MRI-guided adaptive radiotherapy for liver tumours: visualising the future

Optimizing diagnosis and surgical decisions for chronic osteomyelitis through radiomics in the precision medicine era

Introduction: Chronic osteomyelitis is a complex clinical condition that is associated with a high recurrence rate. Traditional surgical interventions often face challenges in achieving a balance between thorough debridement and managing resultant bone defects. Radiomics is an emerging technique that extracts quantitative features from medical images to reveal pathological information imperceptible to the naked eye. This study aims to investigate the potential of radiomics in optimizing osteomyelitis diagnosis and surgical treatment. Methods: Magnetic resonance imaging (MRI) scans of 93 suspected osteomyelitis patients were analyzed. Radiomics features were extracted from the original lesion region of interest (ROI) and an expanded ROI delineated by enlarging the original by 5 mm. Feature selection was performed and support vector machine (SVM) models were developed using the two ROI datasets. To assess the diagnostic efficacy of the established models, we conducted receiver operating characteristic (ROC) curve analysis, employing histopathological results as the reference standard. The model's performance was evaluated by calculating the area under the curve (AUC), sensitivity, specificity, and accuracy. Discrepancies in the ROC between the two models were evaluated using the DeLong method. All statistical analyses were carried out using Python, and a significance threshold of p < 0.05 was employed to determine statistical significance. Results and Discussion: A total of 1,037 radiomics features were extracted from each ROI. The expanded ROI model achieved significantly higher accuracy (0.894 vs. 0.821), sensitivity (0.947 vs. 0.857), specificity (0.842 vs. 0.785) and AUC (0.920 vs. 0.859) than the original ROI model. Key discriminative features included shape metrics and wavelet-filtered texture features. Radiomics analysis of MRI exhibits promising clinical translational potential in enhancing the diagnosis of chronic osteomyelitis by accurately delineating lesions and identifying surgical margins. The inclusion of an expanded ROI that encompasses perilesional tissue significantly improves diagnostic performance compared to solely focusing on the lesions. This study provides clinicians with a more precise and effective tool for diagnosis and surgical decision-making, ultimately leading to improved outcomes in this patient population.

Whole-body magnetic resonance imaging at 0.05 Tesla

Despite a half-century of advancements, global magnetic resonance imaging (MRI) accessibility remains limited and uneven, hindering its full potential in health care. Initially, MRI development focused on low fields around 0.05 Tesla, but progress halted after the introduction of the 1.5 Tesla whole-body superconducting scanner in 1983. Using a permanent 0.05 Tesla magnet and deep learning for electromagnetic interference elimination, we developed a whole-body scanner that operates using a standard wall power outlet and without radiofrequency and magnetic shielding. We demonstrated its wide-ranging applicability for imaging various anatomical structures. Furthermore, we developed three-dimensional deep learning reconstruction to boost image quality by harnessing extensive high-field MRI data. These advances pave the way for affordable deep learning-powered ultra-low-field MRI scanners, addressing unmet clinical needs in diverse health care settings worldwide.

Markerless liver online adaptive stereotactic radiotherapy: feasibility analysisCervantes

Objective. Radio-opaque markers are recommended for image-guided radiotherapy in liver stereotactic ablative radiotherapy (SABR), but their implantation is invasive. We evaluate in thisin-silicostudy the feasibility of cone-beam computed tomography-guided stereotactic online-adaptive radiotherapy (CBCT-STAR) to propagate the target volumes without implanting radio-opaque markers and assess its consequence on the margin that should be used in that context.Approach. An emulator of a CBCT-STAR-dedicated treatment planning system was used to generate plans for 32 liver SABR patients. Three target volume propagation strategies were compared, analysing the volume difference between the GTVPropagatedand the GTVConventional, the vector lengths between their centres of mass (lCoM), and the 95th percentile of the Hausdorff distance between these two volumes (HD95). These propagation strategies were: (1) structure-guided deformable registration with deformable GTV propagation; (2) rigid registration with rigid GTV propagation; and (3) image-guided deformable registration with rigid GTV propagation. Adaptive margin calculation integrated propagation errors, while interfraction position errors were removed. Scheduled plans (PlanNon-adaptive) and daily-adapted plans (PlanAdaptive) were compared for each treatment fraction.Main results.The image-guided deformable registration with rigid GTV propagation was the best propagation strategy regarding tolCoM(mean: 4.3 +/- 2.1 mm), HD95 (mean 4.8 +/- 3.2 mm) and volume preservation between GTVPropagatedand GTVConventional. This resulted in a planning target volume (PTV) margin increase (+69.1% in volume on average). Online adaptation (PlanAdaptive) reduced the violation rate of the most important dose constraints ('priority 1 constraints', 4.2 versus 0.9%, respectively;p< 0.001) and even improved target volume coverage compared to non-adaptive plans (PlanNon-adaptive).Significance. Markerless CBCT-STAR for liver tumours is feasible using Image-guided deformable registration with rigid GTV propagation. Despite the cost in terms of PTV volumes, daily adaptation reduces constraints violation and restores target volumes coverage.

3D cine-magnetic resonance imaging using spatial and temporal implicit neural representation learning (STINR-MR)

Objective. 3D cine-magnetic resonance imaging (cine-MRI) can capture images of the human body volume with high spatial and temporal resolutions to study anatomical dynamics. However, the reconstruction of 3D cine-MRI is challenged by highly under-sampled k-space data in each dynamic (cine) frame, due to the slow speed of MR signal acquisition. We proposed a machine learning-based framework, spatial and temporal implicit neural representation learning (STINR-MR), for accurate 3D cine-MRI reconstruction from highly under-sampled data.Approach. STINR-MR used a joint reconstruction and deformable registration approach to achieve a high acceleration factor for cine volumetric imaging. It addressed the ill-posed spatiotemporal reconstruction problem by solving a reference-frame 3D MR image and a corresponding motion model that deforms the reference frame to each cine frame. The reference-frame 3D MR image was reconstructed as a spatial implicit neural representation (INR) network, which learns the mapping from input 3D spatial coordinates to corresponding MR values. The dynamic motion model was constructed via a temporal INR, as well as basis deformation vector fields (DVFs) extracted from prior/onboard 4D-MRIs using principal component analysis. The learned temporal INR encodes input time points and outputs corresponding weighting factors to combine the basis DVFs into time-resolved motion fields that represent cine-frame-specific dynamics. STINR-MR was evaluated using MR data simulated from the 4D extended cardiac-torso (XCAT) digital phantom, as well as two MR datasets acquired clinically from human subjects. Its reconstruction accuracy was also compared with that of the model-based non-rigid motion estimation method (MR-MOTUS) and a deep learning-based method (TEMPEST).Main results. STINR-MR can reconstruct 3D cine-MR images with high temporal (<100 ms) and spatial (3 mm) resolutions. Compared with MR-MOTUS and TEMPEST, STINR-MR consistently reconstructed images with better image quality and fewer artifacts and achieved superior tumor localization accuracy via the solved dynamic DVFs. For the XCAT study, STINR reconstructed the tumors to a mean ± SD center-of-mass error of 0.9 ± 0.4 mm, compared to 3.4 ± 1.0 mm of the MR-MOTUS method. The high-frame-rate reconstruction capability of STINR-MR allows different irregular motion patterns to be accurately captured.Significance. STINR-MR provides a lightweight and efficient framework for accurate 3D cine-MRI reconstruction. It is a 'one-shot' method that does not require external data for pre-training, allowing it to avoid generalizability issues typically encountered in deep learning-based methods.

Roseburia intestinalis sensitizes colorectal cancer to radiotherapy through the butyrate/OR51E1/RALB axis

The radioresistant signature of colorectal cancer (CRC) hampers the clinical utility of radiotherapy. Here, we find that fecal microbiota transplantation (FMT) potentiates the tumoricidal effects of radiation and degrades the intertwined adverse events in azoxymethane (AOM)/dextran sodium sulfate (DSS)-induced CRC mice. FMT cumulates Roseburia intestinalis (R. intestinalis) in the gastrointestinal tract. Oral gavage of R. intestinalis assembles at the CRC site and synthetizes butyrate, sensitizing CRC to radiation and alleviating intestinal toxicity in primary and CRC hepatic metastasis mouse models. R. intestinalis-derived butyrate activates OR51E1, a G-protein-coupled receptor overexpressing in patients with rectal cancer, facilitating radiogenic autophagy in CRC cells. OR51E1 shows a positive correlation with RALB in clinical rectal cancer tissues and CRC mouse model. Blockage of OR51E1/RALB signaling restrains butyrate-elicited autophagy in irradiated CRC cells. Our findings highlight that the gut commensal bacteria R. intestinalis motivates radiation-induced autophagy to accelerate CRC cell death through the butyrate/OR51E1/RALB axis and provide a promising radiosensitizer for CRC in a pre-clinical setting.

