Organs At Risk Research Articles

Bowel bag sparing in palliative radiotherapy (pRT) of rectal cancer (rCa): Tradeoff between organs at risk (OARs) and use of AI to reduce radiation oncologist (RO) workload.

e15615 Background: We retrospectively studied the potential to reduce bowel toxicity after pRT of rCa using a bowel dose (BD) minimization strategy; also its effect on dose to remaining normal tissues (NT) and pelvic bone marrow (PBM). Finally, we studied the use of AI to reduce the RO workload. Methods: 25 consecutive rCa patients (pts) previously treated with pRT were included. Their treatments were planned without consideration to BD. The following OARs were manually segmented retrospectively: Bowel Bag (BB-M) excluding PTV, PBM (PBM-M), and NT defined as the patient contour excluding PTV and BB-M. The AI-Rad Companion software was used to autosegment: Bowel Loops (BL-AI) and PBM (PBM-AI). For the 25 pts, two Pareto optimal treatment plans (5 Gy x 5) were generated with the Monaco treatment planning system. The first plan (Reference) was optimized aiming to limit dose outside the PTV. The second plan (Opt-BB-M) was optimized aiming firstly to limit BB-M dose and secondly to limit NT dose. A third plan (Opt-BL-AI) was generated for the 10 worst-off pts (in terms of BD) aiming instead to limit BL-AI dose. Two volume-at-dose (VD) metrics (V18Gy, V10Gy) were used as endpoints. Endpoint differences (ΔVD-OAR) were tested using one-sided Wilcoxon signed-rank tests. Spearman (rs) and Pearson (r) correlation coefficients were used to study correlation between variables (ΔVD-BB vs. ΔVD-BM, and ΔVD-BB vs. ΔVD-NT). Dice Similarity Coefficient (DCS) was used to compare PBM-M and PBM-AI. Results: After reoptimization, BB-M VD (V18Gy; V10Gy) was lower (p < 0.001; p < 0.001), PBM-M VD was higher (p = 0.002; p < 0.001), and NT VD was higher (p < 0.001; p < 0.001). For BB-M, ΔV18Gy and ΔV10Gy (median, min, max) were (-4, -46, 0) cm3 and (-33, -254, 0) cm3; for PBM-M: (+2, -4, +56) cm3 and (+33, -6, +189) cm3; for NT: (+10, -43, +194) cm3 and (+146, -18, +614) cm3. Table 1 presents results for the 10 worst-off pts. Medium/strong correlations were found for ΔV18Gy-BB vs. ΔV18Gy-PBM (rs = -0.72, p < 0.001; r = -0.74, p < 0.001), ΔV10Gy-BB vs. ΔV10Gy-PBM (rs = -0.66, p < 0.001; r = -0.32, p = 0.11), ΔV18Gy-BB vs. ΔV18Gy-NT (rs = -0.74, p < 0.001; r = -0.74, p < 0.001), ΔV10Gy-BB vs. ΔV10Gy-NT (rs = -0.74, p < 0.001; r = -0.51, p = 0.009). The DSC (median, min, max) for PBL was (92%, 87%, 94%). Conclusions: Bowel dose in pRT of rCa can be reduced at the expense of increasing dose to PBM and other NT. AI tools can be used effectively to limit RO workload. [Table: see text]

MRI-Linac radiation therapy outcomes in patients with prostate, breast and other advanced malignancies.

e13811 Background: MR-guided radiation therapy offers an innovative approach, providing superior soft tissue contrast that enables clinicians to deliver higher doses to the target site with fewer fractions. The objective of the study is to assess objective response rates and adverse effects related to a community-based single-institution experience with the ViewRay MRIdian. Methods: An IRB-approved registrational trial was conducted at the Providence Cancer Institute starting May 2020, with data cutoff of September 2023. All patients treated underwent MR screening, and the target site(s) were treated using hypofractionated radiation therapy in ≤5 fractions. The primary endpoint was to assess adverse effects attributed to radiation therapy. Secondary measures included local recurrence-free survival (LRFS), distant metastasis-free survival (DMFS), overall survival (OS), and change in prostate-specific antigen (PSA) for patients treated definitively for prostate cancer. The assessments were performed under the guidance of experienced radiation oncologists. Results: From May 2020 to September 2023, n=257 patients received treatment on the MRIdian with a median follow-up of 430 days [range 4-1221 days]. One and 2-year LRFS was 92% and 87%, and excluding prostate and breast cancer, 83% and 70%. Definitive prostatestereotactic body radiation therapy(SBRT) was delivered to 117 patients and significantly reduced PSA (mean difference -6.27, p<0.0001), with no local failures to date. One and 2-year DMFS was 75% and 67%, though if excluding definitive prostate SBRT and partial breast irradiation, these were 48% and 33%. The OS rate at 1 and 2 years was 86% and 76%. Excluding prostate and breast cancer, the 1 and 2-year OS was 74% and 55%. Grade 3+ adverse events possibly or definitely attributable to radiation therapy were noted in 5% (n=13/257) of patients, including 2 possible treatment-associated deaths (bowel perforation following liver SBRT, and respiratory failure following lung SBRT and trastuzumab-deruxtecan systemic therapy). Conclusions: Our institutional experience with the MRIdian demonstrated high levels of local control, while overall survival was driven by out-of-field failures. Serious adverse events were infrequent, but more common in abdominal targets highlighting the need for careful planning and tight organs at risk (OAR) constraints, particularly if systemic therapy is delivered soon after radiation.

