OBJECTIVE: A 4D robust optimisation (4DRO) is usually employed when the tumour respiratory motion needs to be addressed. However, it is computationally demanding, and an automated method is preferable for adaptive planning to avoid manual trial-and-error. This study proposes a 4DRO technique based on dose mimicking for automated adaptive planning. Approach: Initial plans for 4DRO intensity modulated proton therapy were created on an average CT for four patients with clinical target volume (CTV) in the lung, oesophagus, or pancreas, respectively. These plans were robustly optimised using three phases of 4DCT and accounting for setup and density uncertainties. Weekly 4DCTs were used for adaptive replanning, using a constant relative biological effectiveness (cRBE) of 1.1. Two methods were used: (1) template-based adaptive (TA) planning and (2) dose-mimicking-based adaptive (MA) planning. The plans were evaluated using variable RBE (vRBE) weighted doses and biologically consistent dose accumulation (BCDA). Main results: MA and TA plans had comparable CTV coverage except for one patient where the MA plan had a higher D98 and lower D2 but with an increased D2 in few organs at risk (OARs). CTV D98 deviations in non-adaptive plans from the initial plans were up to -7.2 percentage points (p.p.) in individual cases and -1.8 p.p. when using BCDA. For the OARs, MA plans showed a reduced mean dose and D2 compared to the TA plan, with few exceptions. The vRBE-weighted accumulated doses had a mean dose and D2 difference of up to 0.3 Gy and 0.5 Gy, respectively, in the OARs with respect to cRBE-weighted dose. Significance: MA plans indicate better performance in target coverage and OAR dose sparing compared to the TA plans in 4DRO adaptive planning. Moreover, MA method is capable of handling both forms of anatomical variation, namely, changes in density and relative shifts in the position of OARs.

To assess the performance of a knowledge-based planning (KBP) model for generating intensity-modulated proton therapy (IMPT) treatment plans as part of an adaptive radiotherapy (ART) strategy for patients with high-risk prostate cancer. A knowledge-based planning (KBP) model for proton adaptive treatment plan generation was developed based on thirty patient treatment plans utilizing RapidPlanTM PT (Varian Medical Systems, Palo Alto, CA). The model was subsequently validated using an additional eleven patient cases. All patients in the study were administered a prescribed dose of 70.2 Gy to the prostate and seminal vesicle (CTV70.2), along with 46.8 Gy to the pelvic lymph nodes (CTV46.8) through simultaneous integrated boost (SIB) technique. To assess the quality of the validation knowledge-based proton plans (KBPPs), target coverage and organ-at-risk (OAR) dose-volume constraints were compared against those of clinically used expert plans using paired t-tests. The KBP model training statistics (R2) (mean ± SD, 0.763 ± 0.167, range, 0.406 to 0.907) and χ² values (1.162 ± 0.0867, 1.039-1.253) indicate acceptable model training quality. Moreover, the average total treatment planning optimization and calculation time for adaptive plan generation is approximately 10 minutes. The CTV70.2 D98% for the KBPPs (mean ± SD, 69.1 ± 0.08 Gy) and expert plans (69.9 ± 0.04 Gy) shows a significant difference (p < 0.05) but are both within 1.1 Gy of the prescribed dose which is clinically acceptable. While the maximum dose for some organs-at-risk (OARs) such as the bladder and rectum is generally higher in the KBPPs, the doses still fall within clinical constraints. Among all the OARs, most of them received comparable results to the expert plan, except the cauda equina Dmax, which shows statistical significance and was lower in the KBPPs than in expert plans (48.5 ± 0.06 Gy vs 49.3 ± 0.05 Gy). The generated KBPPs were clinically comparable to manually crafted plans by expert treatment planners. The adaptive plan generation process was completed within an acceptable timeframe, offering a quick same-day adaptive treatment option. Our study supports the integration of KBP as a crucial component of an ART strategy, including maintaining plan consistency, improving quality, and enhancing efficiency. This advancement in speed and adaptability promises more precise treatment in proton ART.

Neoadjuvant chemotherapy, when combined with radiotherapy, serves as an optional treatment for patients with locally advanced sigmoid colon cancer and is usually performed in conjunction with complete mesocolic excision. The substantial movement of surrounding organs in cases of sigmoid colon cancer frequently leads to toxicity in normal tissues. The present report details the case of a 76-year-old man diagnosed with locally advanced sigmoid colon cancer. Initially, treatment using the Tomotherapy Hi-Art system was selected; however, during image guidance from the first to the sixth fractions, the tumor location underwent a marked change, exceeding the range of the planning target volume. Efforts to recapture the image were unsuccessful, leading to a decision to transition the patient to the MRIdian system for daily treatment with online adaptive radiotherapy. The positional variations in the tumor were evident in each treatment using the MRIdian system, with mean shifts of 2.58 cm in the right-left direction, 1.24 cm in the cranial-caudal direction and 0.40 cm in the anterior-posterior direction. The mean time from the entry of the patient to treatment completion was 41 min. Adaptive treatment plans were performed for all 19 fractions, with two treatments repeated due to the tumor moving out of tracking range. Following irradiation using the MRIdian system, the gross tumor volume decreased by 62%. Notably, the patient experienced no side effects during treatment. A CT scan conducted 3 months after radiotherapy revealed a marked reduction in the tumor size, consistent with a partial response, leading to the scheduling of surgery. Following surgery, a CT scan after 6 months revealed no local recurrence in the surgical bed region. The findings in the present case support the feasibility of implementing an adaptive treatment plan using the MRIdian system for locally advanced sigmoid colon cancer in the context of neoadjuvant chemoradiotherapy.