Channel-wise attention enhanced and structural similarity constrained cycleGAN for effective synthetic CT generation from head and neck MRI images

BACKGROUND

Magnetic resonance imaging (MRI) plays an increasingly important role in radiotherapy, enhancing the accuracy of target and organs at risk delineation, but the absence of electron density information limits its further clinical application. Therefore, the aim of this study is to develop and evaluate a novel unsupervised network (cycleSimulationGAN) for unpaired MR-to-CT synthesis.

METHODS

The proposed cycleSimulationGAN in this work integrates contour consistency loss function and channel-wise attention mechanism to synthesize high-quality CT-like images. Specially, the proposed cycleSimulationGAN constrains the structural similarity between the synthetic and input images for better structural retention characteristics. Additionally, we propose to equip a novel channel-wise attention mechanism based on the traditional generator of GAN to enhance the feature representation capability of deep network and extract more effective features. The mean absolute error (MAE) of Hounsfield Units (HU), peak signal-to-noise ratio (PSNR), root-mean-square error (RMSE) and structural similarity index (SSIM) were calculated between synthetic CT (sCT) and ground truth (GT) CT images to quantify the overall sCT performance.

RESULTS

One hundred and sixty nasopharyngeal carcinoma (NPC) patients who underwent volumetric-modulated arc radiotherapy (VMAT) were enrolled in this study. The generated sCT of our method were more consistent with the GT compared with other methods in terms of visual inspection. The average MAE, RMSE, PSNR, and SSIM calculated over twenty patients were 61.88 ± 1.42, 116.85 ± 3.42, 36.23 ± 0.52 and 0.985 ± 0.002 for the proposed method. The four image quality assessment metrics were significantly improved by our approach compared to conventional cycleGAN, the proposed cycleSimulationGAN produces significantly better synthetic results except for SSIM in bone.

CONCLUSIONS

We developed a novel cycleSimulationGAN model that can effectively create sCT images, making them comparable to GT images, which could potentially benefit the MRI-based treatment planning.

Do We Have a Winner? Advocating for SBRT in HCC Management

•Stereotactic body radiotherapy (SBRT) is a safe and effective locoregional therapy for inoperable patients with HCC.•SBRT compares favorably with other local therapies in terms of local control, survival, morbidity, and cost-effectiveness.•SBRT should be considered and discussed in multidisciplinary management of appropriate HCC patients.•Advances in SBRT and novel combinations with systemic therapy may further widen the therapeutic index in HCC.

SBRT for Liver Tumors: What the Interventional Radiologist Needs to Know

This review summarizes the clinical evidence supporting the utilization of stereotactic body radiotherapy (SBRT) for liver tumors, including hepatocellular carcinoma, liver metastases, and cholangiocarcinoma. Emerging prospective evidence has demonstrated the benefit and low rates of toxicity across a broad range of clinical contexts. We provide an introduction for the interventional radiologist, with a discussion of underlying themes such as tumor dose-response, mitigation of liver toxicity, and the technical considerations relevant to performing liver SBRT. Ultimately, we recommend that SBRT should be routinely included in the armamentarium of locoregional therapies for liver malignancies, alongside those liver-directed therapies offered by interventional radiology.

MR-LINAC, a New Partner in Radiation Oncology: Current Landscape

Technological advances in radiation oncology are oriented towards improving treatment precision and tumor control. Among these advances, magnetic-resonance-image-guided radiation therapy (MRgRT) stands out, with technological advances to deliver targeted treatments adapted to a tumor's anatomy on the day while minimizing incidental exposure to organs at risk, offering an unprecedented therapeutic advantage compared to X-ray-based IGRT delivery systems. This new technology changes the traditional workflow in radiation oncology and requires an evolution in team coordination to administer more precise treatments. Once implemented, it paves the way for newer indication for radiation therapy to safely deliver higher doses than ever before, with better preservation of healthy tissues to optimize patient outcomes. In this narrative review, we assess the technical aspects of the novel linear accelerators that can deliver MRgRT and summarize the available published experience to date, focusing on oncological results and future challenges.

Transcatheter Arterial Chemoembolization Imaging Features in MR-Linac Radiation Therapy Planning for the Liver

For MR-guided radiation therapy treatment planning, an MRI and CT of the intended treatment site are typically acquired. Patients' prior treatments or procedures can cause image artifacts in one or both scans, which may impact treatment planning or the radiation dose calculation. In this case report, a patient with several previous transcatheter arterial chemoembolization (TACE) procedures was planned for radiation therapy on a low-field MR-linac, and the impact of residual iodinated oil on the radiation dose calculation and MR-guided adaptive workflow was evaluated.

Why we should care about gas pockets in online adaptive MRgRT: a dosimetric evaluation

Introduction

Contouring of gas pockets is a time consuming step in the workflow of adaptive radiotherapy. We would like to better understand which gas pockets electronic densitiy should be used and the dosimetric impact on adaptive MRgRT treatment.

Materials and methods

21 CT scans of patients undergoing SBRT were retrospectively evaluated. Anatomical structures were contoured: Gross Tumour Volume (GTV), stomach (ST), small bowel (SB), large bowel (LB), gas pockets (GAS) and gas in each organ respectively STG, SBG, LBG. Average HU in GAS was converted in RED, the obtained value has been named as Gastrointestinal Gas RED (GIGED). Differences of average HU in GAS, STG, SBG and LBG were computed. Three treatment plans were calculated editing the GAS volume RED that was overwritten with: air RED (0.0012), water RED (1.000), GIGED, generating respectively APLAN, WPLAN and the GPLAN. 2-D dose distributions were analyzed by gamma analysis. Parameter called active gas volume (AGV) was calculated as the intersection of GAS with the isodose of 5% of prescription dose.

Results

Average HU value contained in GAS results to be equal to -620. No significative difference was noted between the average HU of gas in different organ at risk. Value of Gamma Passing Rate (GPR) anticorrelates with the AGV for each plan comparison and the threshold value for GPR to fall below 90% is 41, 60 and 139 cc for WPLANvsAPLAN, GPLANvsAPLAN and WPLANvsGPLAN respectively.

Discussions

GIGED is the right RED for Gastrointestinal Gas. Novel AGV is a useful parameter to evaluate the effect of gas pocket on dose distribution.

JMJD6-BRD4 complex stimulates lncRNA HOTAIR transcription by binding to the promoter region of HOTAIR and induces radioresistance in liver cancer stem cells

BACKGROUND

Long non-coding RNA (lncRNA) HOTAIR acts importantly in liver cancer development, but its effect on radioresistance remains poorly understood. Here, our study probed into the possible impact of HOTAIR in radioresistance in liver cancer stem cells (LCSCs) and to elucidate its molecular basis.

METHODS

Following sorting of stem and non-stem liver cancer cells, LCSCs were identified and subjected to RNA-seq analysis for selecting differentially expressed genes. Expression of HOTAIR was determined in liver cancer tissues and CSCs. The stemness, proliferation, apoptosis and radioresistance of LCSCs were then detected in response to altered expression of HOTAIR-LSD1-JMJD6-BRD4.

RESULTS

Ectopic HOTAIR expression was found to promote radioresistance of LCSCs by maintaining its stemness. Mechanistic investigations indicated that HOTAIR recruited LSD1 to the MAPK1 promoter region and reduced the level of H3K9me2 in the promoter region, thus elevating ERK2 (MAPK1) expression. JMJD6-BRD4 complex promoted HOTAIR transcription by forming a complex and positively regulated ERK2 (MAPK1) expression, maintaining the stemness of LCSCs, and ultimately promoting their radioresistance in vitro and in vivo.

CONCLUSION

Collectively, our work highlights the promoting effect of the JMJD6-BRD4 complex on the radioresistance of LCSCs through a HOTAIR-dependent mechanism.

Local Control Following Stereotactic Body Radiation Therapy for Liver Oligometastases: Lessons from a Quarter Century

The utilization of stereotactic body radiation therapy for the treatment of liver metastasis has been widely studied and has demonstrated favorable local control outcomes. However, several predictive factors play a crucial role in the efficacy of stereotactic body radiation therapy, such as the number and size (volume) of metastatic liver lesions, the primary tumor site (histology), molecular biomarkers (e.g., KRAS and TP53 mutation), the use of systemic therapy prior to SBRT, the radiation dose, and the use of advanced technology and organ motion management during SBRT. These prognostic factors need to be considered when clinical trials are designed to evaluate the efficacy of SBRT for liver metastases.

