Radiotherapy quality assurance for the RTOG 0834/EORTC 26053-22054/NCIC CTG CEC.1/CATNON intergroup trial "concurrent and adjuvant temozolomide chemotherapy in newly diagnosed non-1p/19q deleted anaplastic glioma": Individual case review analysis

Essential requirements for reporting radiation therapy in breast cancer clinical trials: An international multi-disciplinary consensus endorsed by the European Society for Radiotherapy and Oncology (ESTRO)

The European Society for Radiotherapy and Oncology (ESTRO) has advocated the establishment of guidelines to optimise precision radiotherapy (RT) in conjunction with contemporary therapeutics for cancer care. Quality assurance in RT (QART) plays a pivotal role in influencing treatment outcomes. Clinical trials incorporating QART protocols have demonstrated improved survival rates with minimal associated toxicity. Nonetheless, in routine clinical practice, there can be variability in the indications for RT, dosage, fractionation, and treatment planning, leading to uncertainty. In pivotal trials reporting outcomes of systemic therapy for breast cancer, there is limited information available regarding RT, and the potential interaction between modern systemic therapy and RT remains largely uncharted. This article is grounded in a consensus recommendation endorsed by ESTRO, formulated by international breast cancer experts. The consensus was reached through a modified Delphi process and was presented at an international meeting convened in Florence, Italy, in June 2023. These recommendations are regarded as both optimal and essential standards, with the latter aiming to define the minimum requirements. A template for a case report form (CRF) has been devised, which can be utilised by all clinical breast cancer trials involving RT. Optimal requirements include adherence to predefined RT planning protocols and centralised QART. Essential requirements aim to reduce variations and deviations from the guidelines in RT, even when RT is not the primary focus of the trial. These recommendations underscore the significance of implementing these practices in both clinical trials and daily clinical routines to generate high-quality data.

Radiotherapy trial quality assurance processes: a systematic review

Quality assurance remains a neglected component of many trials, particularly for technical interventions, such as surgery and radiotherapy, for which quality of treatment is an important component in defining outcomes. We aimed to evaluate evidence for the processes used in radiotherapy quality assurance of clinical trials. A systematic review was undertaken focusing on use of a pre-trial outlining benchmark case and subsequent on-trial individual case reviews of outlining for recruited patients. These pre-trial and on-trial checks are used to ensure consistency and standardisation of treatment for each patient recruited to the trial by confirming protocol compliance. Non-adherence to the trial protocol has been shown to have a negative effect on trial outcomes. 29 studies published between January, 2000, and December, 2022, were identified that reported on either outlining benchmark case results or outlining individual case review results, or both. The trials identified varied in their use of radiotherapy quality assurance practices and reporting of outcomes was inconsistent. Deviations from trial protocols were frequent, particularly regarding outlining. Studies correlating benchmark case results with on-trial individual case reviews provided mixed results, meaning firm conclusions could not be drawn regarding the influence of the pre-trial benchmark case on subsequent on-trial performance. The optimal radiotherapy quality assurance processes were unclear, and there was little evidence available. Improved reporting of outcomes from radiotherapy quality assurance programmes is needed to develop an evidence base for the optimal approach to radiotherapy quality assurance in trials.

Optimising of axillary therapy in breast cancer: lessons from the past to plan for a better future

In this narrative review, we aim to explore the ability of radiation therapy to eradicate breast cancer regional node metastasis. It is a journey through data of older trials without systemic therapy showing the magnitude of axillary therapy (surgery versus radiation) on cancer control. Considering that both systemic and loco-regional therapies were shown to reduce any recurrence with a complex interaction, our review includes surgical, radiation, and radiobiology consideration for breast cancer, and provide our view of future practise. The aim is to provide information optimise radiation therapy in the era of primary systemic therapy.

The influence of anisotropy on the clinical target volume of brain tumor patients

Objective.Current radiotherapy guidelines for glioma target volume definition recommend a uniform margin expansion from the gross tumor volume (GTV) to the clinical target volume (CTV), assuming uniform infiltration in the invaded brain tissue. However, glioma cells migrate preferentially along white matter tracts, suggesting that white matter directionality should be considered in an anisotropic CTV expansion. We investigate two models of anisotropic CTV expansion and evaluate their clinical feasibility.Approach.To incorporate white matter directionality into the CTV, a diffusion tensor imaging (DTI) atlas is used. The DTI atlas consists of water diffusion tensors that are first spatially transformed into local tumor resistance tensors, also known as metric tensors, and secondly fed to a CTV expansion algorithm to generate anisotropic CTVs. Two models of spatial transformation are considered in the first step. The first model assumes that tumor cells experience reduced resistance parallel to the white matter fibers. The second model assumes that the anisotropy of tumor cell resistance is proportional to the anisotropy observed in DTI, with an 'anisotropy weighting parameter' controlling the proportionality. The models are evaluated in a cohort of ten brain tumor patients.Main results.To evaluate the sensitivity of the model, a library of model-generated CTVs was computed by varying the resistance and anisotropy parameters. Our results indicate that the resistance coefficient had the most significant effect on the global shape of the CTV expansion by redistributing the target volume from potentially less involved gray matter to white matter tissue. In addition, the anisotropy weighting parameter proved useful in locally increasing CTV expansion in regions characterized by strong tissue directionality, such as near the corpus callosum.Significance.By incorporating anisotropy into the CTV expansion, this study is a step toward an interactive CTV definition that can assist physicians in incorporating neuroanatomy into a clinically optimized CTV.

