Hybrid Tri-Co-60 MRI radiotherapy for locally advanced rectal cancer: An in silico evaluation

Radiomics-enhanced early regression index for predicting treatment response in rectal cancer: a multi-institutional 0.35 T MRI-guided radiotherapy study

PURPOSE

The accurate prediction of treatment response in locally advanced rectal cancer (LARC) patients undergoing MRI-guided radiotherapy (MRIgRT) is essential for optimising treatment strategies. This multi-institutional study aimed to investigate the potential of radiomics in enhancing the predictive power of a known radiobiological parameter (Early Regression Index, ERITCP) to evaluate treatment response in LARC patients treated with MRIgRT.

METHODS

Patients from three international sites were included and divided into training and validation sets. 0.35 T T2*/T1-weighted MR images were acquired during simulation and at each treatment fraction. The biologically effective dose (BED) conversion was used to account for different radiotherapy schemes: gross tumour volume was delineated on the MR images corresponding to specific BED levels and radiomic features were then extracted. Multiple logistic regression models were calculated, combining ERITCP with other radiomic features. The predictive performance of the different models was evaluated on both training and validation sets by calculating the receiver operating characteristic (ROC) curves.

RESULTS

A total of 91 patients was enrolled: 58 were used as training, 33 as validation. Overall, pCR was observed in 25 cases. The model showing the highest performance was obtained combining ERITCP at BED = 26 Gy with a radiomic feature (10th percentile of grey level histogram, 10GLH) calculated at BED = 40 Gy. The area under ROC curve (AUC) of this combined model was 0.98 for training set and 0.92 for validation set, significantly higher (p = 0.04) than the AUC value obtained using ERITCP alone (0.94 in training and 0.89 in validation set).

CONCLUSION

The integration of the radiomic analysis with ERITCP improves the pCR prediction in LARC patients, offering more precise predictive models to further personalise 0.35 T MRIgRT treatments of LARC patients.

Comparison of Prospectively Generated Glioma Treatment Plans Clinically Delivered on Magnetic Resonance Imaging (MRI)-Linear Accelerator (MR-Linac) Versus Conventional Linac: Predicted and Measured Skin Dose

Introduction: Magnetic resonance imaging-linear accelerator radiotherapy is an innovative technology that requires special consideration for secondary electron interactions within the magnetic field, which can alter dose deposition at air–tissue interfaces. As part of ongoing quality assurance and quality improvement of new radiotherapy technologies, the purpose of this study was to evaluate skin dose modelled from the treatment planning systems of a magnetic resonance imaging-linear accelerator and a conventional linear accelerator, and then correlate with in vivo measurements of delivered skin dose from each linear accelerator. Methods: In this prospective cohort study, 37 consecutive glioma patients had treatment planning completed and approved prior to radiotherapy initiation using commercial treatment planning systems: a Monte Carlo-based algorithm for magnetic resonance imaging-linear accelerator or a convolution-based algorithm for conventional linear accelerator. In vivo skin dose was measured using an optically stimulated luminescent dosimeter. Results: Monte Carlo-based magnetic resonance imaging-linear accelerator plans and convolution-based conventional linear accelerator plans had similar dosimetric parameters for target volumes and organs-at-risk. However, magnetic resonance imaging-linear accelerator plans had 1.52 Gy higher mean dose to air cavities (P < .0001) and 1.10 Gy higher mean dose to skin (P < .0001). In vivo skin dose was 14.5% greater for magnetic resonance imaging-linear accelerator treatments (P = .0027), and was more accurately predicted by Monte Carlo-based calculation (ρ = 0.95, P < .0001) versus convolution-based (ρ = 0.80, P = .0096). Conclusion: This is the first prospective dosimetric comparison of glioma patients clinically treated on both magnetic resonance imaging-linear accelerator and conventional linear accelerator. Our findings suggest that skin doses were significantly greater with magnetic resonance imaging-linear accelerator plans but correlated better with in vivo measurements of actual skin dose from delivered treatments. Future magnetic resonance imaging-linear accelerator planning processes are being designed to account for skin dosimetry and treatment delivery.