Case Report: MR-LINAC-guided adaptive radiotherapy for gastric cancer

Background

The stomach is one of the most deformable organs. Its shape can be easily affected by breathing movements, and daily diet, and it also varies when the body position is different. The susceptibility of stomach has made it challenging to treat gastric cancer using the conventional image-guided radiotherapy, i.e., the techniques based on kilovoltage X-ray imaging. The magnetic resonance imaging guided radiotherapy (MRgRT) is usually implemented using a hybrid system MR-LINAC. It is feasible to implement adaptive radiotherapy using MR-LINAC for deformable organs such as stomach. In this case report, we present our clinical experience to treat a gastric cancer patient using MR-LINAC.

Case description

The patient is a 58-year-old male who started having black stools with no apparent cause a year ago. Gastroscopy result showed pancreatic cancer, pathology: adenocarcinoma on gastric cancer biopsy, adenocarcinoma on gastric body minor curvature biopsy. The patient was diagnosed with gastric cancer (adenocarcinoma, cTxN+M1, stage IV, HER-2 positive). The patient was treated in 25 fractions with radiotherapy using MR-LINAC with online adaptive treatment plans daily. The target area in daily MR images varied considerably when compared with the target area on the CT simulation images. During the course of treatment, there have even been instances where the planned target area where the patient received radiotherapy did not cover the lesion of the day.

Conclusion

Online adaptive MRgRT can be a meaningful innovation for treating malignancies in the upper abdomen. The results in the current study are promising and are indicative for further optimizing online adaptive MRgRT in patients with inoperable tumors of the upper abdomen.

Multi-parametric MRI for radiotherapy simulation

Magnetic resonance imaging (MRI) has become an important imaging modality in the field of radiotherapy (RT) in the past decade, especially with the development of various novel MRI and image-guidance techniques. In this review article, we will describe recent developments and discuss the applications of multi-parametric MRI (mpMRI) in RT simulation. In this review, mpMRI refers to a general and loose definition which includes various multi-contrast MRI techniques. Specifically, we will focus on the implementation, challenges, and future directions of mpMRI techniques for RT simulation.

Clinical outcomes of patients with unresectable primary liver cancer treated with MR-guided stereotactic body radiation Therapy: A Six-Year experience

Purpose

Magnetic resonance-guided stereotactic body radiation therapy (MRgSBRT) with optional online adaptation has shown promise in delivering ablative doses to unresectable primary liver cancer. However, there remain limited data on the indications for online adaptation as well as dosimetric and longer-term clinical outcomes following MRgSBRT.

Methods and Materials

Patients with unresectable hepatocellular carcinoma (HCC), cholangiocarcinoma (CCA), and combined biphenotypic hepatocellular-cholangiocarcinoma (cHCC-CCA) who completed MRgSBRT to 50 Gy in 5 fractions between June of 2015 and December of 2021 were analyzed. The necessity of adaptive techniques was evaluated. The cumulative incidence of local progression was evaluated and survival and competing risk analyses were performed.

Results

Ninety-nine analyzable patients completed MRgSBRT during the study period and 54 % had planning target volumes (PTVs) within 1 cm of the duodenum, small bowel, or stomach at the time of simulation. Online adaptive RT was used in 53 % of patients to correct organ-at-risk constraint violation and/or to improve target coverage. In patients who underwent adaptive RT planning, online replanning resulted in superior target coverage when compared to projected, non-adaptive plans (median coverage ≥ 95 % at 47.5 Gy: 91 % [IQR: 82-96] before adaptation vs 95 % [IQR: 87-99] after adaptation, p < 0.01). The median follow-up for surviving patients was 34.2 months for patients with HCC and 10.1 months for patients with CCA/cHCC-CCA. For all patients, the 2-year cumulative incidence of local progression was 9.8 % (95 % CI: 1.5-18 %) for patients with HCC and 9.0 % (95 % CI: 0.1-18) for patients with CCA/cHCC-CCA. Grade 3 through 5 acute and late clinical gastrointestinal toxicities were observed in < 10 % of the patients.

Conclusions

MRgSBRT, with the option for online adaptive planning when merited, allows delivery of ablative doses to primary liver tumors with excellent local control with acceptable toxicities. Additional studies evaluating the efficacy and safety of MRgSBRT in the treatment of primary liver cancer are warranted.

Advances in MRI-Guided Radiation Therapy

Image guidance for radiation therapy (RT) has evolved over the last few decades and now is routinely performed using cone-beam computerized tomography (CBCT). Conventional linear accelerators (LINACs) that use CBCT have limited soft tissue contrast, are not able to image the patient's internal anatomy during treatment delivery, and most are not capable of online adaptive replanning. RT delivery systems that use MRI have become available within the last several years and address many of the imaging limitations of conventional LINACs. Herein, the authors review the technical characteristics and advantages of MRI-guided RT as well as emerging clinical outcomes.

The Role of Stereotactic Body Radiation Therapy in the Management of Liver Metastases

The liver is a common site for metastatic spread for various primary tumor histologies. Stereotactic body radiation therapy (SBRT) is a non-invasive treatment technique with broad patient candidacy for the ablation of tumors in the liver and other organs. SBRT involves focused, high-dose radiation therapy delivered in one to several treatments, resulting in high rates of local control. Use of SBRT for ablation of oligometastatic disease has increased in recent years and emerging prospective data have demonstrated improvements in progression free and overall survival in some settings. When delivering SBRT to liver metastases, clinicians must balance the priorities of delivering ablative tumor dosing while respecting dose constraints to surrounding organs at risk (OARs). Motion management techniques are crucial for meeting dose constraints, ensuring low rates of toxicity, maintaining quality of life, and can allow for dose escalation. Advanced radiotherapy delivery approaches including proton therapy, robotic radiotherapy, and real-time MR-guided radiotherapy may further improve the accuracy of liver SBRT. In this article, we review the rationale for oligometastases ablation, the clinical outcomes with liver SBRT, tumor dose and OAR considerations, and evolving strategies to improve liver SBRT delivery.

Advances in Radiation Therapy for Primary Liver Cancer

During the past 30 years, several advances have been made allowing for safer and more effective treatment of patients with liver cancer. This report reviews recent advances in radiation therapy for primary liver cancers including hepatocellular carcinoma and intrahepatic cholangiocarcinoma. First, studies focusing on liver stereotactic body radiation therapy (SBRT) are reviewed focusing on lessons learned and knowledge gained from early pioneering trials. Then, new technologies to enhance SBRT treatments are explored including adaptive therapy and MRI-guided and biology-guided radiation therapy. Finally, treatment with Y-90 transarterial radioembolization is reviewed with a focus on novel approaches focused on personalized therapy.

A roadmap for implementation of kV-CBCT online adaptive radiation therapy and initial first year experiences

PURPOSE

Online Adaptive Radiation Therapy (oART) follows a different treatment paradigm than conventional radiotherapy, and because of this, the resources, implementation, and workflows needed are unique. The purpose of this report is to outline our institution's experience establishing, organizing, and implementing an oART program using the Ethos therapy system.

METHODS

We include resources used, operational models utilized, program creation timelines, and our institutional experiences with the implementation and operation of an oART program. Additionally, we provide a detailed summary of our first year's clinical experience where we delivered over 1000 daily adaptive fractions. For all treatments, the different stages of online adaption, primary patient set-up, initial kV-CBCT acquisition, contouring review and edit of influencer structures, target review and edits, plan evaluation and selection, Mobius3D 2nd check and adaptive QA, 2nd kV-CBCT for positional verification, treatment delivery, and patient leaving the room, were analyzed.

RESULTS

We retrospectively analyzed data from 97 patients treated from August 2021-August 2022. One thousand six hundred seventy seven individual fractions were treated and analyzed, 632(38%) were non-adaptive and 1045(62%) were adaptive. Seventy four of the 97 patients (76%) were treated with standard fractionation and 23 (24%) received stereotactic treatments. For the adaptive treatments, the generated adaptive plan was selected in 92% of treatments. On average(±std), adaptive sessions took 34.52 ± 11.42 min from start to finish. The entire adaptive process (from start of contour generation to verification CBCT), performed by the physicist (and physician on select days), was 19.84 ± 8.21 min.

CONCLUSION

We present our institution's experience commissioning an oART program using the Ethos therapy system. It took us 12 months from project inception to the treatment of our first patient and 12 months to treat 1000 adaptive fractions. Retrospective analysis of delivered fractions showed that the average overall treatment time was approximately 35 min and the average time for the adaptive component of treatment was approximately 20 min.

Stereotactic magnetic resonance-guided online adaptive radiotherapy of adrenal metastases combines high ablative doses with optimized sparing of organs at risk

Purpose/Objective

To evaluate the potential of stereotactic magnetic resonance-guided online adaptive radiotherapy (SMART) to fulfill dose recommendations for stereotactic body radiotherapy (SBRT) of adrenal metastases and spare organs at risk (OAR).