Deep-learning magnetic resonance imaging-based automatic segmentation for organs-at-risk in the brain: Accuracy and impact on dose distribution

Background and purpose

Normal tissue sparing in radiotherapy relies on proper delineation. While manual contouring is time consuming and subject to inter-observer variability, auto-contouring could optimize workflows and harmonize practice. We assessed the accuracy of a commercial, deep-learning, MRI-based tool for brain organs-at-risk delineation.

Materials and methods

Thirty adult brain tumor patients were retrospectively manually recontoured. Two additional structure sets were obtained: AI (artificial intelligence) and AIedit (manually corrected auto-contours). For 15 selected cases, identical plans were optimized for each structure set. We used Dice Similarity Coefficient (DSC) and mean surface-distance (MSD) for geometric comparison and gamma analysis and dose-volume-histogram comparison for dose metrics evaluation. Wilcoxon signed-ranks test was used for paired data, Spearman coefficient(ρ) for correlations and Bland-Altman plots to assess level of agreement.

Results

Auto-contouring was significantly faster than manual (1.1/20 min, p < 0.01). Median DSC and MSD were 0.7/0.9 mm for AI and 0.8/0.5 mm for AIedit. DSC was significantly correlated with structure size (ρ = 0.76, p < 0.01), with higher DSC for large structures. Median gamma pass rate was 74% (71-81%) for Plan_AI and 82% (75-86%) for Plan_AIedit, with no correlation with DSC or MSD. Differences between Dmean_AI and Dmean_Ref were ≤ 0.2 Gy (p < 0.05). The dose difference was moderately correlated with DSC. Bland Altman plot showed minimal discrepancy (0.1/0) between AI and reference Dmean/Dmax.

Conclusions

The AI-model showed good accuracy for large structures, but developments are required for smaller ones. Auto-segmentation was significantly faster, with minor differences in dose distribution caused by geometric variations.

Plan quality association between dummy run and individual case review in a prospective multi-institutional clinical trial of postoperative cervical cancer patients treated with intensity-modulated radiotherapy: Japan Clinical Oncology Group study (JCOG1402)

BACKGROUND AND PURPOSE

The Japan Clinical Oncology Group (JCOG) 1402 conducted a multicenter clinical trial of postoperative intensity-modulated radiotherapy (IMRT) for high-risk uterine cervical cancer patients. We assess effectiveness of the quality assurance (QA) program in central review through dummy runs (DRs) performed before patient enrollment and post-treatment individual case review (ICR), and clarify the pitfalls in treatment planning.

MATERIAL AND METHODS

The ICRs were conducted using the same QA program as the DR for 214 plans. The deviations were compared with those demonstrated in the DRs, and the pitfalls were clarified. Fifteen face-to-face meetings were held with physicians at participating institutions to provide feedback.

RESULTS

Two-hundred and eighty-nine deviations and nine violations were detected in the 214 plans. The patterns of the deviations observed in the ICRs were similar to that in the DR. Frequent deviations were observed in clinical target volume (CTV) delineations, 50% in the DRs and 35% in the ICRs, respectively. In the ICRs, approximately 1.4 deviations/violations were observed per plan, which was lower than DR. Nine violations included inaccurate CTV delineation and improper PTV (planning target volume) margin, which had risks in loco-regional failures by inadequate dose coverage.

CONCLUSIONS

Our developed QA program commonly used in DR and ICR clarified the pitfalls in treatment plans. Although the frequent deviations in CTV delineations were observed in the ICR, the deviations decreased compared to that in the DR. More specified face-to-face meetings with participating institutions will be necessary to maintain the quality of IMRT in the clinical protocol.

TRIAL REGISTRATION

Japanese Clinical Trial Registry #: UMIN000027017 at https://upload.umin.ac.jp/cgi-open-bin/ctr/ctr_view.cgi?recptno=R000030672;language=J.