UNASSIGNED: 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.
UNASSIGNED: 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.
UNASSIGNED: 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.

UNASSIGNED: To identify any clinical or dosimetric parameters that predict which individuals may benefit from on-table adaptation during pancreas stereotactic body radiotherapy (SBRT) with MRI-guided radiotherapy.
UNASSIGNED: This was a retrospective study of patients undergoing MRI-guided SBRT from 2016 to 2022. Pre-treatment clinical variables and dosimetric parameters on the patient\'s simulation scan were recorded for each SBRT course, and their ability to predict for on-table adaptation was analyzed using ordinal logistic regression. The outcome measure was number of fractions adapted.
UNASSIGNED: Sixty-three SBRT courses consisting of 315 fractions were analyzed. Median prescription dose was 40 Gy in five fractions (range, 33-50 Gy); 52% and 48% of courses were prescribed ≤40 Gy and >40 Gy, respectively. The median minimum dose delivered to 95% (D95) of the gross tumor volume (GTV) and planning target volume (PTV) was 40.1 Gy and 37.0 Gy, respectively. Median number of fractions adapted per course was three, with 58% (183 out of 315) total fractions adapted. On univariable analysis, the prescription dose (>40 Gy vs ≤40 Gy), GTV volume, stomach V20 and V25, duodenum V20 and dose maximum, large bowel V33 and V35, GTV dose minimum, PTV dose minimum, and gradient index were significant determinants for adaptation (all p < 0.05). On multivariable analysis, only the prescription dose was significant (adjusted odds ratio 19.7, p = 0.005), but did not remain significant after multiple test correction (p = 0.08).
UNASSIGNED: The likelihood of needing on-table adaptation could not be reliably predicted a priori using pre-treatment clinical characteristics, dosimetry to nearby organs at risk, or other dosimetric parameters based on the patient\'s anatomy at the time of simulation, suggesting the critical importance of day-to-day variations in anatomy and increasing access to adaptive technology for pancreas SBRT. A higher (ablative) prescription dose was associated with increased use of adaptation.

BACKGROUND: Gastrointestinal (GI) tract motility is one of the main sources for intra/inter-fraction variability and uncertainty in radiation therapy for abdominal targets. Models for GI motility can improve the assessment of delivered dose and contribute to the development, testing, and validation of deformable image registration (DIR) and dose-accumulation algorithms.
OBJECTIVE: To implement GI tract motion in the 4D extended cardiac-torso (XCAT) digital phantom of human anatomy.
METHODS: Motility modes that exhibit large amplitude changes in the diameter of the GI tract and may persist over timescales comparable to online adaptive planning and radiotherapy delivery were identified based on literature research. Search criteria included amplitude changes larger than planning risk volume expansions and durations of the order of tens of minutes. The following modes were identified: peristalsis, rhythmic segmentation, high amplitude propagating contractions (HAPCs), and tonic contractions. Peristalsis and rhythmic segmentations were modeled by traveling and standing sinusoidal waves. HAPCs and tonic contractions were modeled by traveling and stationary Gaussian waves. Wave dispersion in the temporal and spatial domain was implemented by linear, exponential, and inverse power law functions. Modeling functions were applied to the control points of the nonuniform rational B-spline surfaces defined in the reference XCAT library. GI motility was combined with the cardiac and respiratory motions available in the standard 4D-XCAT phantom. Default model parameters were estimated based on the analysis of cine MRI acquisitions in 10 patients treated in a 1.5T MR-linac.
RESULTS: We demonstrate the ability to generate realistic 4D multimodal images that simulate GI motility combined with respiratory and cardiac motion. All modes of motility, except tonic contractions, were observed in the analysis of our cine MRI acquisitions. Peristalsis was the most common. Default parameters estimated from cine MRI were used as initial values for simulation experiments. It is shown that in patients undergoing stereotactic body radiotherapy for abdominal targets, the effects of GI motility can be comparable or larger than the effects of respiratory motion.
CONCLUSIONS: The digital phantom provides realistic models to aid in medical imaging and radiation therapy research. The addition of GI motility will further contribute to the development, testing, and validation of DIR and dose accumulation algorithms for MR-guided radiotherapy.

