Multiparametric magnetic resonance imaging (MRI)-based radiomics model explained by the Shapley Additive exPlanations (SHAP) method for predicting complete response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer: a multicenter retrospective study

Background

Predicting the response to neoadjuvant chemoradiotherapy (nCRT) before initiating treatment is essential for tailoring therapeutic strategies and monitoring prognosis in locally advanced rectal cancer (LARC). In this study, we aimed to develop and validate radiomic-based models to predict clinical and pathological complete responses (cCR and pCR, respectively) by incorporating the Shapley Additive exPlanations (SHAP) method for model interpretation.

Methods

A total of 285 patients with complete pretreatment clinical characteristics and T1-weighted (T1W) and T2-weighted (T2W) magnetic resonance imaging (MRI) at 3 centers were retrospectively recruited. The features of tumor lesions were extracted by PyRadiomics and selected using least absolute shrinkage and selection operator (LASSO) algorithm. The selected features were used to build multilayer perceptron (MLP) models alone or combined with clinical features. Area under the receiver operating characteristic curve (AUC), decision curve, and calibration curve were applied to evaluate performance of models. The SHAP method was adopted to explain the prediction models.

Results

The radiomic-based models all showed better performances than clinical models. The clinical-radiomic models showed the best differentiation on cCR and pCR with mean AUCs of 0.718 and 0.810 in the validation set, respectively. The decision curves of the clinical-radiomic models showed its values in clinical application. The SHAP method powerfully interpreted the prediction models both at a holistic and individual levels.

Conclusions

Our study highlights that the radiomic-based prediction models have more excellent abilities than clinical models and can effectively predict treatment response and optimize therapeutic strategies for patients with LARCs.

Evaluation of Ethos intelligent optimization engine for left locally advanced breast cancer

Purpose

To evaluate the feasibility to use a standard Ethos planning template to treat left-sided breast cancer with regional lymph nodes.

Material/Methods

The tuning cohort of 5 patients was used to create a planning template. The validation cohort included 15 patients treated for a locally advanced left breast cancer randomly enrolled. The Ethos planning template was tuned using standard 3 partial arc VMAT and two collimator rotation configurations: 45/285/345° and 30/60/330°. Re-planning was performed automatically using the template without editing. The study was conducted with a schedule of 42.3 Gy in 18 fractions to the breast/chestwall, internal mammary chain (IMC) and regional lymph nodes ("Nodes"). The PTV was defined as a 3D extension of the CTV with a margin of 7 mm, excluding the 5mm below the skin. The manual treatment plans were performed using Eclipse treatment planning system with AAA and PO algorithms (v15.6) and a manual arc VMAT configuration and imported in Ethos TPS (v1.1) for a dose calculation with Ethos Acuros algorithm. The automated plans were compared with the manual plans using PTV and CTV coverage, homogeneity and conformity indices (HI and CN) and doses to organs at risk (OAR) via DVH metrics. For each plan, the patient quality assurance (QA) were performed using Mobius3D and gamma index. Finally, two breast radiation oncologists performed a blinded assessment of the clinical acceptability of each of the three plans (manual and automated) for each patient.

Results

The manual and automated plans provided suitable treatment planning as regards dose constraints. The dosimetric comparison showed the CTV_breast D99% were significantly improved with both automated plans (p< 0,002) while PTV coverage was comparable. The doses to the organs at risk were equivalent for the three plans. Concerning treatment delivery, the Ethos-45° and Ethos-30° plans led to an increase in MUs compared to the manual plans, without affecting the beam on time. The average gamma index pass rates remained consistently above 98% regardless of the type of plan utilized. In the blinded evaluation, clinicians 1 and 2 assessed 13 out of 15 plans for Ethos 45° and 11 out of 15 plans for Ethos 30° as clinically acceptable.

Conclusion

Using a standard planning template for locally advanced breast cancer, the Ethos TPS provided automated plans that were clinically acceptable and comparable in quality to manually generated plans. Automated plans also dramatically reduce workflow and operator variability.