Diffeomorphic transformer-based abdomen MRI-CT deformable image registration.

Stereotactic body radiotherapy (SBRT) is a well-established treatment modality for liver metastases in patients unsuitable for surgery. Both CT and MRI are useful during treatment planning for accurate target delineation and to reduce potential organs-at-risk (OAR) toxicity from radiation. MRI-CT deformable image registration (DIR) is required to propagate the contours defined on high-contrast MRI to CT images. An accurate DIR method could lead to more precisely defined treatment volumes and superior OAR sparing on the treatment plan. Therefore, it is beneficial to develop an accurate MRI-CT DIR for liver SBRT. To create a new deep learning model that can estimate the deformation vector field (DVF) for directly registering abdominal MRI-CT images. The proposed method assumed a diffeomorphic deformation. By using topology-preserved deformation features extracted from the probabilistic diffeomorphic registration model, abdominal motion can be accurately obtained and utilized for DVF estimation. The model integrated Swin transformers, which have demonstrated superior performance in motion tracking, into the convolutional neural network (CNN) for deformation feature extraction. The model was optimized using a cross-modality image similarity loss and a surface matching loss. To compute the image loss, a modality-independent neighborhood descriptor (MIND) was used between the deformed MRI and CT images. The surface matching loss was determined by measuring the distance between the warped coordinates of the surfaces of contoured structures on the MRI and CT images. To evaluate the performance of the model, a retrospective study was carried out on a group of 50 liver cases that underwent rigid registration of MRI and CT scans. The deformed MRI image was assessed against the CT image using the target registration error (TRE), Dice similarity coefficient (DSC), and mean surface distance (MSD) between the deformed contours of the MRI image and manual contours of the CT image. When compared to only rigid registration, DIR with the proposed method resulted in an increase of the mean DSC values of the liver and portal vein from 0.850±0.102 and 0.628±0.129 to 0.903±0.044 and 0.763±0.073, a decrease of the mean MSD of the liver from 7.216±4.513mm to 3.232±1.483mm, and a decrease of the TRE from 26.238±2.769mm to 8.492±1.058mm. The proposed DIR method based on a diffeomorphic transformer provides an effective and efficient way to generate an accurate DVF from an MRI-CT image pair of the abdomen. It could be utilized in the current treatment planning workflow for liver SBRT.

Biological optimization for hybrid proton-photon radiotherapy

Objective. Hybrid proton-photon radiotherapy (RT) is a cancer treatment option to broaden access to proton RT. Additionally, with a refined treatment planning method, hybrid RT has the potential to offer superior plan quality compared to proton-only or photon-only RT, particularly in terms of target coverage and sparing organs-at-risk (OARs), when considering robustness to setup and range uncertainties. However, there is a concern regarding the underestimation of the biological effect of protons on OARs, especially those in close proximity to targets. This study seeks to develop a hybrid treatment planning method with biological dose optimization, suitable for clinical implementation on existing proton and photon machines, with each photon or proton treatment fraction delivering a uniform target dose. Approach. The proposed hybrid biological dose optimization method optimized proton and photon plan variables, along with the number of fractions for each modality, minimizing biological dose to the OARs and surrounding normal tissues. To mitigate underestimation of hot biological dose spots, proton biological dose was minimized within a ring structure surrounding the target. Hybrid plans were designed to be deliverable separately and robustly on existing proton and photon machines, with enforced uniform target dose constraints for the proton and photon fraction doses. A probabilistic formulation was utilized for robust optimization of setup and range uncertainties for protons and photons. The nonconvex optimization problem, arising from minimum monitor unit constraint and dose-volume histogram constraints, was solved using an iterative convex relaxation method. Main results. Hybrid planning with biological dose optimization effectively eliminated hot spots of biological dose, particularly in normal tissues surrounding the target, outperforming proton-only planning. It also provided superior overall plan quality and OAR sparing compared to proton-only or photon-only planning strategies. Significance. This study presents a novel hybrid biological treatment planning method capable of generating plans with reduced biological hot spots, superior plan quality to proton-only or photon-only plans, and clinical deliverability on existing proton and photon machines, separately and robustly.

Stereotactic Body Radiotherapy (SBRT) to Localised Prostate Cancer in the Era of MRI-Guided Adaptive Radiotherapy: Doses Delivered in the HERMES Trial Comparing Two- and Five-Fraction Treatments.

