Online adaptive MR-guided radiotherapy for rectal cancer; feasibility of the workflow on a 1.5T MR-linac: clinical implementation and initial experience

Intven, Martijn; Otterloo, Sophie R de Mol van; Mook, Stella; Doornaert, P.; Breugel, Eline N. de Groot-van; Sikkes, G.G.; Willemsen-Bosman, M.E.; Zijp, H M van; Tijssen, Rob H N

doi:10.1016/j.radonc.2020.09.024

Cited by 64 publications

(53 citation statements)

References 47 publications

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“…When selecting a reference plan for our online work ow the VMAT technique was favored for its fast delivery over IMRT. The 5-eld IMRT technique used for delivery by Intven et al 21 resulted in a median of 7 minutes (IQR 1) treatment delivery time compared to an average of 4 minutes (range 3-6) in our study.…”

Section: Treatment Timescontrasting

confidence: 47%

“…Intven et al 21 was the rst to report daily adaptive radiotherapy for rectal cancer patients treated with 5 x 5 Gy and similar target volumes and showed it was a feasible strategy for MR guided radiotherapy.…”

Section: Treatment Timesmentioning

confidence: 99%

“…For now there is no comparing literature for using CBCT images in an online adaptive work ow, it is commonly performed with an MR-Linac. MR guided radiotherapy has the potential bene t of higher image quality compared to CBCT scans 21 . Possibly, the MRI image quality could result in more accurate re-delineation of contours which needs to be investigated.…”

Section: Imagingmentioning

confidence: 99%

“…Intven et al 21 report that their work ow started with recontouring performed by radiation oncologists for the rst 12 patients. As of patient 13 RTTs were trained followed by a gradual shift in the responsibility of the recontouring to RTTs.…”

Section: Resourcesmentioning

confidence: 99%

“…Whether margins can be reduced further needs to be investigated. Intven et al 21 started using 10 mm PTV margin around the mesorectum in all directions and 8 mm PTV margin around lymph node regions. After 25 patients they reduced margins to the mesorectum to 4 mm in all directions except for 6 mm in CC and ventral direction.…”

Section: Margins and Intra Fraction Motionmentioning

confidence: 99%

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Feasibility of Conebeam CT-based Online Adaptive Radiotherapy for Neoadjuvant Treatment of Rectal Cancer.

Jong

Visser

Wieringen

et al. 2021

Preprint

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BackgroundOnline adaptive radiotherapy has the potential to reduce toxicity for patients treated for rectal cancer because smaller planning target volumes (PTV) margins around the entire clinical target volume (CTV) are required. The aim of this study is to describe the first clinical experience of a Conebeam CT(CBCT)-based online adaptive workflow, evaluating timing of different steps in the workflow, plan quality, target coverage and patient compliance.MethodsTwelve consecutive patients eligible for 5 x 5 Gy pre-operative radiotherapy were treated on a ring-based linear accelerator with a multidisciplinary team present at the treatment machine for each fraction. The accelerator is operated using an integrated software platform for both treatment planning and delivery. In all directions for all CTVs a PTV margin of 5 mm was used, except for the cranial/caudal borders of the total CTV where a margin of 8mm was applied. A reference plan was generated based on a single planning CT. After aligning the patient the online adaptive procedure started with acquisition of a CBCT. The planning CT scan was registered to the CBCT using deformable registration and a synthetic CT scan was generated. With the support of artificial intelligence, structure guided deformation and the synthetic CT scan contours were adapted by the system to match the anatomy on the CBCT. If necessary, these contours were adjusted before a new plan was generated. A second and third CBCT were acquired to validate the new plan with respect to CTV coverage just before and after treatment delivery, respectively. Treatment was delivered using volumetric modulated arc treatment (VMAT). All steps in this process defined and timed. ResultsOn average the timeslot needed at the treatment machine was 34 minutes. The process of acquiring a CBCT, evaluating and adjusting the contours, creating the new plan and verifying the CTV on the CBCT scan took on average 20 minutes. Including delivery and post treatment verification this was 26 minutes. Manual adjustments of the target volumes were necessary in 50% of fractions. Plan quality, target coverage and patient compliance were excellent.ConclusionsFirst clinical experience with CBCT-based online adaptive radiotherapy shows it is feasible for rectal cancer. Trial registrationMedical Research Involving Human Subjects Act (WMO) does not apply to this study and was retrospectively approved by the Medical Ethics review Committee of the Academic Medical Center (W21_087 # 21.097; Amsterdam University Medical Centers, Location Academic Medical Center, Amsterdam, The Netherlands).

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Section: Treatment Timescontrasting

confidence: 47%

Section: Treatment Timesmentioning

confidence: 99%

Section: Imagingmentioning

confidence: 99%

Section: Resourcesmentioning

confidence: 99%

Section: Margins and Intra Fraction Motionmentioning

confidence: 99%

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Feasibility of Conebeam CT-based Online Adaptive Radiotherapy for Neoadjuvant Treatment of Rectal Cancer.