Materials and methods

In this subgroup analysis of a prospective registry trial, 22 patients with adrenal metastases were treated on a 0.35 T MR-Linac in 5-12 fractions with fraction doses of 4-10 Gy. Baseline plans were re-calculated to the anatomy of the day. These predicted plans were reoptimized to generate adapted plans. Baseline, predicted and adapted plans were compared with regard to PTV objectives, OAR constraints and published dose recommendations.

Results

The cohort comprised patients with large GTV (median 36.0 cc) and PTV (median 66.6 cc) and predominantly left-sided metastases. 179 of 181 fractions (98.9 %) were adapted because of PTV and/or OAR violations. Predicted plans frequently violated PTV coverage (99.4 %) and adjacent OAR constraints (bowel: 32.9 %, stomach: 32.8 %, duodenum: 10.4 %, kidneys: 10.8 %). In the predicted plans, the volume exposed to the maximum dose was exceeded up to 16-fold in the duodenum and up to 96-fold in the spinal cord. Adapted plans significantly reduced OAR violations by 96.4 % for the bowel, 98.5 % for the stomach, 85.6 % for the duodenum and 83.3 % for the kidneys. Plan adaptation improved PTV coverage from 82.7 ± 8.1 % to 90.6 ± 4.9 % (p < 0.001). Furthermore, recently established target volume thresholds could easily be fulfilled with SMART. No toxicities > grade II occurred.

Conclusion

SMART fulfills established GTV and PTV dose recommendations while simultaneously sparing organs at risk even in a challenging cohort.

Impact of Adapted Radiotherapy Schedules on Bowel Sparing in Node-Positive Cervical Cancer

PURPOSE

Definitive radiation therapy (RT) for locally advanced node-positive cervical cancer confers significant toxicity to pelvic organs including the small bowel. Gross nodal disease exhibits significant shrinkage during RT, and yet conventional RT does not account for this change. We evaluated the reduction in absorbed bowel dose using various adaptive RT schedules.

METHODS AND MATERIALS

We obtained 130 evaluable scans (computed tomography simulation and 25 cone beam computed tomography scans per patient) of 5 patients who had received definitive external beam RT for lymph node positive cervical cancer daily over 5 weeks. Using a single universal volumetric modulated arc therapy plan with predefined optimization priorities, we created adapted RT plans in 4 schedules: Daily, Weekly, Twice, and NoAdapt (mimicking conventional nonadapted RT). The in silico (computer modeled) patients were treated to 45 Gy to primary cervical disease with a simultaneous integrated boost to 55 Gy to involved lymph nodes. We evaluated dose metrics including D2cc, D15cc, and V45 to determine the impact of adapted RT schedules on bowel sparing. Statistical tests included the Student t test, analysis of variance, and the Spearman rank correlation.

RESULTS

The quantity of reduced bowel dose was significantly associated with the chosen planning schedule in all evaluated metrics and was proportional to the frequency of adaptive RT with significant moderate-to-strong monotonicity. Both D2cc and D15cc were reduced an average of 2.7 Gy using daily replanning compared with a nonadapted approach. A minimally adapted strategy of only 2 replans also confers a significant dosimetric benefit over a nonadapted approach. Reduced standard deviations of D2cc and V45 bowel doses over the treatment courses were significantly associated with the choice of planning schedule with strong monotonicity.

CONCLUSIONS

All adaptive RT schedules evaluated confer significant dosimetric advantages in bowel sparing over a conventional nonadapted technique, with greater sparing seen with more frequent replanning schedules. These findings warrant future trials of adaptive RT for pelvic malignancies.

MRI-LINAC: A transformative technology in radiation oncology

Advances in radiotherapy technologies have enabled more precise target guidance, improved treatment verification, and greater control and versatility in radiation delivery. Amongst the recent novel technologies, Magnetic Resonance Imaging (MRI) guided radiotherapy (MRgRT) may hold the greatest potential to improve the therapeutic gains of image-guided delivery of radiation dose. The ability of the MRI linear accelerator (LINAC) to image tumors and organs with on-table MRI, to manage organ motion and dose delivery in real-time, and to adapt the radiotherapy plan on the day of treatment while the patient is on the table are major advances relative to current conventional radiation treatments. These advanced techniques demand efficient coordination and communication between members of the treatment team. MRgRT could fundamentally transform the radiotherapy delivery process within radiation oncology centers through the reorganization of the patient and treatment team workflow process. However, the MRgRT technology currently is limited by accessibility due to the cost of capital investment and the time and personnel allocation needed for each fractional treatment and the unclear clinical benefit compared to conventional radiotherapy platforms. As the technology evolves and becomes more widely available, we present the case that MRgRT has the potential to become a widely utilized treatment platform and transform the radiation oncology treatment process just as earlier disruptive radiation therapy technologies have done.

Proton Beam Therapy and Photon-Based Magnetic Resonance Image-Guided Radiation Therapy: The Next Frontiers of Radiation Therapy for Hepatocellular Carcinoma

External beam radiation therapy (EBRT) has increasingly been utilized in the treatment of hepatocellular carcinoma (HCC) due to technological advances with positive clinical outcomes. Innovations in EBRT include improved image guidance, motion management, treatment planning, and highly conformal techniques such as intensity-modulated radiation therapy (IMRT) and stereotactic body radiation therapy (SBRT). Moreover, proton beam therapy (PBT) and magnetic resonance image-guided radiation therapy (MRgRT) have expanded the capabilities of EBRT. PBT offers the advantage of minimizing low- and moderate-dose radiation to the surrounding normal tissue, thereby preserving uninvolved liver and allowing for dose escalation. MRgRT provides the advantage of improved soft tissue delineation compared to computerized tomography (CT) guidance. Additionally, MRgRT with online adaptive therapy is particularly useful for addressing motion not otherwise managed and reducing high-dose radiation to the normal tissue such as the stomach and bowel. PBT and online adaptive MRgRT are emerging technological advancements in EBRT that may provide a significant clinical benefit for patients with HCC.

Self-supervised learning for automated anatomical tracking in medical image data with minimal human labeling effort

BACKGROUND AND OBJECTIVE

Tracking of anatomical structures in time-resolved medical image data plays an important role for various tasks such as volume change estimation or treatment planning. State-of-the-art deep learning techniques for automated tracking, while providing accurate results, require large amounts of human-labeled training data making their wide-spread use time- and resource-intensive. Our contribution in this work is the implementation and adaption of a self-supervised learning (SSL) framework that addresses this bottleneck of training data generation.

METHODS

To this end we adapted and implemented an SSL framework that allows for automated anatomical tracking without the necessity for human-labeled training data. We evaluated this method by comparison to conventional- and deep learning optical flow (OF)-based tracking methods. We applied all methods on three different time-resolved medical image datasets (abdominal MRI, cardiac MRI, and echocardiography) and assessed their accuracy regarding tracking of pre-defined anatomical structures within and across individuals.

RESULTS

We found that SSL-based tracking as well as OF-based methods provide accurate results for simple, rigid and smooth motion patterns. However, regarding more complex motion, e.g. non-rigid or discontinuous motion patterns in the cardiac region, and for cross-subject anatomical matching, SSL-based tracking showed markedly superior performance.

CONCLUSION

We conclude that automated tracking of anatomical structures on time-resolved medical image data with minimal human labeling effort is feasible using SSL and can provide superior results compared to conventional and deep learning OF-based methods.

The critical components for effective adaptive radiotherapy in patients with unresectable non-small-cell lung cancer: who, when and how

Adaptive radiotherapy (ART) is a new radiotherapy technology based on image-guided radiation therapy technology, used to avoid radiation overexposure to residual tumors and the surrounding normal tissues. Tumors undergoing the same radiation doses and modes can occur unequal shrinkage due to the variation of response times to radiation doses in different patients. To perform ART effectively, eligible patients with a high probability of benefits from ART need to be identified. Confirming the precise timetable for ART in every patient is another urgent problem to be resolved. Moreover, the outcomes of ART are different depending on the various image guidance used. This review discusses 'who, when and how' as the three key factors involved in the most effective implementation for the management of ART.

Radiomics-based nomogram as predictive model for prognosis of hepatocellular carcinoma with portal vein tumor thrombosis receiving radiotherapy

Background

This study aims to establish and validate a predictive model based on radiomics features, clinical features, and radiation therapy (RT) dosimetric parameters for overall survival (OS) in hepatocellular carcinoma (HCC) patients treated with RT for portal vein tumor thrombosis (PVTT).