Geometrical accuracy of magnetic resonance imaging for ocular proton therapy planning

Background & purpose

Magnetic resonance imaging (MRI) is increasingly used in treatment preparation of ocular proton therapy, but its spatial accuracy might be limited by geometric distortions due to susceptibility artefacts. A correct geometry of the MR images is paramount since it defines where the dose will be delivered. In this study, we assessed the geometrical accuracy of ocular MRI.

Materials & methods

A dedicated ocular 3 T MRI protocol, with localized shimming and increased gradients, was compared to computed tomography (CT) and X-ray images in a phantom and in 15 uveal melanoma patients. The MRI protocol contained three-dimensional T2-weighted and T1-weighted sequences with an isotropic reconstruction resolution of 0.3-0.4 mm. Tantalum clips were identified by three observers and clip-clip distances were compared between T2-weighted and T1-weighted MRI, CT and X-ray images for the phantom and between MRI and X-ray images for the patients.

Results

Interobserver variability was below 0.35 mm for the phantom and 0.30(T1)/0.61(T2) mm in patients. Mean absolute differences between MRI and reference were below 0.27 ± 0.16 mm and 0.32 ± 0.23 mm for the phantom and in patients, respectively. In patients, clip-clip distances were slightly larger on MRI than on X-ray images (mean difference T1: 0.11 ± 0.38 mm, T2: 0.10 ± 0.44 mm). Differences did not increase at larger distances and did not correlate to interobserver variability.

Conclusions

A dedicated ocular MRI protocol can produce images of the eye with a geometrical accuracy below half the MRI acquisition voxel (<0.4 mm). Therefore, these images can be used for ocular proton therapy planning, both in the current model-based workflow and in proposed three-dimensional MR-based workflows.

Multi-centre real-world validation of automated treatment planning for breast radiotherapy

PURPOSE

To present the results of the first multi-centre real-world validation of autoplanning for whole breast irradiation after breast-sparing surgery, encompassing high complexity cases (e.g. with a boost or regional lymph nodes) and a wide range of clinical practices.

METHODS

The 24 participating centers each included 10 IMRT/VMAT/Tomotherapy patients, previously treated with a manually generated plan ('manplan'). There were no restrictions regarding case complexity, planning aims, plan evaluation parameters and criteria, fractionation, treatment planning system or treatment machine/technique. In addition to dosimetric comparisons of autoplans with manplans, blinded plan scoring/ranking was conducted by a clinician from the treating center. Autoplanning was performed using a single configuration for all patients in all centres. Deliverability was verified through measurements at delivery units.

RESULTS

Target dosimetry showed comparability, while reductions in OAR dose parameters were 21.4 % for heart Dmean, 16.7 % for ipsilateral lung Dmean, and 101.9 %, 45.5 %, and 35.7 % for contralateral breast D0.03cc, D5% and Dmean, respectively (all p < 0.001). Among the 240 patients included, the clinicians preferred the autoplan for 119 patients, with manplans preferred for 96 cases (p = 0.01). Per centre there were on average 5.0 ± 2.9 (1SD) patients with a preferred autoplan (range [0-10]), compared to 4.0 ± 2.7 with a preferred manplan ([0,9]). No differences were observed regarding deliverability.

CONCLUSION

The automation significantly reduced the hands-on planning workload compared to manual planning, while also achieving an overall superiority. However, fine-tuning of the autoplanning configuration prior to clinical implementation may be necessary in some centres to enhance clinicians' satisfaction with the generated autoplans.

Dosimetrical and geometrical parameters in single-fraction lattice radiotherapy for the treatment of bulky tumors: Insights from initial clinical experience

PURPOSE

This study aims to investigate lattice radiotherapy (LRT) for bulky tumor in 10 patients, analyzing geometrical and dosimetrical parameters and correlations among variables.

METHODS

Patients were prescribed a single-fraction of 18 Gy to 50 % of each spherical vertex (1.5 cm diameter). Vertices were arranged in equidistant planes forming a triangular pattern. Center-to-center distance (Dc-c) between vertices was varied from 4 to 5 cm. A new method for calculating the valley-to-peak dose ratio (VPDR) was proposed and compared to other two from existing literature. GTV volumes (VGTV), vertex number (Nvert), low-dose related parameters and vertex D99%, D50%, and D1% were recorded. Beam-on time and Monitor Units (MU) were also evaluated. Correlations were assessed using Spearman's coefficient, with significant differences analyzed using Mann-Whitney U test.