Delta radiomics for rectal cancer response prediction using low field magnetic resonance guided radiotherapy: an external validation

INTRODUCTION

A recent study performed on 16 locally advanced rectal cancer (LARC) patients treated using magnetic resonance guided radiotherapy (MRgRT) has identified two delta radiomics features as predictors of clinical complete response (cCR) after neoadjuvant radio-chemotherapy (nCRT). This study aims to validate these features (ΔL_least and Δglnu) on an external larger dataset, expanding the analysis also for pathological complete response (pCR) prediction.

METHODS

A total of 43 LARC patients were enrolled: Gross Tumour Volume (GTV) was delineated on T2/T1* MR images acquired during MRgRT and the two delta features were calculated. Receiver Operating Characteristic (ROC) curve analysis was performed on the 16 cases of the original study and the best cut-off value was identified. The performance of ΔL_least and Δglnu was evaluated at the best cut-off value.

RESULTS

On the original dataset of 16 patients, ΔL_least reported an AUC of 0.81 for cCR and 0.93 for pCR, while Δglnu 0.72 and 0.54 respectively. The best cut-off values of ΔL_least was 0.73 for both outcomes, while Δglnu reported 0.54 for cCR and 0.93 for pCR. At the external validation, ΔL_least showed an accuracy of 81% for cCR and 79% for pCR, while Δglnu reported 63% for cCR and 40% for pCR.

CONCLUSION

The accuracy of ΔL_least in predicting cCR and pCR is significantly higher than those obtained considering Δglnu, but inferior if compared with other image-based biomarker, such as the early-regression index. Studies with larger cohorts of patients are recommended to further investigate the role of delta radiomic features in MRgRT.

External Validation of Early Regression Index (ERITCP) as Predictor of Pathologic Complete Response in Rectal Cancer Using Magnetic Resonance-Guided Radiation Therapy

PURPOSE

Tumor control probability (TCP)-based early regression index (ERI_TCP) is a radiobiological parameter that showed promising results in predicting pathologic complete response (pCR) on T2-weighted 1.5 T magnetic resonance (MR) images of patients with locally advanced rectal cancer. This study aims to validate the ERI_TCP in the context of low-tesla MR-guided radiation therapy, using images acquired with different magnetic field strength (0.35 T) and image contrast (T2/T1). Furthermore, the optimal timing for pCR prediction was estimated, calculating the ERI index at different biologically effective dose (BED) levels.

METHODS AND MATERIALS

Fifty-two patients with locally advanced rectal cancer treated with neoadjuvant chemoradiation therapy were enrolled in this multi-institutional retrospective study. For each patient, a 0.35 T T2/T1-weighted MR image was acquired during simulation and on each treatment day. Gross tumor volume was contoured according to International Commission on Radiation Units Report 83 guidelines. According to the original definition, ERI_TCP was calculated considering the residual tumor volume at BED = 25 Gy. ERI was also calculated in correspondence with several BED levels: 13, 21, 32, 40, 46, 54, 59, and 67. The predictive performance of the different ERI indices were evaluated in terms of receiver operating characteristic curve. The robustness of ERI_TCP with respect to the interobserver variability was also evaluated considering 2 operators and calculating the intraclass correlation index.

RESULTS

Fourteen patients showed pCR. ERI_TCP correctly 47 of 52 cases (accuracy = 90%), showing good results in terms of sensitivity (86%), specificity (92%), negative predictive value (95%), and positive predictive value (80%). The analysis at different BED levels shows that the best predictive performance is obtained when this parameter is calculated at BED = 25 Gy (area under the curve = 0.93). ERI_TCP results are robust with respect to interobserver variability (intraclass correlation index = 0.99).

CONCLUSIONS

This study confirmed the validity and the robustness of ERI_TCP as a pCR predictor in the context of low-tesla MR-guided radiation therapy and indicate 25 Gy as the best BED level to perform predictions.

On-line adaptive MR guided radiotherapy for locally advanced pancreatic cancer: Clinical and dosimetric considerations

Introduction

Magnetic Resonance-guided Radiation Therapy (MRgRT) allows online adaptations (OA) of the treatment plan to optimize daily dose distribution based on patient's anatomy, just before fraction delivery. The aim of this study is to evaluate feasibility and the dosimetric improvement of the OA workflow implemented in our institution for locally advanced pancreatic cancer (LAPC) patients, in terms of target coverage and organs at risk (OARs) sparing.