Types of deviation and review criteria in pretreatment central quality control of tumor bed boost in medulloblastoma-an analysis of the German Radiotherapy Quality Control Panel in the SIOP PNET5 MB trial

Purpose

In Germany, Austria, and Switzerland, pretreatment radiotherapy quality control (RT-QC) for tumor bed boost (TB) in non-metastatic medulloblastoma (MB) was not mandatory but was recommended for patients enrolled in the SIOP PNET5 MB trial between 2014 and 2018. This individual case review (ICR) analysis aimed to evaluate types of deviations in the initial plan proposals and develop uniform review criteria for TB boost.

Patients and methods

A total of 78 patients were registered in this trial, of whom a subgroup of 65 patients were available for evaluation of the TB treatment plans. Dose uniformity was evaluated according to the definitions of the protocol. Additional RT-QC criteria for standardized review of target contours were elaborated and data evaluated accordingly.

Results

Of 65 initial TB plan proposals, 27 (41.5%) revealed deviations of target volume delineation. Deviations according to the dose uniformity criteria were present in 14 (21.5%) TB plans. In 25 (38.5%) cases a modification of the RT plan was recommended. Rejection of the TB plans was rather related to unacceptable target volume delineation than to insufficient dose uniformity.

Conclusion

In this analysis of pretreatment RT-QC, protocol deviations were present in a high proportion of initial TB plan proposals. These findings emphasize the importance of pretreatment RT-QC in clinical trials for MB. Based on these data, a proposal for RT-QC criteria for tumor bed boost in non-metastatic MB was developed.

Supplementary Information

The online version of this article (10.1007/s00066-021-01822-0) contains supplementary material, which is available to authorized users.

Analyzing magnetic resonance imaging data from glioma patients using deep learning

The quantitative analysis of images acquired in the diagnosis and treatment of patients with brain tumors has seen a significant rise in the clinical use of computational tools. The underlying technology to the vast majority of these tools are machine learning methods and, in particular, deep learning algorithms. This review offers clinical background information of key diagnostic biomarkers in the diagnosis of glioma, the most common primary brain tumor. It offers an overview of publicly available resources and datasets for developing new computational tools and image biomarkers, with emphasis on those related to the Multimodal Brain Tumor Segmentation (BraTS) Challenge. We further offer an overview of the state-of-the-art methods in glioma image segmentation, again with an emphasis on publicly available tools and deep learning algorithms that emerged in the context of the BraTS challenge.

Cranial organs at risk delineation: heterogenous practices in radiotherapy planning

BACKGROUND

Segmentation is a crucial step in treatment planning that directly impacts dose distribution and optimization. The aim of this study was to evaluate the inter-individual variability of common cranial organs at risk (OAR) delineation in neurooncology practice.

METHODS

Anonymized simulation contrast-enhanced CT and MR scans of one patient with a solitary brain metastasis was used for delineation and analysis. Expert professionals from 16 radiotherapy centers involved in brain structures delineation were asked to segment 9 OAR on their own treatment planning system. As reference, two experts in neurooncology, produced a unique consensual contour set according to guidelines. Overlap ratio, Kappa index (KI), volumetric ratio, Commonly Contoured Volume, Supplementary Contoured Volume were evaluated using Artiview™ v 2.8.2-according to occupation, seniority and level of expertise of all participants.

RESULTS

For the most frequently delineated and largest OAR, the mean KI are often good (0.8 for the parotid and the brainstem); however, for the smaller OAR, KI degrade (0.3 for the optic chiasm, 0.5% for the cochlea), with a significant discrimination (p < 0.01). The radiation oncologists, members of Association des Neuro-Oncologue d'Expression Française society performed better in all indicators compared to non-members (p < 0.01). Our exercise was effective in separating the different participating centers with 3 of the reported indicators (p < 0.01).

CONCLUSION

Our study illustrates the heterogeneity in normal structures contouring between professionals. We emphasize the need for cerebral OAR delineation harmonization-that is a major determinant of therapeutic ratio and clinical trials evaluation.

An MRI-based radiomics signature as a pretreatment noninvasive predictor of overall survival and chemotherapeutic benefits in lower-grade gliomas

OBJECTIVES

The aim of this study was to develop and validate a radiomics signature for predicting survival and chemotherapeutic benefits of patients with lower-grade gliomas (LGG).

METHODS

Radiomics features were extracted from precontrast axial fluid-attenuated inversion recovery (FLAIR) and contrast-enhanced axial T-1 weighted (CE-T1-w) sequence. Lasso Cox regression model was used for feature selection and radiomics signature building. The radiomics signature was developed in a primary cohort that consisted of 149 LGG patients and was then validated on an entirely new validation cohort that contained 66 LGG patients. A radiomics nomogram for the prediction of OS was established by adding the radiomics to clinicopathologic nomogram which developed with clinical data.