HERMES is a phase II trial of MRI-guided daily-adaptive radiotherapy (MRIgART) randomising men with localised prostate cancer to either 2-fractions of SBRT with a boost to the tumour or 5-fraction SBRT. In the context of this highly innovative regime the dose delivered must be carefully considered. The first ten patients recruited to HERMES were analysed in order to establish the dose received by the targets and organs at risk (OARS) in the context of intrafraction motion. A regression analysis was performed to measure how the volume of air within the rectum might further impact rectal dose secondary to the electron return effect (ERE). One hundred percent of CTV target objectives were achieved on the MRI taken prior to beam-on-time. The post-delivery MRI showed that high-dose CTV coverage was achieved in 90% of sub-fractions (each fraction is delivered in two sub-fractions) in the 2-fraction cohort and in 88% of fractions the 5-fraction cohort. Rectal D1 cm3 was the most exceeded constraint; three patients exceeded the D1 cm3 < 20.8 Gy in the 2-fraction cohort and one patient exceeded the D1 cm3 < 36 Gy in the 5-fraction cohort. The volume of rectal gas within 1 cm of the prostate was directly proportional to the increase in rectal D1 cm3, with a strong (R = 0.69) and very strong (R = 0.90) correlation in the 2-fraction and 5-fraction cohort respectively. Dose delivery specified in HERMES is feasible, although for some patients delivered doses to both target and OARs may vary from those planned.

Modulated Arc Therapy for hippocampal-avoidance whole brain radiation therapy: planning comparison with intensity modulated Radiation Therapy.

This study aimed to evaluate the modulated arc therapy (mARC) technique as a planning and treatment option for hippocampal sparing whole brain radiotherapy (HS-WBRT) following the Radiation Therapy Oncology Group (RTOG) 0933 dosimetric criteria. Computed tomography (CT) and magnetic resonance imaging (MRI) were selected retrospectively for 15 patients. Two types of plans were created for each patient, namely an intensity-modulated radiation therapy (IMRT) and a mARC plan. IMRT and mARC plans were compared in terms of plan quality indices, absorbed dose to organs at risk (OARs), number of monitor units (MUs), and treatment time. All plans in both techniques were considered clinically acceptable for treatment. However, IMRT plans presented a higher conformity (p = 0.01) as well as a higher homogeneity as compared to mARC plans, but this difference was not statistically significant (p > 0.05). In terms of the preservation of the hippocampus, it was observed that the IMRT plans achieved significantly lower doses for both 100% of its volume and for its maximum dose (p < 0.001). The evaluation of the remaining OARs showed that the IMRT technique resulted in lower doses, and significant differences were observed for the following organs: left cochlea (p < 0.001), left eye (p < 0.001), right eye (p = 0.03), both lenses of the eye (p < 0.001), and right optic nerve (p = 0.02). Despite these differences, the absolute differences in all dosimetric parameters were low enough to bear any clinical relevance. A drastic (close to 65%) and significant (p < 0.001) decrease was observed in the number of MUs for the mARC plans. This resulted in a substantial decrease in treatment time (60.45%, p < 0.001). It is concluded that the mARC technique is a feasible planning and treatment solution for HS-WBRT that meets the RTOG 0933 criteria. The main advantage of using mARC over IMRT for HS-WBRT is the considerable reduction in MUs and treatment time.

Dose-Painting Proton Radiotherapy Guided by Functional MRI in Non-enhancing High-Grade Gliomas

AimsThis study aimed to demonstrate the feasibility and evaluate the dosimetric effect and clinical impact of dose-painting proton radiotherapy (PRT) guided by functional MRI in non-enhancing high-grade gliomas (NE-HGGs). Materials and methodsThe 3D-ASL and T2 FLAIR MR images of ten patients with NE-HGGs before radiotherapy were studied retrospectively. The hyperintensity on T2 FLAIR was used to generate the planning target volume (PTV), and the high-perfusion volume on 3D-ASL (PTV-ASL) was used to generate the simultaneous integrated boost (SIB) volume. Each patient received pencil beam scanning PRT and photon intensity-modulated radiotherapy (IMRT). There were five plans in each modality: (1) Uniform plans (IMRT60 vs. PRT60): 60Gy in 30 fractions to the PTV. (2)–(5) SIB plans (IMRT72, 84, 96, 108 vs. PRT72, 84, 96, 108): Uniform plan plus additional dose boost to PTV-ASL in 30 fractions to 72, 84, 96, 108 Gy. The dosimetric differences between various plans were compared. The clinical effects of target volume and organs at risk (OARs) were assessed using biological models for both tumor control probability (TCP) and normal tissue complication probability (NTCP). ResultsCompared with the IMRT plan, the D2 and D50 of the PRT plans with the same prescription dose increased by 1.27–4.12% and 0.64–2.01%, respectively; the R30 decreased by > 32%; the dose of brainstem and chiasma decreased by > 27% and >32%; and the dose of normal brain tissue (Br-PTV), optic nerves, eyeballs, lens, cochlea, spinal cord, and hippocampus decreased by > 50% (P < 0.05). The maximum necessary dose was 96GyE to achieve >98% TCP for PRT, and it was 84Gy to achieve >91% TCP for IMRT. The average NTCP of Br-PTV was 1.30% and 1.90% for PRT and IMRT at the maximum dose escalation, respectively. The NTCP values of the remaining OARs approached zero in all PRT plans. ConclusionThe functional MRI-guided dose escalation using PRT is feasible while sparing the OARs constraints and demonstrates a potential clinical benefit by improving TCP with no or minimal increase in NCTP for tissues outside the PTV. This retrospective study suggested that the use of PRT-based SIB guided by functional MRI may represent a strategy to provide benefits for patients with NE-HGGs.