Methods

We retrospectively analysed 8 LAPC patients treated with MRgRT in combination with the OA approach, using video-assisted inspiratory breath-hold for a total of 38 fractions with a dose ranging from 30 Gy to 40 Gy in 5 fractions.Dose distribution of the baseline plan was first calculated based on daily anatomy, obtaining a "predicted" plan to assess the dosimetric improvement. If the dose distribution did not meet the constraints set in the planning phase, PTV, GTV and OARs were re-contoured within a distance of 3 cm from the PTV external edge and a new online "adaptive" plan was generated. Other clinical and planning parameters were also evaluated to assess the feasibility and the dosimetic benefit of the online adaptive workflow.

Results

Out of 38 total fractions, 26 (68.4%) were adapted online and 12 (31.6%) were delivered using the baseline plan. The use of the adaptive workflow resulted to be feasible in our clinical practice and advantageous in all the patients: mean PTV V95% increased by 10.8% (5.7-20.8) while mean CTV V98% of 12.6% (7.3-17.7). Also OARs V33 and V25 showed a positive trend avoiding unnecessary irradiation.

Conclusion

OA workflow improves the dosimetric benefit of MRgRT, preventing the occurrence of high-doses to OARs and increasing the safety of stereotactic treatment for LAPC, without any drawback for our daily clinical practice routine.

Magnetic resonance-guided radiation therapy: A review

Magnetic resonance-guided radiation therapy (MRgRT) is a promising approach to improving clinical outcomes for patients treated with radiation therapy. The roles of image guidance, adaptive planning and magnetic resonance imaging in radiation therapy have been increasing over the last two decades. Technical advances have led to the feasible combination of magnetic resonance imaging and radiation therapy technologies, leading to improved soft-tissue visualisation, assessment of inter- and intrafraction motion, motion management, online adaptive radiation therapy and the incorporation of functional information into treatment. MRgRT can potentially transform radiation oncology by improving tumour control and quality of life after radiation therapy and increasing convenience of treatment by shortening treatment courses for patients. Multiple groups have developed clinical implementations of MRgRT predominantly in the abdomen and pelvis, with patients having been treated since 2014. While studies of MRgRT have primarily been dosimetric so far, an increasing number of trials are underway examining the potential clinical benefits of MRgRT, with coordinated efforts to rigorously evaluate the benefits of the promising technology. This review discusses the current implementations, studies, potential benefits and challenges of MRgRT.

Magnetic Resonance Guided Radiotherapy for Rectal Cancer: Expanding Opportunities for Non-Operative Management

Colorectal cancer is the third most common cancer in men and the second most common in women worldwide, and the incidence is increasing among younger patients. 30% of these malignancies arise in the rectum. Patients with rectal cancer have historically been managed with preoperative radiation, followed by radical surgery, and adjuvant chemotherapy, with permanent colostomies in up to 20% of patients. Beginning in the early 2000s, non-operative management (NOM) of rectal cancer emerged as a viable alternative to radical surgery in select patients. Efforts have been ongoing to optimize neoadjuvant therapy for rectal cancer, thereby increasing the number of patients potentially eligible to forgo radical surgery. Magnetic resonance guided radiotherapy (MRgRT) has recently emerged as a treatment modality capable of intensifying preoperative radiation therapy for rectal cancer patients. This technology may also predict which patients will achieve a complete response to preoperative therapy, thereby allowing for more appropriate selection of patients for NOM. The present work seeks to illustrate the potential role MRgRT could play in personalizing rectal cancer treatment thus expanding the role of NOM in rectal cancer.

MR-guided radiotherapy in rectal cancer: First clinical experience of an innovative technology

•This study represents one of the first reports of online MRgRT.•Integrated Low-field MR provides better anatomical visualization than CBCT or MVCT.•Better visualization of the target can help to reduce the margins from CTV to PTV.•MRgRT appears a feasible option in rectal cancer treatment offering potential benefits.•MRgRT represents a promising technology for rectal cancer management.