RESULTS

Tumor volumes ranged from 417 to 3615 cm3. Median vertex number was 14.5 (IQR:11.3-17.8). VPDR ranged from 0.16 to 0.28. Median D99% spanned from 10.0 to 13.7 Gy, median D50% exceeded 18.0 Gy, and median D1% surpassed 23.3 Gy. Periphery dose remained under 4.0 Gy. Plans exhibited high modulation, with median beam-on time and MU of 8.8 min (IQR:8.2-10.1) and 13,069 MU (IQR:11574-13639). Significant correlations were found between Nvert and VGTV (p < 0.01), MU (p < 0.02) and beam-on time (p < 0.01) and between Dc-c and two VPDR definitions (p < 0.02) and periphery dose (p < 0.01). Significant differences were observed among the three valley dose definitions (p < 0.01) and the three peak dose definitions (p < 0.01).

CONCLUSIONS

Reporting geometrical and dosimetrical parameters in LRT is crucial, alongside the need for unified definitions of valley and peak doses.

Sensitivity of automated and manual treatment planning approaches to contouring variation in early-breast cancer treatment

PURPOSE

One of the advantages of integrating automated processes in treatment planning is the reduction of manual planning variability. This study aims to assess whether a deep-learning-based auto-planning solution can also reduce the contouring variation-related impact on the planned dose for early-breast cancer treatment.

METHODS

Auto- and manual plans were optimized for 20 patients using both auto- and manual OARs, including both lungs, right breast, heart, and left-anterior-descending (LAD) artery. Differences in terms of recalculated dose (ΔDrcM,ΔDrcA) and reoptimized dose (ΔDroM,ΔDroA) for manual (M) and auto (A)-plans, were evaluated on manual structures. The correlation between several geometric similarities and dose differences was also explored (Spearman's test).

RESULTS

Auto-contours were found slightly smaller in size than manual contours for right breast and heart and more than twice larger for LAD. Recalculated dose differences were found negligible for both planning approaches except for heart (ΔDrcM=-0.4 Gy, ΔDrcA=-0.3 Gy) and right breast (ΔDrcM=-1.2 Gy, ΔDrcA=-1.3 Gy) maximum dose. Re-optimized dose differences were considered equivalent to recalculated ones for both lungs and LAD, while they were significantly smaller for heart (ΔDroM=-0.2 Gy, ΔDroA=-0.2 Gy) and right breast (ΔDroM =-0.3 Gy, ΔDroA=-0.9 Gy) maximum dose. Twenty-one correlations were found for ΔDrcM,A (M=8,A=13) that reduced to four for ΔDroM,A (M=3,A=1).

CONCLUSIONS

The sensitivity of auto-planning to contouring variation was found not relevant when compared to manual planning, regardless of the method used to calculate the dose differences. Nonetheless, the method employed to define the dose differences strongly affected the correlation analysis resulting highly reduced when dose was reoptimized, regardless of the planning approach.

Total Neoadjuvant Therapy in Localized Pancreatic Cancer: Is More Better?

Pancreatic ductal adenocarcinoma (PDAC) poses a significant challenge in oncology due to its advanced stage upon diagnosis and limited treatment options. Surgical resection, the primary curative approach, often results in poor long-term survival rates, leading to the exploration of alternative strategies like neoadjuvant therapy (NAT) and total neoadjuvant therapy (TNT). While NAT aims to enhance resectability and overall survival, there appears to be potential for improvement, prompting consideration of alternative neoadjuvant strategies integrating full-dose chemotherapy (CT) and radiotherapy (RT) in TNT approaches. TNT integrates chemotherapy and radiotherapy prior to surgery, potentially improving margin-negative resection rates and enabling curative resection for locally advanced cases. The lingering question: is more always better? This article categorizes TNT strategies into six main groups based on radiotherapy (RT) techniques: (1) conventional chemoradiotherapy (CRT), (2) the Dutch PREOPANC approach, (3) hypofractionated ablative intensity-modulated radiotherapy (HFA-IMRT), and stereotactic body radiotherapy (SBRT) techniques, which further divide into (4) non-ablative SBRT, (5) nearly ablative SBRT, and (6) adaptive ablative SBRT. A comprehensive analysis of the literature on TNT is provided for both borderline resectable pancreatic cancer (BRPC) and locally advanced pancreatic cancer (LAPC), with detailed sections for each.