Jong

Visser

Wieringen

et al. 2021

Preprint

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Evaluation of Unity 1.5 T MR‐linac plan quality in patients with prostate cancer

Tanaka

Ishizawa

Katsuta

et al. 2023

J Applied Clin Med Phys

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The Unity magnetic resonance (MR) linear accelerator (MRL) with MR‐guided adaptive radiotherapy (MRgART) is capable of online MRgART where images are acquired on the treatment day and the radiation treatment plan is immediately replanned and performed. We evaluated the MRgART plan quality and plan reproducibility of the Unity MRL in patients with prostate cancer. There were five low‐ or moderate‐risk and five high‐risk patients who received 36.25 Gy or 40 Gy, respectively in five fractions. All patients underwent simulation magnetic resonance imaging (MRI) and five online adaptive MRI. We created plans for 5, 7, 9, 16, and 20 beams and for 60, 100, and 150 segments. We evaluated the target and organ doses for different number of beams and segments, respectively. Variation in dose constraint between the simulation plan and online adaptive plan was measured for each patient to assess plan reproducibility. The plan quality improved with the increasing number of beams. However, the proportion of significantly improved dose constraints decreased as the number of beams increased. For some dose parameters, there were statistically significant differences between 60 and 100 segments, and 100 and 150 segments. The plan of five beams exhibited limited reproducibility. The number of segments had minimal impact on plan reproducibility, but 60 segments sometimes failed to meet dose constraints for online adaptive plan. The optimization and delivery time increased with the number of beams and segments. We do not recommend using five or fewer beams for a reproducible and high‐quality plan in the Unity MRL. In addition, many number of segments and beams may help meet dose constraints during online adaptive plan. Treatment with the Unity MRL should be performed with the appropriate number of beams and segments to achieve a good balance among plan quality, delivery time, and optimization time.

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Pretreatment information–aided automatic segmentation for online magnetic resonance imaging‐guided prostate radiotherapy

et al. 2023

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BackgroundIt is necessary to contour regions of interest (ROIs) for online magnetic resonance imaging (MRI)‐guided adaptive radiotherapy (MRIgART). These updated contours are used for online replanning to obtain maximum dosimetric benefits. Contouring can be accomplished using deformable image registration (DIR) and deep learning (DL)‐based autosegmentation methods. However, these methods may require considerable manual editing and thus prolong treatment time.PurposeThe present study aimed to improve autosegmentation performance by integrating patients’ pretreatment information in a DL‐based segmentation algorithm. It is expected to improve the efficiency of current MRIgART process.MethodsForty patients with prostate cancer were enrolled retrospectively. The online adaptive MR images, patient‐specific planning computed tomography (CT), and contours in CT were used for segmentation. The deformable registration of planning CT and MR images was performed first to obtain a deformable CT and corresponding contours. A novel DL network, which can integrate such patient‐specific information (deformable CT and corresponding contours) into the segmentation task of MR images was designed. We performed a four‐fold cross‐validation for the DL models. The proposed method was compared with DIR and DL methods on segmentation of prostate cancer. The ROIs included the clinical target volume (CTV), bladder, rectum, left femur head, and right femur head. Dosimetric parameters of automatically generated ROIs were evaluated using a clinical treatment planning system.ResultsThe proposed method enhanced the segmentation accuracy of conventional procedures. Its mean value of the dice similarity coefficient (93.5%) over the five ROIs was higher than both DIR (87.5%) and DL (87.2%). The number of patients (n = 40) that required major editing using DIR, DL, and our method were 12, 18, and 7 (CTV); 17, 4, and 1 (bladder); 8, 11, and 5 (rectum); 2, 4, and 1 (left femur head); and 3, 7, and 1 (right femur head), respectively. The Spearman rank correlation coefficient of dosimetry parameters between the proposed method and ground truth was 0.972 ± 0.040, higher than that of DIR (0.897 ± 0.098) and DL (0.871 ± 0.134).ConclusionThis study proposed a novel method that integrates patient‐specific pretreatment information into DL‐based segmentation algorithm. It outperformed baseline methods, thereby improving the efficiency and segmentation accuracy in adaptive radiotherapy.

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Online adaptive MR-guided radiotherapy for rectal cancer; feasibility of the workflow on a 1.5T MR-linac: clinical implementation and initial experience

Cited by 64 publications

References 47 publications

Feasibility of Conebeam CT-based Online Adaptive Radiotherapy for Neoadjuvant Treatment of Rectal Cancer.

Feasibility of Conebeam CT-based Online Adaptive Radiotherapy for Neoadjuvant Treatment of Rectal Cancer.

Evaluation of Unity 1.5 T MR‐linac plan quality in patients with prostate cancer

Pretreatment information–aided automatic segmentation for online magnetic resonance imaging‐guided prostate radiotherapy

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