Radiotherapy respiratory motion management in hepatobiliary and pancreatic malignancies: a systematic review of patient factors influencing effectiveness of motion reduction with abdominal compression

Patient Positional Uncertainty and Margin Reduction in Lung Stereotactic Ablative Radiation Therapy Using Pneumatic Abdominal Compression

PURPOSE

Motion management presents a significant challenge in thoracic stereotactic ablative radiation therapy (SABR). Currently, a 5.0-mm standard planning target volume (PTV) margin is widely used to ensure adequate dose to the tumor. Considering recent advancements in tumor localization and motion management, there is merit to reassessing the necessary PTV margins for modern techniques. This work presents a large-scale analysis of intrafraction repositioning for lung SABR under forced shallow breathing to determine the margin requirements for modern delivery techniques.

METHODS AND MATERIALS

Treatment data for 124 lung SABR patients treated in 607 fractions on a linear accelerator were retrospectively collected for analysis. All patients were treated using pneumatic abdominal compression and intrafraction 4-dimensional (4D) cone beam computed tomography (4D CBCT)-guided repositioning halfway through treatment. Executed repositioning shifts were collected and used to calculate margin requirements using the 2-SD method and an analytical model which accounts for systematic and random errors in treatment.

RESULTS

A total of 85.7% of treated fractions had 3-dimensional repositioning shifts under 5.0 mm. Fifty-three fractions (8.7%) had shifts ≥ 5.0 mm in at least 1 direction. Margins in the right-left, inferior-superior, and posterior-anterior directions were 3.62 mm, 4.34 mm, and 3.50 mm, respectively, calculated using the 2-SD method. The analytical approach estimated that 4.01 mm, 4.37 mm, and 3.95 mm margins were appropriate for our workflow. Executing intrafraction repositioning reduced margin requirements by 0.73 ± 0.07 mm.

CONCLUSIONS

Clinical data suggest that the uniform 5.0-mm margin is conservative for our workflow. Using modern techniques such as 4D CT, 4D CBCT, and effective motion management can significantly reduce required margins, and therefore necessary healthy tissue dose. However, the limitations of margin calculation models must be considered, and margin reduction must be approached with caution. Users should conduct a formal risk assessment prior to adopting new standard PTV margins.

Intrafraction motion and impact of margin reduction for MR-Linac online adaptive radiotherapy for pancreatic cancer treatments

INTRODUCTION

Online adaptive radiotherapy is well suited for stereotactic ablative radiotherapy (SABR) in pancreatic cancer due to considerable intrafractional tumour motion. This study aimed to assess intrafraction motion and generate adjusted planning target volume (PTV) margins required for online adaptive radiotherapy in pancreatic cancer treatment using abdominal compression on the magnetic resonance linear accelerator (MR-Linac).

METHODS

Motion monitoring images obtained from 67 fractions for 15 previously treated pancreatic cancer patients were analysed. All patients received SABR (50 Gy in five fractions) on the MR-Linac using abdominal compression. The analysis included quantification of intrafraction motion, leading to the development of adjusted PTV margins. The dosimetric impact of implementing the adjusted PTV was then evaluated in a cohort of 20 patients.

RESULTS

Intrafraction motion indicated an average target displacement of 1-3 mm, resulting in an adjusted PTV margin of 2 mm in the right-left and superior-inferior directions, and 3 mm in the anterior-posterior direction. Plans incorporating these adjusted margins consistently demonstrated improved dose to target volumes, with improvements averaging 1.5 Gy in CTV D99%, 4.9 Gy in PTV D99% and 1.2 Gy in PTV-high D90%, and better sparing of the organs at risk (OAR).

CONCLUSIONS

The improved target volume coverage and reduced OAR dose suggest potential for reducing current clinical margins for MR-Linac treatment. However, it is important to note that decreasing margins may reduce safeguards against geographical misses. Nonetheless, the continued integration of gating systems on MR-Linacs could provide confidence in adopting reduced margins.

A systematic review of the impact of abdominal compression and breath-hold techniques on motion, inter-fraction set-up errors, and intra-fraction errors in patients with hepatobiliary and pancreatic malignancies

BACKGROUND AND PURPOSE

Reducing motion is vital when radiotherapy is used to treat patients with hepatobiliary (HPB) and pancreatic malignancies. Abdominal compression (AC) and breath-hold (BH) techniques aim to minimise respiratory motion, yet their adoption remains limited, and practices vary. This review examines the impact of AC and BH on motion, set-up errors, and patient tolerability in HPB and pancreatic patients.

MATERIALS AND METHODS

This systematic review, conducted using PRISMA and PICOS criteria, includes publications from January 2015 to February 2023. Eligible studies focused on AC and BH interventions in adults with HPB and pancreatic malignancies. Endpoints examined motion, set-up errors, intra-fraction errors, and patient tolerability. Due to study heterogeneity, Synthesis Without Meta-Analysis was used, and a 5 mm threshold assessed the impact of motion mitigation.

RESULTS

In forty studies, 14 explored AC and 26 BH, with 20 on HPB, 13 on pancreatic, and 7 on mixed cohorts. Six studied pre-treatment, 22 inter/intra-fraction errors, and 12 both. Six AC pre-treatment studies showed > 5 mm motion, and 4 BH and 2 AC studies reported > 5 mm inter-fraction errors. Compression studies commonly investigated the arch and belt, and DIBH was the predominant BH technique. No studies compared AC and BH. There was variation in the techniques, and several studies did not follow standardised error reporting. Patient experience and tolerability were under-reported.