Longitudinal Image Data for Outcome Modeling

In oncology, medical imaging is crucial for diagnosis, treatment planning and therapy execution. Treatment responses can be complex and varied and are known to involve factors of treatment, patient characteristics and tumor microenvironment. Longitudinal image analysis is able to track temporal changes, aiding in disease monitoring, treatment evaluation, and outcome prediction. This allows for the enhancement of personalized medicine. However, analyzing longitudinal 2D and 3D images presents unique challenges, including image registration, reliable segmentation, dealing with variable imaging intervals, and sparse data. This review presents an overview of techniques and methodologies in longitudinal image analysis, with a primary focus on outcome modeling in radiation oncology.

Baseline [18F]FDG PET/CT and MRI first-order breast tumor features do not improve pathological complete response prediction to neoadjuvant chemotherapy

PURPOSE

To verify the ability of pretreatment [18F]FDG PET/CT and T1-weighed dynamic contrast-enhanced MRI to predict pathological complete response (pCR) after neoadjuvant chemotherapy (NAC) in breast cancer (BC) patients.

METHODS

This retrospective study includes patients with BC of no special type submitted to baseline [18F]FDG PET/CT, NAC and surgery. [18F]FDG PET-based features reflecting intensity and heterogeneity of tracer uptake were extracted from the primary BC and suspicious axillary lymph nodes (ALN), for comparative analysis related to NAC response (pCR vs. non-pCR). Multivariate logistic regression was performed for response prediction combining the breast tumor-extracted PET-based features and clinicopathological features. A subanalysis was performed in a patients' subsample by adding breast tumor-extracted first-order MRI-based features to the multivariate logistic regression.

RESULTS

A total of 170 tumors from 168 patients were included. pCR was observed in 60/170 tumors (20/107 luminal B-like, 25/45 triple-negative and 15/18 HER2-enriched surrogate molecular subtypes). Higher intensity and higher heterogeneity of [18F]FDG uptake in the primary BC were associated with NAC response in HER2-negative tumors (immunohistochemistry score 0, 1 + or 2 + non-amplified by in situ hybridization). Also, higher intensity of tracer uptake was observed in ALN in the pCR group among HER2-negative tumors. No [18F]FDG PET-based features were associated with pCR in the other subgroup analyses. A subsample of 103 tumors was also submitted to extraction of MRI-based features. When combined with clinicopathological features, neither [18F]FDG PET nor MRI-based features had additional value for pCR prediction. The only significant predictors were estrogen receptor status, HER2 expression and grade.

CONCLUSION

Pretreatment [18F]FDG PET-based features from primary BC and ALN are not associated with response to NAC, except in HER2-negative tumors. As compared with pathological features, no breast tumor-extracted PET or MRI-based feature improved response prediction.

Validation and reproducibility of in vivo dosimetry for pencil beam scanned FLASH proton treatment in mice

PURPOSE

To investigate quality assurance (QA) techniques for in vivo dosimetry and establish its routine uses for proton FLASH small animal experiments with a saturated monitor chamber.

METHODS AND MATERIALS

227 mice were irradiated at FLASH or conventional (CONV) dose rates with a 250 MeV FLASH-capable proton beamline using pencil beam scanning to characterize the proton FLASH effect on abdominal irradiation and examining various endpoints. A 2D strip ionization chamber array (SICA) detector was positioned upstream of collimation and used for in vivo dose monitoring during irradiation. Before each irradiation series, SICA signal was correlated with the isocenter dose at each delivered dose rate. Dose, dose rate, and 2D dose distribution for each mouse were monitored with the SICA detector.