Stereotactic Magnetic Resonance-Guided Daily Adaptive SABR (SMART) for Localised Non-Metastatic Pancreatic Cancer: First Reported Clinical Outcomes From the UK

AimsPrognosis of locally advanced pancreatic cancer (LAPC) remains poor with limited therapeutic options. Radiation therapy in pancreatic cancer has been restricted by the disease's proximity to radiosensitive organs at risk (OAR). However, stereotactic magnetic resonance-guided adaptive radiation therapy (SMART) has demonstrated promise in delivering ablative doses safely. We sought to report clinical outcomes from a UK-based Compassionate Access Programme that provided access to SMART to patients with LAPC. Materials and methodsThis was a registry retrospective study conducted at a single centre with access to SMART. Patients with LAPC were treated with prescription dose of 40 Gy in 5 fractions. The planning objective was that 98% of PTV received ≥95% of the prescribed dose, prioritising duodenal, stomach and bowel UK SABR consortium constraints. Daily online adaptation was performed using magnetic resonance guidance and on-table re-optimisation. 0–3 months and > 3-month post-treatment-related toxicities, local progression-free survival, metastatic-free survival and overall survival were evaluated. Results55 patients were treated with SMART at our institution from 2020 to 2022. Median follow-up from date of diagnosis was 17 months (range 5–37 months). Median age was 69.87% of patients underwent induction chemotherapy. 71% of patients reported 0–1 grade acute toxicity only. No grade >3 acute toxicity was reported. 5 patients (9%) reported a grade 3 toxicity (fatigue, nausea, abdominal pain, duodenal stricture). No grade >3 toxicity after 3 months was reported. 6 (10%) of patients had grade 3 toxicity (fatigue, nausea, abdominal pain, duodenal haemorrhage). Median local PFS post diagnosis was 17 months (95% CI 15.3–18.7). Median OS post diagnosis was 19 months (95% CI 15.9–22.1). One-year local control post SMART was 65%. ConclusionThis is the first UK-reported experience of MR-guided daily adaptive pancreatic SABR. SMART shows promise in delivering ablative doses with acceptable toxicity rates and good clinical outcomes.

Radiotherapy Plan Quality Assurance in NRG Oncology Trials for Brain and Head/Neck Cancers: An AI-Enhanced Knowledge-Based Approach.

The quality of radiation therapy (RT) treatment plans directly affects the outcomes of clinical trials. KBP solutions have been utilized in RT plan quality assurance (QA). In this study, we evaluated the quality of RT plans for brain and head/neck cancers enrolled in multi-institutional clinical trials utilizing a KBP approach. The evaluation was conducted on 203 glioblastoma (GBM) patients enrolled in NRG-BN001 and 70 nasopharyngeal carcinoma (NPC) patients enrolled in NRG-HN001. For each trial, fifty high-quality photon plans were utilized to build a KBP photon model. A KBP proton model was generated using intensity-modulated proton therapy (IMPT) plans generated on 50 patients originally treated with photon RT. These models were then applied to generate KBP plans for the remaining patients, which were compared against the submitted plans for quality evaluation, including in terms of protocol compliance, target coverage, and organ-at-risk (OAR) doses. RT plans generated by the KBP models were demonstrated to have superior quality compared to the submitted plans. KBP IMPT plans can decrease the variation of proton plan quality and could possibly be used as a tool for developing improved plans in the future. Additionally, the KBP tool proved to be an effective instrument for RT plan QA in multi-center clinical trials.

Dosimetric and NTCP analyses for selecting parotid gland cancer patients for proton therapy.