Methods

We retrospectively reviewed 131 patients. Patients were randomly divided into the training (n = 105) and validation (n = 26) cohorts. The clinical target volume was contoured on pre-RT computed tomography images and 48 textural features were extracted. The least absolute shrinkage and selection operator regression was used to determine the radiomics score (rad-score). A nomogram based on rad-score, clinical features, and dosimetric parameters was developed using the results of multivariate regression analysis. The predictive nomogram was evaluated using Harrell’s concordance index (C-index), area under the curve (AUC), and calibration curve.

Results

Two radiomics features were extracted to calculate the rad-score for the prediction of OS. The radiomics-based nomogram had better performance than the clinical nomogram for the prediction of OS, with a C-index of 0.73 (95% CI, 0.67–0.79) and an AUC of 0.71 (95% CI, 0.62–0.79). The predictive accuracy was assessed by a calibration curve.

Conclusion

The radiomics-based predictive model significantly improved OS prediction in HCC patients treated with RT for PVTT.

Simulated computed tomography-guided stereotactic adaptive radiotherapy (CT-STAR) for the treatment of locally advanced pancreatic cancer

BACKGROUND AND PURPOSE

We conducted a prospective, in silico imaging clinical trial to evaluate the feasibility and potential dosimetric benefits of computed tomography-guided stereotactic adaptive radiotherapy (CT-STAR) for the treatment of locally advanced pancreatic cancer (LAPC).

MATERIALS AND METHODS

Eight patients with LAPC received five additional CBCTs on the ETHOS system before or after their standard of care radiotherapy treatment. Initial plans were created based on their initial simulation anatomy (P_I) and emulated adaptive plans were created based on their anatomy-of-the-day (P_A). The prescription was 50 Gy/5 fractions. Plans were created under a strict isotoxicity approach, in which organ-at-risk (OAR) constraints were prioritized over planning target volume coverage. The P_I was evaluated on the patient's anatomy-of-the-day, compared to the daily P_A, and the superior plan was selected. Feasibility was defined as successful completion of the workflow in compliance with strict OAR constraints in ≥80% of fractions.

RESULTS

CT-STAR was feasible in silico for LAPC and improved OAR and/or target dosimetry in 100% of fractions. Use of the P_I based on the patient's anatomy-of-the-day would have yielded a total of 94 OAR constraint violations and ≥1 hard constraint violation in 40/40 fractions. In contrast, 39/40 P_A met all OAR constraints. In one fraction, the P_A minimally exceeded the large bowel constraint, although dosimetrically improved compared to the P_I. Total workflow time per fraction was 36.28 minutes (27.57-55.86).

CONCLUSION

CT-STAR for the treatment of LAPC cancer proved feasible and was dosimetrically superior to non-adapted CT-stereotactic body radiotherapy.

Improving liver tumor image contrast and synthesizing novel tissue contrasts by adaptive multiparametric MRI fusion

Purpose

Multiparametric MRI contains rich and complementary anatomical and functional information, which is often utilized separately. This study aims to propose an adaptive multiparametric MRI (mpMRI) fusion method and examine its capability in improving tumor contrast and synthesizing novel tissue contrasts among liver cancer patients.

Methods

An adaptive mpMRI fusion method was developed with five components: image pre-processing, fusion algorithm, database, adaptation rules, and fused MRI. Linear-weighted summation algorithm was used for fusion. Weight-driven and feature-driven adaptations were designed for different applications. A clinical-friendly graphic-user-interface (GUI) was developed in Matlab and used for mpMRI fusion. Twelve liver cancer patients and a digital human phantom were included in the study. Synthesis of novel image contrast and enhancement of image signal and contrast were examined in patient cases. Tumor contrast-to-noise ratio (CNR) and liver signal-to-noise ratio (SNR) were evaluated and compared before and after mpMRI fusion.

Results

The fusion platform was applicable in both XCAT phantom and patient cases. Novel image contrasts, including enhancement of soft-tissue boundary, vertebral body, tumor, and composition of multiple image features in a single image were achieved. Tumor CNR improved from -1.70 ± 2.57 to 4.88 ± 2.28 (p < 0.0001) for T1-w, from 3.39 ± 1.89 to 7.87 ± 3.47 (p < 0.01) for T2-w, and from 1.42 ± 1.66 to 7.69 ± 3.54 (p < 0.001) for T2/T1-w MRI. Liver SNR improved from 2.92 ± 2.39 to 9.96 ± 8.60 (p < 0.05) for DWI. The coefficient of variation (CV) of tumor CNR lowered from 1.57, 0.56, and 1.17 to 0.47, 0.44, and 0.46 for T1-w, T2-w and T2/T1-w MRI, respectively.

Conclusion

A multiparametric MRI fusion method was proposed and a prototype was developed. The method showed potential in improving clinically relevant features such as tumor contrast and liver signal. Synthesis of novel image contrasts including the composition of multiple image features into single image set was achieved.

Deep learning-based low-dose CT for adaptive radiotherapy of abdominal and pelvic tumors

The shape and position of abdominal and pelvic organs change greatly during radiotherapy, so image-guided radiation therapy (IGRT) is urgently needed. The world’s first integrated CT-linac platform, equipped with fan beam CT (FBCT), can provide a diagnostic-quality FBCT for achieve adaptive radiotherapy (ART). However, CT scans will bring the risk of excessive scanning radiation dose. Reducing the tube current of the FBCT system can reduce the scanning dose, but it will lead to serious noise and artifacts in the reconstructed images. In this study, we proposed a deep learning method, Content-Noise Cycle-Consistent Generative Adversarial Network (CNCycle-GAN), to improve the image quality and CT value accuracy of low-dose FBCT images to meet the requirements of adaptive radiotherapy. We selected 76 patients with abdominal and pelvic tumors who received radiation therapy. The patients received one low-dose CT scan and one normal-dose CT scan in IGRT mode during different fractions of radiotherapy. The normal dose CT images (NDCT) and low dose CT images (LDCT) of 70 patients were used for network training, and the remaining 6 patients were used to validate the performance of the network. The quality of low-dose CT images after network restoration (RCT) were evaluated in three aspects: image quality, automatic delineation performance and dose calculation accuracy. Taking NDCT images as a reference, RCT images reduced MAE from 34.34 ± 5.91 to 20.25 ± 4.27, PSNR increased from 34.08 ± 1.49 to 37.23 ± 2.63, and SSIM increased from 0.92 ± 0.08 to 0.94 ± 0.07. The P value is less than 0.01 of the above performance indicators indicated that the difference were statistically significant. The Dice similarity coefficients (DCS) between the automatic delineation results of organs at risk such as bladder, femoral heads, and rectum on RCT and the results of manual delineation by doctors both reached 0.98. In terms of dose calculation accuracy, compared with the automatic planning based on LDCT, the difference in dose distribution between the automatic planning based on RCT and the automatic planning based on NDCT were smaller. Therefore, based on the integrated CT-linac platform, combined with deep learning technology, it provides clinical feasibility for the realization of low-dose FBCT adaptive radiotherapy for abdominal and pelvic tumors.

Clinical performance evaluation of O-Ring Halcyon Linac: A real-world study

BACKGROUND

Radiation therapy, especially the development of linear accelerators, plays a key role in cancer management. The fast-rotating coplanar O-ring Halcyon Linac has demonstrated many advantages. The previous literature has mainly focused on the machine parameters and plan quality of Halcyon, with a lack of relevant research on its clinical application.

AIM

To evaluate the clinical performance of the O-ring Halcyon treatment system in a real-world application setting.

METHODS

Data from sixty-one patients who were treated with the Halcyon system throughout the entire radiotherapy process in Peking Union Medical College Hospital between August 2019 and September 2020 were retrospectively reviewed. We evaluated the target tumour response to radiotherapy and irradiation toxicity from 1 to 3 mo after treatment. Dosimetric verification of Halcyon plans was performed using a quality assurance procedure, including portal dosimetry, ArcCHECK and point dose measurements for verification of the system delivery accuracy.

RESULTS

Of the 61 patients in the five groups, 16, 12, 7 and 26 patients had complete response, partial response, progressive disease and stable disease, respectively. No increase in the irradiated target tumour volume was observed when separately evaluating the local response. Regarding irradiation toxicity, no radiation-induced deaths were observed. Thirty-eight percent (23/61 patients) had no radiation toxicity after radiotherapy, 56% (34/61 patients) experienced radiation toxicity that resolved after treatment, and 6% (4/61 patients) had irreversible adverse reactions. The average gamma passing rates with a 2% dose difference and 2-mm distance to agreement for IMRT/VMAT/SRT plans were ArcCHECK at 96.4% and portal dosimetry at 96.7%, respectively. All of the validated clinical plans were within 3% for point dose measurements, and Halcyon’s ArcCHECK demonstrated a high pass rate of 99.1% ± 1.1% for clinical gamma passing criteria of 3%/3 mm.