RESULTS

Calibration curves between the upstream SICA detector signal and the delivered dose at isocenter had good linearity with minimal R2 values of 0.991 (FLASH) and 0.985 (CONV), and slopes were consistent for each modality. After reassigning mice, standard deviations were less than 1.85 % (FLASH) and 0.83 % (CONV) for all dose levels, with no individual subject dose falling outside a ± 3.6 % range of the designated dose. FLASH fields had a field-averaged dose rate of 79.0 ± 0.8 Gy/s and mean local average dose rate of 160.6 ± 3.0 Gy/s. In vivo dosimetry allowed for the accurate detection of variation between the delivered and the planned dose.

CONCLUSION

In vivo dosimetry benefits FLASH experiments through enabling real-time dose and dose rate monitoring allowing mouse cohort regrouping when beam fluctuation causes delivered dose to vary from planned dose.

Intrafraction organ movement in adaptive MR-guided radiotherapy of abdominal lesions - dosimetric impact and how to detect its extent in advance

INTRODUCTION

Magnetic resonance guided radiotherapy (MRgRT) allows daily adaptation of treatment plans to compensate for positional changes of target volumes and organs at risk (OARs). However, current adaptation times are relatively long and organ movement occurring during the adaptation process might offset the benefit gained by adaptation. The aim of this study was to evaluate the dosimetric impact of these intrafractional changes. Additionally, a method to predict the extent of organ movement before the first treatment was evaluated in order to have the possibility to compensate for them, for example by adding additional margins to OARs.

MATERIALS & METHODS

Twenty patients receiving adaptive MRgRT for treatment of abdominal lesions were retrospectively analyzed. Magnetic resonance (MR) images acquired at the start of adaptation and immediately before irradiation were used to calculate adapted and pre-irradiation dose in OARs directly next to the planning target volume. The extent of organ movement was determined on MR images acquired during simulation sessions and adaptive treatments, and their agreement was evaluated. Correlation between the magnitude of organ movement during simulation and the duration of simulation session was analyzed in order to assess whether organ movement might be relevant even if the adaptation process could be accelerated in the future.

RESULTS

A significant increase in dose constraint violations was observed from adapted (6.9%) to pre-irradiation (30.2%) dose distributions. Overall, OAR dose increased significantly by 4.3% due to intrafractional organ movement. Median changes in organ position of 7.5 mm (range 1.5-10.5 mm) were detected within a median time of 17.1 min (range 1.6-28.7 min). Good agreement was found between the range of organ movement during simulation and adaptation (66.8%), especially if simulation sessions were longer and multiple MR images were acquired. No correlation was determined between duration of simulation sessions and magnitude of organ movement.

CONCLUSION

Intrafractional organ movement can impact dose distributions and lead to violations of OAR tolerance doses, which impairs the benefit of daily on-table plan adaptation. By application of simulation images, the extent of intrafractional organ movement can be predicted, which possibly allows to compensate for them.

Robustness of intensity modulated proton treatment of esophageal cancer for anatomical changes and breathing motion

BACKGROUND AND PURPOSE

In this study, we assessed the robustness of intensity modulated proton therapy (IMPT) in esophageal cancer for anatomical variations during treatment.

METHODS

The first sixty esophageal cancer patients, treated clinically with chemoradiotherapy were included. The treatment planning strategy was based on an internal target volume (ITV) approach, where the ITV was created from the clinical target volumes (CTVs) delineated on all phases of a 4DCT. For optimization, a 3 mm isotropic margin was added to the ITV, combined with robust optimization using 5 mm setup and 3 % range uncertainty. Each patient received weekly repeat CTs (reCTs). Robust plan re-evaluation on all reCTs, and a robust dose summation was performed. To assess the factors influencing ITV coverage, a multivariate linear regression analysis was performed. Additionally, clinical adaptations were evaluated.