To perform a dosimetric and a normal tissue complication probability (NTCP) comparison between intensity modulated proton therapy and photon volumetric modulated arc therapy in a cohort of patients with parotid gland cancers in a post-operative or radical setting. From May 2011 to September 2021, 37 parotid gland cancers patients treated at two institutions were eligible. Inclusion criteria were as follows: patients aged ⩾ 18 years, diagnosis of parotid gland cancers candidate for postoperative radiotherapy or definitive radiotherapy, presence of written informed consent for the use of anonymous data for research purposes. Organs at risk (OARs) were retrospectively contoured. Target coverage goal was defined as D95 > 98%. Six NTCP models were selected. NTCP profiles were calculated for each patient using an internally-developed Python script in RayStation TPS. Average differences in NTCP between photon and proton plans were tested for significance with a two-sided Wilcoxon signed-rank test. Seventy-four plans were generated. A lower Dmean to the majority of organs at risk (inner ear, cochlea, oral cavity, pharyngeal constrictor muscles, contralateral parotid and submandibular gland) was obtained with intensity modulated proton therapy vs volumetric modulated arc therapy with statistical significance (p < .05). Ten (27%) patients had a difference in NTCP (photon vs proton plans) greater than 10% for hearing loss and tinnitus: among them, seven qualified for both endpoints, two patients for hearing loss only, and one for tinnitus. In the current study, nearly one-third of patients resulted eligible for proton therapy and they were the most likely to benefit in terms of prevention of hearing loss and tinnitus.

A machine learning-based approach to predict energy layer for each field in spot-scanning proton arc therapy for lung cancer: A feasibility study.

Determining the optimal energy layer (EL) for each field, under considering both dose constraints and delivery efficiency, is crucial to promoting the development of proton arc therapy (PAT) technology. This study aimed to explore the feasibility and potential clinical benefits of utilizing machine learning (ML) technique to automatically select EL for each field in PAT plans of lung cancer. Proton Bragg peak position (BPP) was employed to characterize EL. The ground truth BPPs for each field were determined using the modified ELO-SPAT framework. Features in geometric, water-equivalent thicknesses (WET) and beamlet were defined and extracted. By analyzing the relationship between the extracted features and ground truth, a polynomial regression model with L2-norm regularization (Ridge regression) was constructed and trained. The performance of the regression model was reported as an error between the predictions and the ground truth. Besides, the predictions were used to make PAT plans (PAT_PRED). These plans were compared with those using the ground truth BPPs (PAT_TRUTH) and the mid-WET of the target volumes (PAT_MID) in terms of relative biological effectiveness-weighted dose (RWD) distributions. One hundred ten patients with lung cancer, a total of 7920 samples, were enrolled retrospectively, with 5940 cases randomly selected as the training set and the remaining 1980 cases as the testing set. Nine patients (648 samples) were collected additionally to evaluate the regression model in terms of plan quality and robustness. With regard to the prediction errors, the root mean squared errors and mean absolute errors between the ML-predicted and ground truth BPPs for the testing set were 9.165 and 6.572mm, respectively, indicating differences of approximately two to three ELs. As for plan quality, the PAT_TRUTH and PAT_PRED plans performed similarly in terms of plan robustness, target coverage and organs at risk (OARs) protection, with differences smaller than 0.5Gy(RBE). This trend was also observed for dose conformity and uniformity. The PAT_MID plans produced the lowest robustness index and lowest doses to OARs, along with the highest heterogeneity index, indicating better protection for OARs, improved plan robustness, but compromised dose homogeneity. Additionally, for relatively small tumor sizes, the PAT_MID plan demonstrated a notably poor dose conformity index. Within this cohort under investigation, our study demonstrated the feasibility of using ML technique to predict ELs for each field, offering a fast (within 2 s) and memory-efficient reduced way to select ELs for PAT plan.

Multiple organ segmentation framework for brain metastasis radiotherapy

Radiotherapy is a preferred treatment for brain metastases, which kills cancer cells via high doses of radiation meanwhile hardly avoiding damage to surrounding healthy cells. Therefore, the delineation of organs-at-risk (OARs) is vital in treatment planning to minimize radiation-induced toxicity. However, the following aspects make OAR delineation a challenging task: extremely imbalanced organ sizes, ambiguous boundaries, and complex anatomical structures. To alleviate these challenges, we imitate how specialized clinicians delineate OARs and present a novel cascaded multi-OAR segmentation framework, called OAR-SegNet. OAR-SegNet comprises two distinct levels of segmentation networks: an Anatomical-Prior-Guided network (APG-Net) and a Point-Cloud-Guided network (PCG-Net). Specifically, APG-Net handles segmentation for all organs, where multi-view segmentation modules and a deep prior loss are designed under the guidance of prior knowledge. After APG-Net, PCG-Net refines small organs through the mini-segmentation and the point-cloud alignment heads. The mini-segmentation head is further equipped with the deep prior feature. Extensive experiments were conducted to demonstrate the superior performance of the proposed method compared to other state-of-the-art medical segmentation methods.