CONCLUSION

The O-ring Halcyon Linac could achieve a better therapeutic effect on the target volume by providing accurate treatment delivery plans with tolerable irradiation toxicity.

MR-LINAC-Guided Adaptive Radiotherapy for Gastric MALT: Two Case Reports and a Literature Review

It is still very challenging to use conventional radiation therapy techniques to treat stomach tumors, although image-guided radiotherapy, mainly by kV X-ray imaging techniques, has become routine in the clinic. This is because the stomach is one of the most deformable organs, and thus it is vulnerable to respiratory motions, daily diet, and body position changes. In addition, X-ray radiographs and CT volumetric images have low contrast in soft tissues. In contrast, magnetic resonance imaging (MRI) techniques provide good contrast in images of soft tissues. The emerging MR-guided radiotherapy, based on the MR-LINAC system, may have the potential to solve the above difficulties due to its unique advantages. The real-time imaging feature and the high-contrast of soft tissues MR images provided by the MR-LINAC system have facilitated the therapeutic adaptive planning. Online learning capabilities could be used to optimize the automatic delineation of the target organ or tissue prior to each radiotherapy session. This could greatly improve the accuracy and efficiency of the target delineation in adaptive planning. In this clinical case report, we elaborated a workflow for the diagnosis and treatment of two patients with gastric mucosa-associated lymphoid tissue (MALT) lymphoma. One patient underwent MR-guided daily adaptive radiotherapy based on daily automated segmentation using the novel artificial intelligence (AI) technique for gastric delineation.

Single projection driven real-time multi-contrast (SPIDERM) MR imaging using pre-learned spatial subspace and linear transformation

Objective. To develop and test the feasibility of a novel Single ProjectIon DrivEn Real-time Multi-contrast (SPIDERM) MR imaging technique that can generate real-time 3D images on-the-fly with flexible contrast weightings and a low latency. Approach. In SPIDERM, a ‘prep’ scan is first performed, with sparse k-space sampling periodically interleaved with the central k-space line (navigator data), to learn a subject-specific model, incorporating a spatial subspace and a linear transformation between navigator data and subspace coordinates. A ‘live’ scan is then performed by repeatedly acquiring the central k-space line only to dynamically determine subspace coordinates. With the ‘prep’-learned subspace and ‘live’ coordinates, real-time 3D images are generated on-the-fly with computationally efficient matrix multiplication. When implemented based on a multi-contrast pulse sequence, SPIDERM further allows for data-driven image contrast regeneration to convert real-time contrast-varying images into contrast-frozen images at user’s discretion while maintaining motion states. Both digital phantom and in-vivo experiments were performed to evaluate the technical feasibility of SPIDERM. Main results. The elapsed time from the input of the central k-space line to the generation of real-time contrast-frozen 3D images was approximately 45 ms, permitting a latency of 55 ms or less. Motion displacement measured from SPIDERM and reference images showed excellent correlation ( R 2 ≥ 0.983 ). Geometric variation from the ground truth in the digital phantom was acceptable as demonstrated by pancreas contour analysis (Dice ≥ 0.84, mean surface distance ≤ 0.95 mm). Quantitative image quality metrics showed good consistency between reference images and contrast-varying SPIDREM images in in-vivo studies (mean NMRSE = 0.141 , PSNR = 3 0.12 , SSIM = 0.88 ). Significance. SPIDERM is capable of generating real-time multi-contrast 3D images with a low latency. An imaging framework based on SPIDERM has the potential to serve as a standalone package for MR-guided radiation therapy by offering adaptive simulation through a ‘prep’ scan and real-time image guidance through a ‘live’ scan.

SPIO-enhanced 0.35T MRI-guided radiotherapy for liver malignancies: usefulness in tumor visualization

OBJECTIVES

The purpose of this study was to investigate the changes of tumor-to-liver signal ratio in a 0.35T MRI-guided radiotherapy system and to evaluate the usefulness and pitfalls of superparamagnetic iron oxide (SPIO) administration for visualization of liver tumors.

METHODS

Forty-two patients treated with MRI-guided stereotactic ablative radiotherapy (SABR) for liver tumors were included in this study. The tumor-to-liver signal ratios before and after SPIO administration were retrospectively assessed and compared on true fast imaging with steady-state precession (FISP).

RESULTS

Before SPIO administration, liver tumors were either invisible or barely visible in 15 cases (36%), but all tumors became visible after SPIO administration. The mean values of tumor-to-liver signal ratio before and after SPIO administration were 0.939 ± 0.201 and 1.336 ± 0.300, respectively (mean ± standard deviation, p < 0.001). In six (14%) patients, liver tumors were visible on true FISP imaging before SPIO administration, but became invisible after administration.

CONCLUSIONS

This study showed that liver tumors that are invisible on true FISP imaging can be made visible by administration of SPIO, and that MRI-guided SABR can be performed accurately.

ADVANCES IN KNOWLEDGE

This is the first report to examine the usefulness of liver-specific contrast agent superparamagnetic iron oxides in 0.35T MRI-guided radiation therapy. Liver tumors that are invisible on true fast imaging with steady-state precession can be made visible by administration of superparamagnetic iron oxides.

Methyltransferase 1 is required for nonhomologous end-joining repair and renders hepatocellular carcinoma resistant to radiotherapy

BACKGROUND AND AIMS

Radiotherapy is an increasingly essential therapeutic strategy in the management of hepatocellular carcinoma (HCC). Nevertheless, resistance to radiotherapy is one of the primary obstacles to successful treatment outcomes. Hence, we aim to elucidate the mechanisms underlying radioresistance and identify reliable biotargets that would be inhibited to enhance the efficacy of radiotherapy in HCC.

APPROACH AND RESULTS

From a label-free quantitative proteome screening, we identified transfer RNA (tRNA; guanine-N [7]-) methyltransferase 1 (METTL1), a key enzyme for N7-methylguanosine (m⁷ G) tRNA modification, as an essential driver for HCC cells radioresistance. We reveal that METTL1 promotes DNA double-strand break (DSB) repair and renders HCC cells resistant to ionizing radiation (IR) using loss-of-function and gain-of-function assays in vitro and in vivo. Mechanistically, METTL1-mediated m⁷ G tRNA modification selectively regulates the translation of DNA-dependent protein kinase catalytic subunit or DNA ligase IV with higher frequencies of m⁷ G-related codons after IR treatment, thereby resulting in the enhancement of nonhomologous end-joining (NHEJ)-mediated DNA DSB repair efficiency. Clinically, high METTL1 expression in tumor tissue is significantly correlated with poor prognosis in radiotherapy-treated patients with HCC.

CONCLUSIONS

Our findings show that METTL1 is a critical enhancer for HCC cell NHEJ-based DNA repair following IR therapy. These findings give insight into the role of tRNA modification in messenger RNA translation control in HCC radioresistance.

Radiomics for the detection of microvascular invasion in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the most common primary liver cancer, accounting for about 90% of liver cancer cases. It is currently the fifth most common cancer in the world and the third leading cause of cancer-related mortality. Moreover, recurrence of HCC is common. Microvascular invasion (MVI) is a major factor associated with recurrence in postoperative HCC. It is difficult to evaluate MVI using traditional imaging modalities. Currently, MVI is assessed primarily through pathological and immunohistochemical analyses of postoperative tissue samples. Needle biopsy is the primary method used to confirm MVI diagnosis before surgery. As the puncture specimens represent just a small part of the tumor, and given the heterogeneity of HCC, biopsy samples may yield false-negative results. Radiomics, an emerging, powerful, and non-invasive tool based on various imaging modalities, such as computed tomography, magnetic resonance imaging, ultrasound, and positron emission tomography, can predict the HCC-MVI status preoperatively by delineating the tumor and/or the regions at a certain distance from the surface of the tumor to extract the image features. Although positive results have been reported for radiomics, its drawbacks have limited its clinical translation. This article reviews the application of radiomics, based on various imaging modalities, in preoperative evaluation of HCC-MVI and explores future research directions that facilitate its clinical translation.

Hypofractionation in Hepatocellular Carcinoma - The Effect of Fractionation Size

The use of stereotactic body radiotherapy (SBRT) in hepatocellular carcinoma (HCC) has increased over the years. Several prospective studies have demonstrated its safety and efficacy, and randomised trials are underway. The advancement in technology has enabled the transition from three-dimensional conformal radiotherapy to highly focused SBRT. Liver damage is the primary limiting toxicity with radiation, with the incidence of grade 3 varying from 0 to 30%. The reported radiotherapy fractionation schedule for HCC, and in practice use, ranges from one to 10 fractions, based on clinician preference and technology available, tumour location and tumour size. This review summarises the safety and efficacy of various SBRT fractionation schedules for HCC.