RESULTS

The target coverage was adequate (ITV V94%>98 % on the robust voxel-wise minimum dose) on most reCTs (91 %), and on the summed dose in 92 % of patients. Significant predictors for ITV coverage in the multivariate analysis were diaphragm baseline shift and water equivalent depth (WED) of the ITV in the beam direction. Underdosage of the ITV mainly occurred in week 1 and 4, leading to treatment adaptation of eight patients, all on the first reCT.

CONCLUSION

Our IMPT treatment of esophageal cancer is robust for anatomical variations. Adaptation appears to be most effective in the first week of treatment. Diaphragm baseline shifts and WED are predictive factors for ITV underdosage, and should be incorporated in an adaptation protocol.

Accuracy of gross tumour volume delineation with [68Ga]-PSMA-PET compared to histopathology for high-risk prostate cancer

BACKGROUND

The delineation of intraprostatic lesions is vital for correct delivery of focal radiotherapy boost in patients with prostate cancer (PC). Errors in the delineation could translate into reduced tumour control and potentially increase the side effects. The purpose of this study is to compare PET-based delineation methods with histopathology.

MATERIALS AND METHODS

The study population consisted of 15 patients with confirmed high-risk PC intended for prostatectomy. [68Ga]-PSMA-PET/MR was performed prior to surgery. Prostate lesions identified in histopathology were transferred to the in vivo [68Ga]-PSMA-PET/MR coordinate system. Four radiation oncologists manually delineated intraprostatic lesions based on PET data. Various semi-automatic segmentation methods were employed, including absolute and relative thresholds, adaptive threshold, and multi-level Otsu threshold.

RESULTS

The gross tumour volumes (GTVs) delineated by the oncologists showed a moderate level of interobserver agreement with Dice similarity coefficient (DSC) of 0.68. In comparison with histopathology, manual delineations exhibited the highest median DSC and the lowest false discovery rate (FDR) among all approaches. Among semi-automatic approaches, GTVs generated using standardized uptake value (SUV) thresholds above 4 (SUV > 4) demonstrated the highest median DSC (0.41), with 0.51 median lesion coverage ratio, FDR of 0.66 and the 95th percentile of the Hausdorff distance (HD95%) of 8.22 mm.

INTERPRETATION

Manual delineations showed a moderate level of interobserver agreement. Compared to histopathology, manual delineations and SUV > 4 exhibited the highest DSC and the lowest HD95% values. The methods that resulted in a high lesion coverage were associated with a large overestimation of the size of the lesions.

Artificial Intelligence in Head and Neck Surgery

This article explores artificial intelligence's (AI's) role in otolaryngology for head and neck cancer diagnosis and management. It highlights AI's potential in pattern recognition for early cancer detection, prognostication, and treatment planning, primarily through image analysis using clinical, endoscopic, and histopathologic images. Radiomics is also discussed at length, as well as the many ways that radiologic image analysis can be utilized, including for diagnosis, lymph node metastasis prediction, and evaluation of treatment response. The study highlights AI's promise and limitations, underlining the need for clinician-data scientist collaboration to enhance head and neck cancer care.

Computer Vision-Radiomics & Pathognomics

The role of computer vision in extracting radiographic (radiomics) and histopathologic (pathognomics) features is an extension of molecular biomarkers that have been foundational to our understanding across the spectrum of head and neck disorders. Especially within head and neck cancers, machine learning and deep learning applications have yielded advances in the characterization of tumor features, nodal features, and various outcomes. This review aims to overview the landscape of radiomic and pathognomic applications, informing future work to address gaps. Novel methodologies will be needed to potentially engineer ways of integrating multidimensional data inputs to examine disease features to guide prognosis comprehensively and ultimately clinical management.