Mixed-size spot scanning with a compact large momentum acceptance superconducting (LMA-SC) gantry beamline for proton therapy

Objective. Lowering treatment costs and improving treatment quality are two primary goals for next-generation proton therapy (PT) facilities. This work will design a compact large momentum acceptance superconducting (LMA-SC) gantry beamline to reduce the footprint and expense of the PT facilities, with a novel mixed-size spot scanning method to improve the sparing of organs at risk (OAR). Approach. For the LMA-SC gantry beamline, the movable energy slit is placed in the middle of the last achromatic bending section, and the beam momentum spread of delivered spots can be easily changed during the treatment. Simultaneously, changing the collimator size can provide spots with various lateral spot sizes. Based on the provided large-size and small-size spot models, the treatment planning with mixed spot scanning is optimized: the interior of the target is irradiated with large-size spots (to cover the uniform-dose interior efficiently), while the peripheral of the target is irradiated with small-size spots (to shape the sharp dose falloff at the peripheral accurately). Main results. The treatment plan with mixed-size spot scanning was evaluated and compared with small and large-size spot scanning for thirteen clinical prostate cases. The mixed-size spot plan had superior target dose homogeneities, better protection of OAR, and better plan robustness than the large-size spot plan. Compared to the small-size spot plan, the mixed-size spot plan had comparable plan quality, better plan robustness, and reduced plan delivery time from 65.9 to 40.0 s. Significance. The compact LMA-SC gantry beamline is proposed with mixed-size spot scanning, with demonstrated footprint reduction and improved plan quality compared to the conventional spot scanning method.

Interpretable deep learning insights: Unveiling the role of 1 Gy volume on lymphopenia after radiotherapy in breast cancer

BackgroundLymphopenia is known for its significance on poor survivals in breast cancer patients. Considering full dosimetric data, this study aimed to develop and validate predictive models for lymphopenia after radiotherapy (RT) in breast cancer. Material and methodsPatients with breast cancer treated with adjuvant RT were eligible in this multicenter study. The study endpoint was lympopenia, defined as the reduction in absolute lymphocytes and graded lymphopenia after RT. The dose-volume histogram (DVH) data of related critical structures and clinical factors were taken into account for the development of dense neural network (DNN) predictive models. The developed DNN models were validated using external patient cohorts. ResultsA total of 918 consecutive patients with invasive breast cancer enrolled. The training, testing, and external validating datasets consisted of 589, 203, and 126 patients, respectively. Treatment volumes at nearly all dose levels of the DVH were significant predictors for lymphopenia following RT, including volumes at very low-dose 1 Gy (V1) of organs at risk (OARs) including lung, heart and body, especially ipsilateral-lung V1. A final DNN model, combining full DVH dosimetric parameters of OARs and three key clinical factors, achieved a predictive accuracy of 75 % or higher. ConclusionThis study demonstrated and externally validated the significance of full dosimetric data, particularly the volume of low dose at as low as 1 Gy of critical structures on lymphopenia after radiation in patients with breast cancer. The significance of V1 deserves special attention, as modern VMAT RT technology often has a relatively high value of this parameter. Further study is warranted for RT plan optimization.

Prospective phase II trial on ablative stereotactic body radiation therapy (SBRT) for medically inoperable thoracic nodes metastases

BackgroundOligometastases in mediastinal nodes are increasingly prevalent, posing challenges for treatment with stereotactic body radiotherapy (SBRT) due to proximity to organs at risk (OARs). We report the results of a single prospective observational phase II trial on ablative SBRT for medically inoperable thoracic nodes metastases (NCT02970955). Material and methodsSince 2017, patients with < 3 nodal metastases were evaluated by the tumor board and included if deemed inoperable. SBRT was delivered using risk adaptive approach based on number, site and size of metastatic nodes (50 Gy/5fractions, 60 Gy/8fractions, 70 Gy/10 fractions). Planning target volume (PTV) partial underdosage was allowed. The primary end point was local control (LC) at 12 months. Secondary end points were: acute and late toxicities, overall survival (OS), progression free survival (PFS), and time to next systemic therapy (TTNS). ResultsBetween 03/2017–11/2021, 32 patients (41 nodal metastases) were included. NSCLC (13pts), breast (5pts) and colorectal cancer (4pts) were the most represented primary tumour. In 66 % cases, partial PTV undercoverage was necessary. LC at 1 and 2 years was 93.5 % and 82.3 %, respectively. Treatment was well-tolerated with no acute or late toxicity ≥ G3. Median OS was 59.7 months. OS at 1 and 2 years was 96.9 % and 83.8 % respectively. Median PFS was 12.2 months. PFS at 1 and 2 years was 53.1 % and 31.3 %, respectively. ConclusionThis trial supported the feasibility and safety of ablative SBRT for thoracic nodes metastases thanks to risk adaptive approach allowing to delay of new systemic therapies. Larger studies are needed to confirm these observations.