Stereotactic radiotherapy for liver oligometastases

The liver is the first metastatic site in 15–25% of colorectal cancer patients and one of the first metastatic sites for lung and breast cancer patients.

A computed tomography (CT ) scan with contrast medium is a standard procedure for assessing liver lesions but magnetic resonance imaging (MRI) characterizes small lesions better thanks to its high soft-tissue contrast. Positron emission tomography with computed tomography (PET-CT ) plays a complementary role in the diagnosis of liver metastases. Triphasic (arterial, venous and time-delayed) acquisition of contrast-medium CT images is the first step in treatment planning. Since the liver exhibits a relatively wide mobility due to respiratory movements and bowel filling, appropriate techniques are needed for target identification and motion management. Contouring requires precise recognition of target lesion edges. Information from contrast MRI and/or PET-CT is crucial as they best visualize metastatic disease in the parenchyma. Even though different fractionation schedules were reported, doses and fractionation schedules for liver stereotactic radiotherapy (SRT ) have not yet been established. The best local control rates were obtained with BED₁₀ values over 100 Gy. Local control rates from most retrospective studies, which were limited by short follow-ups and included different primary tumors with intrinsic heterogeneity, ranged from 60% to 90% at 1 and 2 years. The most common SRT-related toxicities are increases in liver enzymes, hyperbilirubinemia and hypoalbuminemia. Overall, late toxicity is mild even in long-term follow-ups.

Evaluation of Multisource Adaptive MRI Fusion for Gross Tumor Volume Delineation of Hepatocellular Carcinoma

Purpose

Tumor delineation plays a critical role in radiotherapy for hepatocellular carcinoma (HCC) patients. The incorporation of MRI might improve the ability to correctly identify tumor boundaries and delineation consistency. In this study, we evaluated a novel Multisource Adaptive MRI Fusion (MAMF) method in HCC patients for tumor delineation.

Methods

Ten patients with HCC were included in this study retrospectively. Contrast-enhanced T1-weighted MRI at portal-venous phase (T1W_PP), contrast-enhanced T1-weighted MRI at 19-min delayed phase (T1W_DP), T2-weighted (T2W), and diffusion-weighted MRI (DWI) were acquired on a 3T MRI scanner and imported to in-house-developed MAMF software to generate synthetic MR fusion images. The original multi-contrast MR image sets were registered to planning CT by deformable image registration (DIR) using MIM. Four observers independently delineated gross tumor volumes (GTVs) on the planning CT, four original MR image sets, and the fused MRI for all patients. Tumor contrast-to-noise ratio (CNR) and Dice similarity coefficient (DSC) of the GTVs between each observer and a reference observer were measured on the six image sets. Inter-observer and inter-patient mean, SD, and coefficient of variation (CV) of the DSC were evaluated.

Results

Fused MRI showed the highest tumor CNR compared to planning CT and original MR sets in the ten patients. The mean ± SD tumor CNR was 0.72 ± 0.73, 3.66 ± 2.96, 4.13 ± 3.98, 4.10 ± 3.17, 5.25 ± 2.44, and 9.82 ± 4.19 for CT, T1W_PP, T2W, DWI, T1W_DP, and fused MRI, respectively. Fused MRI has the minimum inter-observer and inter-patient variations as compared to original MR sets and planning CT sets. GTV delineation inter-observer mean DSC across the ten patients was 0.81 ± 0.09, 0.85 ± 0.08, 0.88 ± 0.04, 0.89 ± 0.08, 0.90 ± 0.04, and 0.95 ± 0.02 for planning CT, T1W_PP, T2W, DWI, T1W_DP, and fused MRI, respectively. The patient mean inter-observer CV of DSC was 3.3%, 3.2%, 1.7%, 2.6%, 1.5%, and 0.9% for planning CT, T1W_PP, T2W, DWI, T1W_DP, and fused MRI, respectively.

Conclusion

The results demonstrated that the fused MRI generated using the MAMF method can enhance tumor CNR and improve inter-observer consistency of GTV delineation in HCC as compared to planning CT and four commonly used MR image sets (T1W_PP, T1W_DP, T2W, and DWI). The MAMF method holds great promise in MRI applications in HCC radiotherapy treatment planning.

A multi-institutional comparison of dosimetric data for a 0.35 T MR-linac

Objective. A comparison of percent depth dose (PDD) curves, lateral beam profiles, output factors (OFs), multileaf collimator (MLC) leakage, and couch transmission factors was performed between ten institutes for a commercial 0.35 T MR-linac. Approach. The measured data was collected during acceptance testing of the MR-linac. The PDD curves were measured for the 3.32 × 3.32 cm2, 9.96 × 9.96 cm2, and 27.20 × 24.07 cm2 field sizes. The lateral beam profiles were acquired for a 27.20 × 24.07 cm2 field size using an ion chamber array and penumbra was defined as the distance between 80% of the maximum dose and 20% of the maximum dose after normalizing the profiles to the dose at the inflection points. The OFs were measured using solid-state dosimeters, whereas radiochromic films were utilized to measure radiation leakage through the MLC stacks. The relative couch transmission factors were measured for various gantry angles. The variation in the multi-institutional data was quantified using the percent standard deviation metric. Main results. Minimal variations (<1%) were found between the PDD data, except for the build-up region and the deeper regions of the PDD curve. The in-field region of the lateral beam profiles varied <1.5% between different institutions and a small variation (<0.7 mm) in penumbra was observed. A variation of <1% was observed in the OF data for field sizes above 1.66 × 1.66 cm2, whereas large variations were shown for small-field sizes. The average and maximum MLC leakage was calculated to be <0.3% and <0.6%, which was well below the international electrotechnical commission (IEC) leakage thresholds. The couch transmission was smallest for oblique beams and ranged from 0.83 to 0.87. Significance. The variation in the data was found to be relatively small and the different 0.35 T MR-linacs were concluded to have similar dosimetric characteristics.

Rapid Progress in Intelligent Radiotherapy and Future Implementation

Radiotherapy is one of the major approaches to cancer treatment. Artificial intelligence in radiotherapy (shortly, Intelligent radiotherapy) mainly involves big data, deep learning, extended reality, digital twin, radiomics, Internet plus and Internet of Things (IoT), which establish an automatic and intelligent network platform consisting of radiotherapy preparation, target volume delineation, treatment planning, radiation delivery, quality assurance (QA) and quality control (QC), prognosis judgment and post-treatment follow-up. Intelligent radiotherapy is an interdisciplinary frontier discipline in infancy. The review aims to summary the important implements of intelligent radiotherapy in various areas and put forward the future of unmanned radiotherapy center.

Shielding Ferritin with a Biomineralized Shell Enables Efficient Modulation of Tumor Microenvironment and Targeted Delivery of Diverse Therapeutic Agents

Ferritin (Fn) is considered a promising carrier for targeted delivery to tumors, but the successful application in vivo has not been fully achieved yet. Herein, strong evidence is provided that the Fn receptor is expressed in liver tissues, resulting in an intercept effect in regards to tumor delivery. Building on these observations, a biomineralization technology is rationally designed to shield Fn using a calcium phosphate (CaP) shell, which can improve the delivery performance by reducing Fn interception in the liver while re-exposing it in acidic tumors. Moreover, the selective dissolution of the CaP shell not only neutralizes the acidic microenvironment but also induces the intratumoral immunomodulation and calcification. Upon multiple cell line and patient-derived xenografts, it is demonstrated that the elaboration of the highly flexible Fn@CaP chassis by loading a chemotherapeutic drug into the Fn cavity confers potent antitumor effects, and additionally encapsulating a photosensitizer into the outer shell enables a combined chemo-photothermal therapy for complete suppression of advanced tumors. Altogether, these results support Fn@CaP as a new nanoplatform for efficient modulation of the tumor microenvironment and targeted delivery of diverse therapeutic agents.

MRI-Guided Online Adaptive Stereotactic Body Radiation Therapy of Liver and Pancreas Tumors on an MR-Linac System

Simple Summary

The hybrid magnetic resonance imaging and medical linear accelerator (MR-Linac) systems are expected to revolutionize radiation therapy, uniquely offering high quality soft-tissue contrast and fast imaging to facilitate the online re-planning and guidance of the treatment delivery. While the clinical procedures for stereotactic body radiotherapy are well-established for conventional linacs (with their strengths and weaknesses), they still require significant development and refinement for the MR-Linac systems. Adjustment of fractionation schemes including clinical goals, patient selection, organ motion management, treatment session length, staff logistics, and overall complexity of the online re-planning sessions are key factors that drive the adoption of MR-Linac technologies. In this report, we present the clinical implementation of an MRI-guided radiation therapy workflow, which was used to treat 16 upper gastro-intestinal cancer patients on a 1.5 T MR-Linac platform. The workflow was proven to be feasible for a wide range of clinical scenarios, and the overall treatment session time was significantly reduced as tasks were optimized and the clinical team gradually gained expertise.