CONCLUSION

The results indicate that AC effectively reduces motion, but its effectiveness may vary between patients. BH can immobilise motion; however, it can be inconsistent between fractions. The review underscores the need for larger, standardised studies and emphasizes the importance of considering the patient's perspective for tailored treatments.

Feasibility of abdominal fat quantification on MRI and impact on effectiveness of abdominal compression for radiotherapy motion management

The impact of fat on abdominal compression effectiveness in abdominal cancers was determined using magnetic resonance imaging (MRI). Visceral and subcutaneous fat were delineated on T2W 3D MRI, and motion change with compression was measured on 2D cine MRI. Results from 16 participants showed no correlation between fat percentage, body mass index (BMI), and motion change. Median BMI was 28.7 (SD, 4.9). Mean motion reduction was 7.8 mm (IQR, 5.0; p = 0.001) with compression. While no direct link was found between fat, BMI, and compression effectiveness, abdominal compression remains crucial for motion management in radiotherapy planning, providing dosimetric benefits.

Intrafraction Motion Management With MR-Guided Radiation Therapy

High quality radiation therapy requires highly accurate and precise dose delivery. MR-guided radiotherapy (MRgRT), integrating an MRI scanner with a linear accelerator, offers excellent quality images in the treatment room without subjecting patient to ionizing radiation. MRgRT therefore provides a powerful tool for intrafraction motion management. This paper summarizes different sources of intrafraction motion for different disease sites and describes the MR imaging techniques available to visualize and quantify intrafraction motion. It provides an overview of MR guided motion management strategies and of the current technical capabilities of the commercially available MRgRT systems. It describes how these motion management capabilities are currently being used in clinical studies, protocols and provides a future outlook.

Mitigation of motion-induced artifacts in cone beam computed tomography using deep convolutional neural networks

BACKGROUND

Cone beam computed tomography (CBCT) is often employed on radiation therapy treatment devices (linear accelerators) used in image-guided radiation therapy (IGRT). For each treatment session, it is necessary to obtain the image of the day in order to accurately position the patient and to enable adaptive treatment capabilities including auto-segmentation and dose calculation. Reconstructed CBCT images often suffer from artifacts, in particular those induced by patient motion. Deep-learning based approaches promise ways to mitigate such artifacts.

PURPOSE

We propose a novel deep-learning based approach with the goal to reduce motion induced artifacts in CBCT images and improve image quality. It is based on supervised learning and includes neural network architectures employed as pre- and/or post-processing steps during CBCT reconstruction.

METHODS

Our approach is based on deep convolutional neural networks which complement the standard CBCT reconstruction, which is performed either with the analytical Feldkamp-Davis-Kress (FDK) method, or with an iterative algebraic reconstruction technique (SART-TV). The neural networks, which are based on refined U-net architectures, are trained end-to-end in a supervised learning setup. Labeled training data are obtained by means of a motion simulation, which uses the two extreme phases of 4D CT scans, their deformation vector fields, as well as time-dependent amplitude signals as input. The trained networks are validated against ground truth using quantitative metrics, as well as by using real patient CBCT scans for a qualitative evaluation by clinical experts.

RESULTS

The presented novel approach is able to generalize to unseen data and yields significant reductions in motion induced artifacts as well as improvements in image quality compared with existing state-of-the-art CBCT reconstruction algorithms (up to +6.3 dB and +0.19 improvements in peak signal-to-noise ratio, PSNR, and structural similarity index measure, SSIM, respectively), as evidenced by validation with an unseen test dataset, and confirmed by a clinical evaluation on real patient scans (up to 74% preference for motion artifact reduction over standard reconstruction).

CONCLUSIONS

For the first time, it is demonstrated, also by means of clinical evaluation, that inserting deep neural networks as pre- and post-processing plugins in the existing 3D CBCT reconstruction and trained end-to-end yield significant improvements in image quality and reduction of motion artifacts.

What do we want? Training! When do we want it? Now? A training needs analysis for adaptive radiotherapy for therapeutic radiographers

INTRODUCTION

Therapeutic radiographers (TRs) have adapted to the changing requirements and demands of the oncology service and in response to advanced techniques such as on-line adaptive MRI-guided radiotherapy (MRIgRT). The skills required for MRIgRT would benefit many TRs not just those involved in this technique. This study presents the results of a training needs analysis (TNA) for the required MRIgRT skills in readiness for training TRs for current and future practice.

METHODS

A UK-based TNA was used to ask TRs about their knowledge and experience with essential skills required for MRIgRT based on previous investigations into the topic. A five-point Likert scale was used for each of the skills and the difference in values were used to calculate the training need for current and future practice.

RESULTS

261 responses were received (n = 261). The skill rated the most important to current practice was CBCT/CT matching and/or fusion. The current highest priority needs were radiotherapy planning and radiotherapy dosimetry. The skill rated the most important to future practice was CBCT/CT matching and/or fusion. The future highest priority needs were MRI acquisition and MRI Contouring. Over 50% of participants wanted training or additional training in all skills. There was an increase in all values for skills investigated from current to future roles.

CONCLUSION

Although the examined skills were viewed as important to current roles, the future training needs, both overall and high priority, were different compared to current roles. As the 'future' of radiotherapy can arrive rapidly, it is essential that training is delivered appropriately and timely. Before this can occur, there must be investigations into the method and delivery of this training.

IMPLICATIONS FOR PRACTICE

Role development. Education changes for therapeutic radiographers.