Generalizability of deep learning in organ-at-risk segmentation: A transfer learning study in cervical brachytherapy

PurposeDeep learning can automate delineation in radiation therapy, reducing time and variability. Yet, its efficacy varies across different institutions, scanners, or settings, emphasizing the need for adaptable and robust models in clinical environments. Our study demonstrates the effectiveness of the transfer learning (TL) approach in enhancing the generalizability of deep learning models for auto-segmentation of organs-at-risk (OARs) in cervical brachytherapy. MethodsA pre-trained model was developed using 120 scans with ring and tandem applicator on a 3T magnetic resonance (MR) scanner (RT3). Four OARs were segmented and evaluated. Segmentation performance was evaluated by Volumetric Dice Similarity Coefficient (vDSC), 95 % Hausdorff Distance (HD95), surface DSC, and Added Path Length (APL). The model was fine-tuned on three out-of-distribution target groups. Pre- and post-TL outcomes, and influence of number of fine-tuning scans, were compared. A model trained with one group (Single) and a model trained with all four groups (Mixed) were evaluated on both seen and unseen data distributions. ResultsTL enhanced segmentation accuracy across target groups, matching the pre-trained model’s performance. The first five fine-tuning scans led to the most noticeable improvements, with performance plateauing with more data. TL outperformed training-from-scratch given the same training data. The Mixed model performed similarly to the Single model on RT3 scans but demonstrated superior performance on unseen data. ConclusionsTL can improve a model’s generalizability for OAR segmentation in MR-guided cervical brachytherapy, requiring less fine-tuning data and reduced training time. These results provide a foundation for developing adaptable models to accommodate clinical settings.

Minimizing normal tissue low dose bath for left breast Volumetric Modulated Arc Therapy (VMAT) using jaw offset.

With proper beam setup and optimization constraints in the treatment planning system, volumetric modulated arc therapy (VMAT) can improve target dose coverage and conformity while reducing doses to adjacent structures for whole breast radiation therapy. However, the low-dose bath effect on critical structures, especially the heart and the ipsilateral lung, remains a concern. In this study, we present a VMAT technique with the jaw offset VMAT (JO-VMAT) to reduce the leakage and scatter doses to critical structures for whole breast radiation therapy. The data of 10 left breast cancer patients were retrospectively used for this study. CT images were acquired on a CT scanner (GE, Discovery) with the deep-inspiration breath hold (DIBH) technique. The planning target volumes (PTVs) and the normal structures (the lungs, the heart, and the contralateral breast) were contoured on the DIBH scan. A 3D field-in-field plan (3D-FiF), a tangential VMAT (tVMAT) plan, and a JO-VMAT plan were created with the Eclipse treatment planning system. An arc treatment field with the x-jaw closed across the central axis creates a donut-shaped high-dose distribution and a cylinder-shaped low-dose volume along the central axis of gantry rotation. Applying this setup with proper multi-leaf collimator (MLC) modulation, the optimized plan potentially can provide sufficient target coverage and reduce unnecessary irradiation to critical structures. The JO-VMAT plans involve 5-6 tangential arcs (3 clockwise arcs and 2-3 counterclockwise arcs) with jaw offsets. The plans were optimized with objective functions specified to achieve PTV dose coverage and homogeneity; For organs at risk (OARs), objective functions were specified individually for each patient to accomplish the best achievable treatment plan. For tVMAT plans, optimization constraints were kept the same except that the jaw offset was removed from the initial beam setup. The dose volume histogram (DVH) parameters were generated for dosimetric evaluation of PTV and OARs. The D95% to the PTV was greater than the prescription dose of 42.56Gy for all the plans. With both VMAT techniques, the PTV conformity index (CI) was statistically improved from 0.62 (3D-FiF) to 0.83 for tVMAT and 0.84 for JO-VMAT plans. The difference in the homogeneity index (HI) was not significant. The Dmax to the heart was reduced from 12.15Gy for 3D-FiF to 8.26Gy for tVMAT and 7.20Gy for JO-VMAT plans. However, a low-dose bath effect was observed with tVMAT plans to all the critical structures including the lungs, the heart, and the contralateral breast. With JO-VMAT, the V5Gy and V2Gy of the heart were reduced by 32.7% and 15.4% compared to 3D-FiF plans. Significantly, the ipsilateral lung showed a reduction in mean dose (4.65-3.44Gy) and low dose parameters (23.4% reduction for V5Gy and 10.7% reduction for V2Gy) for JO-VMAT plans compared to the 3D-FiF plans. The V2Gy dose to the contralateral lung and breast was minimal with JO-VMAT techniques. A JO-VMAT technique was evaluated in this study and compared with 3D-FiF and tVMAT techniques. Our results showed that the JO-VMAT technique can achieve clinically comparable coverage and homogeneity and significantly improve dose conformity within PTV. Additionally, JO-VMAT eliminated the low-dose bath effect at all OARs evaluation metrics including the ipsilateral/contralateral lung, the heart, and the contralateral breast compared to 3D-FiF and tVMAT. This technique is feasible for the whole breast radiation therapy of left breast cancers.