MR-guidance in clinical reality: current treatment challenges and future perspectives

Magnetic Resonance-guided radiotherapy (MRgRT) marks the beginning of a new era. MR is a versatile and suitable imaging modality for radiotherapy, as it enables direct visualization of the tumor and the surrounding organs at risk. Moreover, MRgRT provides real-time imaging to characterize and eventually track anatomical motion. Nevertheless, the successful translation of new technologies into clinical practice remains challenging. To date, the initial availability of next-generation hybrid MR-linac (MRL) systems is still limited and therefore, the focus of the present preview was on the initial applicability in current clinical practice and on future perspectives of this new technology for different treatment sites.MRgRT can be considered a groundbreaking new technology that is capable of creating new perspectives towards an individualized, patient-oriented planning and treatment approach, especially due to the ability to use daily online adaptation strategies. Furthermore, MRL systems overcome the limitations of conventional image-guided radiotherapy, especially in soft tissue, where target and organs at risk need accurate definition. Nevertheless, some concerns remain regarding the additional time needed to re-optimize dose distributions online, the reliability of the gating and tracking procedures and the interpretation of functional MR imaging markers and their potential changes during the course of treatment. Due to its continuous technological improvement and rapid clinical large-scale application in several anatomical settings, further studies may confirm the potential disruptive role of MRgRT in the evolving oncological environment.

Online adaptive magnetic resonance guided radiotherapy for pancreatic cancer: state of the art, pearls and pitfalls

BACKGROUND

Different studies have proved in recent years that hypofractionated radiotherapy (RT) improves overall survival of patients affected by locally advanced, unresectable, pancreatic cancer. The clinical management of these patients generally leads to poor results and is considered very challenging, due to different factors, heavily influencing treatment delivery and its outcomes. Firstly, the dose prescribed to the target is limited by the toxicity that the highly radio-sensitive organs at risk (OARs) surrounding the disease can develop. Treatment delivery is also complicated by the significant inter-fractional and intra-fractional variability of therapy volumes, mainly related to the presence of hollow organs and to the breathing cycle. The recent introduction of magnetic resonance guided radiotherapy (MRgRT) systems leads to the opportunity to control most of the aforementioned sources of uncertainty influencing RT treatment workflow in pancreatic cancer. MRgRT offers the possibility to accurately identify radiotherapy volumes, thanks to the high soft-tissue contrast provided by the Magnetic Resonance imaging (MRI), and to monitor the tumour and OARs positions during the treatment fraction using a high-temporal cine MRI. However, the main advantage offered by the MRgRT is the possibility to online adapt the RT treatment plan, changing the dose distribution while the patient is still on couch and successfully addressing most of the sources of variability.

SHORT CONCLUSION

Aim of this study is to present and discuss the state of the art, the main pitfalls and the innovative opportunities offered by online adaptive MRgRT in pancreatic cancer treatment.

Delta radiomics for rectal cancer response prediction with hybrid 0.35 T magnetic resonance-guided radiotherapy (MRgRT): a hypothesis-generating study for an innovative personalized medicine approach

The aim of this study was to evaluate the variation of radiomics features, defined as "delta radiomics", in patients undergoing neoadjuvant radiochemotherapy (RCT) for rectal cancer treated with hybrid magnetic resonance (MR)-guided radiotherapy (MRgRT). The delta radiomics features were then correlated with clinical complete response (cCR) outcome, to investigate their predictive power. A total of 16 patients were enrolled, and 5 patients (31%) showed cCR at restaging examinations. T2*/T1 MR images acquired with a hybrid 0.35 T MRgRT unit were considered for this analysis. An imaging acquisition protocol of 6 MR scans per patient was performed: the first MR was acquired at first simulation (t0) and the remaining ones at fractions 5, 10, 15, 20 and 25. Radiomics features were extracted from the gross tumour volume (GTV), and each feature was correlated with the corresponding delivered dose. The variations of each feature during treatment were quantified, and the ratio between the values calculated at different dose levels and the one extracted at t0 was calculated too. The Wilcoxon-Mann-Whitney test was performed to identify the features whose variation can be predictive of cCR, assessed with a MR acquired 6 weeks after RCT and digital examination. The most predictive feature ratios in cCR prediction were the L_least and glnu ones, calculated at the second week of treatment (22 Gy) with a p value = 0.001. Delta radiomics approach showed promising results and the quantitative analysis of images throughout MRgRT treatment can successfully predict cCR offering an innovative personalized medicine approach to rectal cancer treatment.