RESULTS

A radiomics signature derived from joint CE-T1-w and FLAIR images showed better prognostic performance (C-index, 0.798) than signatures derived from CE-T1-w (C-index, 0.744) or FLAIR (C-index, 0.736) sequences alone. Multivariable Cox regression revealed that the radiomics signature was an independent prognostic factor. One radiomics nomogram integrated the radiomics signature from joint CE-T1-w and FLAIR sequences with the clinicopathologic nomogram outperformed the clinicopathologic nomogram based on clinicopathologic data alone in predicting OS of LGG (C-index, 0.821 vs. 0.692; p < 0.001). Further analysis revealed that patients with higher radiomics signature were prone to benefit from chemotherapy.

CONCLUSIONS

The radiomics signature was independent with clinicopathologic data and was a noninvasive pretreatment predictor for LGG patients' survival. Moreover, it could predict which patients with LGG benefit from chemotherapy.

KEY POINTS

• A radiomics signature derived from joint CE-T1-w and FLAIR sequences showed better prognostic performance than signatures derived from either single imaging modality. • The radiomics signature is an independent prognostic factor and outperformed clinicopathologic features in predicting overall survival of LGG patients. • The radiomics signature could help preoperatively identify LGG patients who may benefit from chemotherapy.

Dummy-run for standardizing plan quality of intensity-modulated radiotherapy for postoperative uterine cervical cancer: Japan Clinical Oncology Group study (JCOG1402)

BACKGROUND

The purpose of this study was to assess compliance with treatment planning in a dummy-run for a multicenter clinical trial involving patients with high-risk postoperative uterine cervical cancer using intensity-modulated radiation therapy (IMRT) (JCOG1402 trial).

METHODS

For the dummy-run, we prepared a computed tomography dataset comprising two anonymized cases of post-hysterectomy cervical cancer. These were sent to the 47 participating institutions to assess institutional plan quality such as delineations and dose distributions.

RESULTS

Central review showed 3 and 4 deviations per treatment plan on average. The deviations related to the nodal and vaginal cuff clinical target volume (CTV) delineation, which accounted for approximately 50% of the total deviations. The CTV vaginal cuff showed considerable differences in delineation compared with the nodal CTV. For the Dice similarity coefficient, case 1 showed a mean ± 1σ of 0.81 ± 0.03 and 0.60 ± 0.09 for the nodal and the CTV vaginal cuff, respectively, while these were 0.81 ± 0.04 and 0.54 ± 0.14, respectively, for case two. Of the 47 institutions, 10 were required to resubmit their treatment plan because the delineations, planning target volume margin, and required dose distributions were not in accordance with the JCOG1402 protocol.

CONCLUSIONS

The dummy-run test in postoperative uterine cervical cancer demonstrated substantial deviations in the delineations, particularly for the CTV vaginal cuff. The analysis data could provide helpful information on delineation and planning, allowing standardization of IMRT planning for postoperative uterine cervical cancer.

TRIAL REGISTRATION

Japanese Clinical Trial Registry #: UMIN000027017 at https://upload.umin.ac.jp/cgi-open-bin/ctr/ctr_view.cgi?recptno=R000030672;language=J.

Downregulation of microRNA-374a predicts poor prognosis in human glioma

Certain microRNAs (miRNAs/miRs) may be used as prognostic biomarkers in various types of cancer. The purpose of the present study was to identify miRNAs that were abnormally expressed in glioma of different grades, and to evaluate their clinical implications in patients with glioma. The differentially expressed miRNAs were evaluated from the expression profiles of six glioma tissues (three low-grade and three high-grade gliomas) determined using a microarray platform. Reverse transcription-quantitative polymerase chain reaction analysis was used to further verify the aberrant expression of the candidate miRNA in a set of 42 patients and 5 healthy controls. The miRNA target genes were predicted and the protein-protein interaction network was generated; furthermore, functional enrichment analysis of the target genes in Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways was performed. Kaplan-Meier curves and Log-rank analysis, as well as multivariate Cox regression analysis were performed to assess the association of the candidate miRNA with patient survival. A total of 15 differentially expressed miRNAs, including 13 downregulated and 2 upregulated miRNAs, were identified by comparison of low-grade and high-grade glioma tissues. The miR-374a expression of high-grade gliomas was significantly lower than that of low-grade gliomas (fold change, -4.43; P=0.027). The expression levels of miR-374a gradually decreased with the increase of the pathological grade of glioma. Pearson's Chi-square test was used to determine the association of miR-374a expression with several clinicopathological factors. Furthermore, low expression of miR-374a was determined to be an independent prognostic marker and that it was significantly associated with overall survival (P=0.0213). GO and KEGG pathway analysis revealed that the target genes of miR-374a may be involved in the regulation of the RNA polymerase II promoter and mTOR signaling pathway. The four hub genes (CCND1, SP1, CDK4, CDK6) were also identified by PPI network analysis. In conclusion, the present study indicated that miR-374a may be used as a promising prognostic biomarker for the screening of high-risk populations and for the assessment of the prognosis of patients with glioma.