created using an in-house column-generation algorithm. The collision-free beam solution space throughout the 4π steradian was determined using a computer-aided-design model of the Varian TrueBeam system and a human subject. Twenty beams were optimized for each case and imported into Eclipse for intensity modulated radiation therapy planning. Beam orientations with neighboring couch kicks were merged for increased delivery efficiency, generating plans with an average of 16 beam orientations. Volumetric modulated arc therapy (VMAT) plans with 3-4 arcs were also generated for each case, and the plan achieving superior dosimetric quality was selected for treatment. Patient comfort was surveyed after every fraction. Multiple 2-dimensional X-ray images were obtained to measure intrafractional motion. RESULTS: Of 11 patients, 9 were treated with 4π. Mean and maximum organ at risk doses were equal or significantly lower (P < .05) with 4π than with VMAT. Particularly substantial dose reduction of 2.92 Gy in the average accumulated brainstem maximum dose enabled treatments that would otherwise not satisfy safe dose constraints with VMAT. One patient was not treated because neither plan met the dosimetric criteria. The other was treated with VMAT owing to comparable dosimetry resulting from a planning target volume located in a separate co-plane superior to organs at risk. Treatments were well tolerated, with an average patient comfort score of 8.6/10. Intrafractional motion was <1.5 mm for all delivered fractions, and the average delivery time was 34.1 minutes. CONCLUSIONS: The feasibility, safety, dosimetric benefits, delivery efficiency, and patient comfort of 4π radiation therapy have been clinically demonstrated with a prospective clinical trial. The results elucidate the potential and challenges of wider clinical implementations.

Differential regulation of CCL21 in lymphoid/nonlymphoid tissues for effectively attracting T cells to peripheral tissues.

CC chemokine ligand 21 (CCL21)/secondary lymphoid chemokine (SLC), a ligand for CC chemokine receptor 7 (CCR7), has been demonstrated to play a vital role in the homing and localization of immune cells to lymphoid tissues, but its role in nonlymphoid tissues largely remains undefined. Here, we provide evidence that CCL21 in lymphoid and nonlymphoid tissues is differentially regulated by lymphotoxin-dependent (LT-dependent) and -independent mechanisms, respectively. This differential regulation is due to the selective regulation of the CCL21-Ser/CCL21a but not the CCL21-Leu/CCL21b gene by the LT and noncanonical NF-kappaB pathways. This alternate pathway, not dependent on LT or lymphocytes, leading to constitutive expression of CCL21 in nonlymphoid tissues, is critical for the initial recruitment of T lymphocytes to peripheral effector sites. CCL21 expression is subsequently further enhanced in a LT-dependent fashion following airway challenge, potentially facilitating a positive feedback loop to attract additional CCR7+ effector cells. These findings establish an essential role for CCL21 in the recruitment of effector T cells to peripheral tissues and suggest that LT-dependent and -independent regulation of CCL21 plays a role in balancing the central and peripheral immune responses between lymphoid and nonlymphoid tissues.