Integration of Ultrasound in Image-Guided Adaptive Brachytherapy in Cancer of the Uterine Cervix

Cervical cancer continues to be a public health concern, as it remains the second most common cancer despite screening programs. It is the third most common cause of cancer-related death for women, and the majority of cases happen in developing nations. The standard treatment for locally advanced cervical cancer involves the use of external beam radiation therapy, along with concurrent chemotherapy, followed by an image-guided adaptive brachytherapy (IGABT) boost. The five-year relative survival rate for European women diagnosed with cervical cancer was 62% between 2000 and 2007. Updated cervical cancer treatment guidelines based on IGABT have been developed by the Gynecological working group, which is composed of the Group Européen de Curiethérapie–European Society for Therapeutic Radiology and Oncology. The therapeutic strategy makes use of three-dimensional imaging, which can be tailored to the target volume and at-risk organs through the use of computed tomography or magnetic resonance imaging. Under anaesthesia, the brachytherapy implantation is carried out. Ultrasonography is utilised to assess the depth of the uterine cavity and to facilitate the dilation of the uterine canal during the application insertion. In this study, we examine data from the international literature regarding the application of ultrasound in cervical cancer brachytherapy.

Influence of the Planning Parameters of a New Algorithm on the Dosimetric Quality, Beam-on Time and Delivery Accuracy of Tomotherapy Plans

Background: This work aimed to determine the optimum VOLOTM Ultra algorithm parameters for tomotherapy treatments. Methods: 1056 treatment plans were generated with VOLOTM Ultra for 36 patients and six anatomical locations. The impact of varying four parameters was studied: the accelerated treatment (AT), leaf open/close time (LOT) cutoff, normal tissue objective (NTO) weight, and number of iterations. The beam-on time and dosimetric metrics were quantified for the target volumes and organs at risk (OARs). Delivery quality assurance measurements were obtained for 36 plans to assess the delivery accuracy. Results: The mean beam-on time for the helical tomotherapy and TomoDirect (TD) plans decreased by 26.6 ± 2.8% and 17.4 ± 4.3%, respectively, when the accelerated treatment parameter was increased from 0 to 10, at the expense of the planning target volume (PTV) coverage (2% lower D98%) and OAR dose (up to 15% increase). For TD plans, it seems preferable to systematically use an AT value of 10. Increasing the number of iterations beyond six seems unnecessary. In this study, an NTO weight of approximately 10 appears to be ideal and eliminates the need to use rings in the treatment plan. Finally, no correlation was found between the leaf open/close time cutoff and the delivery accuracy, while a leaf open/close cutoff of 60 ms seemed to degrade dosimetry quality. Conclusion: Optimal values for the AT, LOT cutoff, NTO weight, and number of optimization rounds were identified and should help improve the management of patients whose tomotherapy treatments are planned with VOLOTM Ultra.

Exclusion of non-Involved uterus from the target volume (EXIT-trial): An individualized treatment for locally advanced cervical cancer using modern radiotherapy and imaging techniques followed by completion surgery

Background and purposeChemoradiotherapy followed by brachytherapy is the standard of care for locally advanced cervical cancer (LACC). In this study, we postulate that omitting an iconographical unaffected uterus (+12 mm distance from the tumour) from the treatment volume is safe and that no tumour will be found in the non-targeted uterus (NTU) leading to reduction of high-dose volumes of surrounding organs at risk (OARs) Material and MethodsIn this single-arm phase 2 study, two sets of target volumes were delineated: one standard-volume (whole uterus) and an EXIT-volume (exclusion of non-tumour-bearing parts of the uterus with a minimum 12 mm margin from the tumour). All patients underwent chemoradiotherapy targeting the EXIT-volume, followed by completion hysterectomy. In 15 patients, a plan comparison between two treatment plans (PTV vs PTV_EXIT) was performed. The primary endpoint was the pathological absence of tumour involvement in the non-targeted uterus (NTU). Secondary endpoints included dosimetric impact of target volume reduction on OARs, acute and chronic toxicity, overall survival (OS), locoregional recurrence-free survival (LRFS), and progression-free survival (PFS). ResultsIn all 21 (FIGO stage I: 2; II: 14;III: 3; IV: 2) patients the NTU was pathologically negative. Ssignificant reductions in Dmean in bladder, sigmoid and rectum; V15Gy in sigmoid and rectum, V30Gy in bladder, sigmoid and rectum; V40Gy and V45Gy in bladder, bowel bag, sigmoid and rectum; V50Gy in rectum were achieved. Median follow-up was 54 months (range 7–79 months). Acute toxicity was mainly grade 2 and 5 % grade 3 urinary. The 3y- OS, PFS and LRFS were respectively 76,2%, 64,9% and 81 %. ConclusionMRI-based exclusion of the non-tumour-bearing parts of the uterus at a minimum distance of 12 mm from the tumour out of the target volume in LACC can be done without risk of residual disease in the NTU, leading to a significant reduction of the volume of surrounding OARS treated to high doses.