OBJECTIVE: To establish and evaluate a (quasi) real-time automated treatment planning (RTTP) strategy utilizing a one-step full 3D fluence map prediction model based on a nonorthogonal convolution operation for rectal cancer radiotherapy.
METHODS: The RTTP approach directly extracts 3D projections from volumetric CT and anatomical data according to the beam incident direction. A 3D deep learning model with a nonorthogonal convolution operation was established that takes projections in cone beam space as input, extracts the features along and around the ray-trace path, and outputs a predicted fluence map (PFM) for each beam. The PFM is then converted to the MLC sequence with deliverable MUs to generate the final treatment plan. A total of 314 rectal adenocarcinoma patients with 2198 projection data samples were used in model training and validation. An extra 20 patients were used to test the feasibility of the RTTP method by comparing the plan quality, efficiency, deliverability performance, and physician blinded review results with the manual plans.
RESULTS: Overall, the RTTP plans met the clinical dose criteria for target coverage, conformity, homogeneity, and organ-at-risk dose sparing. Compared to manual plans, the RTTP plans showed increases in PTV D1% by only 2.33% (p < 0.001) and a decrease in PTV D99% by 0.45% (p < 0.05). The RTTP plans showed a dose increase in the bladder, with a V50 of 14.01 ± 11.75% vs. 10.74 ± 8.51%, respectively, and no significant increases in the femoral head with the mean dose. The planning efficiency was improved in RTTP planning, with 39 s vs. 944 s in fluence map generation; the deliverability performance was saved by 1.91% (p < 0.001) in total MU. According to the blinded plan review by our physician, 55% of RTTP plans can be directly used in clinical radiotherapy treatment.
CONCLUSIONS: The quasi RTTP method improves the planning efficiency and deliverability performance while maintaining a plan quality close to that of the optimized manual plans in rectal radiotherapy.

Using an magnetic resonance linear accelerator (MR-Linac) may improve the precision of visible tumor boosting with ultra-hypofractionation by accounting for daily positional changes in the target and organs at risk (OAR).
Fifteen patients with prostate cancer and an MR-detected dominant lesion were treated on the MR-Linac with stereotactic body radiation (SBRT) to 40 Gy in 5 fractions, boosting the gross tumor volume (GTV) to 45 Gy with daily adaptive planning. Imaging was acquired again after initial planning (verification scan), and immediately after treatment (post-treatment scan). Prior to beam-on, additional adjustments were made on the verification scan. Contours were retrospectively adjusted on verification and post-treatment scans, and the daily plan recalculated on these scans to estimate the true dose delivered.
The median prostate D95% for plan 1, 2 and 3 was 40.3 Gy, 40.5 Gy and 40.3 Gy and DIL D95% was 45.7 Gy, 45.2 Gy and 44.6 Gy, respectively. Bladder filling was associated with reduced GTV coverage (p = 0.03, plan 1 vs 2) and prostate coverage (p = 0.03, plan 2 vs 3). The D0.035 cc constraint was exceeded on verification and post-treatment plans in 24 % and 33 % of fractions for the urethra, 31 % and 45 % for the bladder, and 35 % and 25 % for the rectum, respectively.
MR-Linac guided, daily adaptive SBRT with focal boosting of the GTV yields acceptable planned and delivered dosimetry. Adaptive planning with a MR-Linac may reliably deliver the prescribed dose to the intended tumor target.

Radiotherapy is the primary treatment modality for nasopharyngeal carcinoma (NPC). Successful curative treatment requires optimal radiotherapy planning and precise beam delivery that maximizes locoregional control while minimizing treatment-related side effects. In this article, we highlight considerations in target delineation, radiation dose, and the adoption of technological advances with the aim of optimizing the benefits of radiotherapy in NPC patients.

UNASSIGNED: Pancreatic neuroendocrine tumor (NET) is rare, and the majority presents late in their clinical course. Here, we present a huge locally advanced pancreatic NET having Hi-Art helical Tomotherapy that resulted in a 68% reduction in target volume during adaptive image-guided radiotherapy (IGRT).
UNASSIGNED: A 63-year-old man without any history of systemic disease developed voiding difficulty for several months. Associated symptoms included poor appetite, nausea, distended abdomen, and body weight loss. Further magnetic resonance imaging showed a large multilobulated tumor in the left upper abdomen. Tumor biopsy revealed well-differentiated, grade 2, neuroendocrine tumor. Complete resection was unattainable. Therefore, Lanreotide was prescribed initially. However, tumor progression up to the greatest diameter of 18 cm was noted on computed tomography 5 months later. Thus, he stopped Lanreotide and commenced on concurrent chemoradiotherapy (CCRT). With a total dose of 70 Gy in 35 fractions, we generated two adaptive treatment plans during the whole course. Laparoscopic subtotal pancreatectomy with spleen preservation was performed after neoadjuvant CCRT. It has been more than 3 years after IGRT, and he remains cancer free and reports no side effects during regular follow-ups.
UNASSIGNED: Tomotherapy caused tumor size reduction and hence facilitated surgical possibility for this originally unresectable pancreatic NET. Neoadjuvant IGRT incorporated with adaptive treatment planning enhanced delivery accuracy. In this case of pancreatic NET resistant to Lanreotide, inter-fractional tumor regression from 1910 to 605 cc (68%) was documented.