Abstract

Purpose: To describe a comprehensive workflow for MRI-guided online adaptive stereotactic body radiation therapy (SBRT) specific to upper gastrointestinal cancer patients with abdominal compression on a 1.5T MR-Linac system. Additionally, we discuss the workflow’s clinical feasibility and early experience in the case of 16 liver and pancreas patients. Methods: Eleven patients with liver cancer and five patients with pancreas cancer were treated with online adaptive MRI-guidance under abdominal compression. Two liver patients received single-fraction treatments; the remainder plus all pancreas cancer patients received five fractions. A total of 65 treatment sessions were investigated to provide analytics relevant to the online adaptive processes. The quantification of target and organ motion as well as definition and validation of internal target volume (ITV) margins were performed via multi-contrast imaging provided by three different 2D cine sequences. The plan generation was driven by full re-optimization strategies and using T2-weighted 3D image series acquired by means of a respiratory-triggered exhale phase or a time-averaged imaging protocol. As a pre-requisite for the clinical development of the procedure, the image quality was thoroughly investigated via phantom measurements and numerical simulations specific to upper abdominal sites. The delivery of the online adaptive treatments was facilitated by real-time monitoring with 2D cine imaging. Results: Liver 1-fraction and 5-fraction online adaptive session time were on average 80 and 67.5 min, respectively. The total session length varied between 70–90 min for a single fraction and 55–90 min for five fractions. The pancreas sessions were 54–85 min long with an average session time of 68.2 min. Target visualization on the 2D cine image data varied per patient, with at least one of the 2D cine sequences providing sufficient contrast to confidently identify its location and confirm reproducibility of ITV margins. The mean/range of absolute and relative dose values for all treatment sessions evaluated with ArcCheck were 90.6/80.9–96.1% and 99/95.4–100%, respectively. Conclusion: MR-guidance is feasible for liver and pancreas tumors when abdominal compression is used to reduce organ motion, improve imaging quality, and achieve a robust intra- and inter-fraction patient setup. However, the treatment length is significantly longer than for the conventional linac, and patient compliance is paramount for the successful completion of the treatment. Opportunities for reducing the online adaptive session time should be explored. As the next steps, dose-of-the-day and dose accumulation analysis and tools are needed to enhance the workflow and to help further refine the online re-planning processes.

Magnetic resonance linear accelerator technology and adaptive radiation therapy: An overview for clinicians

Radiation therapy (RT) continues to play an important role in the treatment of cancer. Adaptive RT (ART) is a novel method through which RT treatments are evolving. With the ART approach, computed tomography or magnetic resonance (MR) images are obtained as part of the treatment delivery process. This enables the adaptation of the irradiated volume to account for changes in organ and/or tumor position, movement, size, or shape that may occur over the course of treatment. The advantages and challenges of ART maybe somewhat abstract to oncologists and clinicians outside of the specialty of radiation oncology. ART is positioned to affect many different types of cancer. There is a wide spectrum of hypothesized benefits, from small toxicity improvements to meaningful gains in overall survival. The use and application of this novel technology should be understood by the oncologic community at large, such that it can be appropriately contextualized within the landscape of cancer therapies. Likewise, the need to test these advances is pressing. MR-guided ART (MRgART) is an emerging, extended modality of ART that expands upon and further advances the capabilities of ART. MRgART presents unique opportunities to iteratively improve adaptive image guidance. However, although the MRgART adaptive process advances ART to previously unattained levels, it can be more expensive, time-consuming, and complex. In this review, the authors present an overview for clinicians describing the process of ART and specifically MRgART.

Initial clinical applications treating pediatric and adolescent patients using MR-guided radiotherapy

Purpose

To demonstrate the clinical applications and feasibility of online adaptive magnetic resonance image guided radiotherapy (MRgRT) in the pediatric, adolescent and young adult (AYA) population.

Methods

This is a retrospective case series of patients enrolled onto a prospective study. All pediatric (age < 18) and AYA patients (age< 30), treated on the Elekta Unity MR linear accelerator (MRL) from 2019 to 2021 were enrolled onto a prospective registry. Rationale for MRgRT included improved visualization of and alignment to the primary tumor, re-irradiation in a critical area, ability to use smaller margins, and need for daily adaptive replanning to minimize dose to adjacent critical structures. Step-and-shoot intensity-modulated radiation treatment (IMRT) plans were generated for all Unity patients with a dose grid of 3 mm and a statistical uncertainty of < 1% per plan.

Results

A total of 15 pediatric and AYA patients have been treated with median age of 13 years (range: 6 mos - 27 yrs). Seven patients were <10 yo. The clinical applications of MRgRT included Wilms tumor with unresectable IVC thrombus (n=1), Ewing sarcoma (primary and metastatic, n=3), recurrent diffuse intrinsic pontine glioma (DIPG, n=2), nasopharyngeal carcinoma (n=1), clival chordoma (n=1), primitive neuroectodermal tumor of the pancreas (n=1), recurrent gluteo-sacral germ cell tumor (n=1), C-spine ependymoma (n=1), and posterior fossa ependymoma (n=1). Two children required general anesthesia. One AYA patient could not complete the MRgRT course due to tumor-related pain exacerbated by longer treatment times. Two AYA patients experienced anxiety related to treatment on the MRL, one of which required daily Ativan. No patient experienced treatment interruptions or unexpected toxicity.

Conclusion

MRgRT was well-tolerated by pediatric and AYA patients. There was no increased use of anesthesia outside of our usual practice. Dosimetric advantages were seen for patients with tumors in critical locations such as adjacent to or involving optic structures, stomach, kidney, bowel, and heart.

Synthesizing high-resolution magnetic resonance imaging using parallel cycle-consistent generative adversarial networks for fast magnetic resonance imaging

PURPOSE

The common practice in acquiring the magnetic resonance (MR) images is to obtain two-dimensional (2D) slices at coarse locations while keeping the high in-plane resolution in order to ensure enough body coverage while shortening the MR scan time. The aim of this study is to propose a novel method to generate HR MR images from low-resolution MR images along the longitudinal direction. In order to address the difficulty of collecting paired low- and high-resolution MR images in clinical settings and to gain the advantage of parallel cycle consistent generative adversarial networks (CycleGANs) in synthesizing realistic medical images, we developed a parallel CycleGANs based method using a self-supervised strategy.

METHODS AND MATERIALS

The proposed workflow consists of two parallely trained CycleGANs to independently predict the HR MR images in the two planes along the directions that are orthogonal to the longitudinal MR scan direction. Then, the final synthetic HR MR images are generated by fusing the two predicted images. MR images, including T1-weighted (T1), contrast enhanced T1-weighted (T1CE), T2-weighted (T2), and T2 Fluid Attenuated Inversion Recovery (FLAIR), of the multimodal brain tumor segmentation challenge 2020 (BraTS2020) dataset were processed to evaluate the proposed workflow along the cranial-caudal (CC), lateral, and anterior-posterior directions. Institutional collected MR images were also processed for evaluation of the proposed method. The performance of the proposed method was investigated via both qualitative and quantitative evaluations. Metrics of normalized mean absolute error (NMAE), peak signal-to-noise ratio (PSNR), edge keeping index (EKI), structural similarity index measurement (SSIM), information fidelity criterion (IFC), and visual information fidelity in pixel domain (VIFP) were calculated.

RESULTS

It is shown that the proposed method can generate HR MR images visually indistinguishable from the ground truth in the investigations on the BraTS2020 dataset. In addition, the intensity profiles, difference images and SSIM maps can also confirm the feasibility of the proposed method for synthesizing HR MR images. Quantitative evaluations on the BraTS2020 dataset shows that the calculated metrics of synthetic HR MR images can all be enhanced for the T1, T1CE, T2, and FLAIR images. The enhancements in the numerical metrics over the low-resolution and bi-cubic interpolated MR images, as well as those genearted with a comparative deep learning method, are statistically significant. Qualitative evaluation of the synthetic HR MR images of the clinical collected dataset could also confirm the feasibility of the proposed method.

CONCLUSIONS

The proposed method is feasible to synthesize HR MR images using self-supervised parallel CycleGANs, which can be expected to shorten MR acquisition time in clinical practices.