Application and dosimetric comparison of surface-guided deep inspiration breath-hold for lung stereotactic body radiotherapy

Respiratory motion management is the crucial challenge for safe and effective application of lung stereotactic body radiotherapy (SBRT). The present study implemented lung SBRT treatment in voluntary deep inspiration breath-hold (DIBH) with surface-guided radiotherapy (SGRT) system and evaluated the geometric and dosimetric benefits of DIBH to organs-at-risk (OARs), aiming to advising the choice between DIBH technology and conventional free breathing 4 dimensions (FB-4D) technology. Five patients of lung SBRT treated in DIBH with SGRT at our institution were retrospectively analyzed. CT scans were acquired in DIBH and FB-4D, treatment plans were generated for both respiratory phases. The geometric and dosimetry of tumor, ipsilateral lung, double lungs and heart were compared between the DIBH and FB-4D treatment plans. In terms of target coverage, utilizing DIBH significantly reduced the mean plan target volume (PTV) by 21.9% (p = 0.09) compared to FB-4D, the conformity index (CI) of DIBH and FB-4D were comparable, but the dose gradient index (DGI) of DIBH was higher. With DIBH expanding lung, the volumes of ipsilateral lung and double lungs were 2535.1 ± 403.0cm3 and 4864.3 ± 900.2cm3, separately, 62.2% (p = 0.009) and 73.1% (p = 0.009) more than volumes of ipsilateral lung (1460.03 ± 146.60cm3) and double lungs (2811.25 ± 603.64cm3) in FB-4D. The heart volume in DIBH was 700.0 ± 146.1cm3, 11.6% (p = 0.021) less than that in FB-4D. As for OARs protection, the mean dose, percent of volume receiving > 20Gy (V20) and percent of volume receiving > 5Gy (V5) of ipsilateral lung in DIBH were significantly lower by 33.2% (p = 0.020), 44.0% (p = 0.022) and 24.5% (p = 0.037) on average, separately. Double lungs also showed significant decrease by 31.1% (p = 0.019), 45.5% (p = 0.024) and 20.9% (p = 0.048) on average for mean dose, V20 and V5 in DIBH. Different from the lung, the mean dose and V5 of heart showed no consistency between DIBH and FB-4D, but lower maximum dose of heart was achieved in DIBH for all patients in this study. Appling lung SBRT in DIBH with SGRT was feasibly performed with high patient compliance. DIBH brought significant dosimetric benefits to lung, however, it caused more or less irradiated heart dose that depend on the patients' individual differences which were unpredictable.

Lung sparing in MR-guided non-adaptive SBRT treatment of peripheral lung tumors

Objective.We aim to: (1) quantify the benefits of lung sparing using non-adaptive magnetic resonance guided stereotactic body radiotherapy (MRgSBRT) with advanced motion management for peripheral lung cancers compared to conventional x-ray guided SBRT (ConvSBRT); (2) establish a practical decision-making guidance metric to assist a clinician in selecting the appropriate treatment modality.Approach.Eleven patients with peripheral lung cancer who underwent breath-hold, gated MRgSBRT on an MR-guided linear accelerator (MR linac) were studied. Four-dimensional computed tomography (4DCT)-based retrospective planning using an internal target volume (ITV) was performed to simulate ConvSBRT, which were evaluated against the original MRgSBRT plans. Metrics analyzed included planning target volume (PTV) coverage, various lung metrics and the generalized equivalent unform dose (gEUD). A dosimetric predictor for achievable lung metrics was derived to assist future patient triage across modalities.Main results.PTV coverage was high (median V100% > 98%) and comparable for both modalities. MRgSBRT had significantly lower lung doses as measured by V20 (median 3.2% versus 4.2%), mean lung dose (median 3.3 Gy versus 3.8 Gy) and gEUD. Breath-hold, gated MRgSBRT resulted in an average reduction of 47% in PTV volume and an average increase of 19% in lung volume. Strong correlation existed between lung metrics and the ratio of PTV to lung volumes (RPTV/Lungs) for both modalities, indicating that RPTV/Lungsmay serve as a good predictor for achievable lung metrics without the need for pre-planning. A threshold value of RPTV/Lungs< 0.035 is suggested to achieve V20 < 10% using ConvSBRT. MRgSBRT should otherwise be considered if the threshold cannot be met.Significance.The benefits of lung sparing using MRgSBRT were quantified for peripheral lung tumors; RPTV/Lungswas found to be an effective predictor for achievable lung metrics across modalities. RPTV/Lungscan assist a clinician in selecting the appropriate modality without the need for labor-intensive pre-planning, which has significant practical benefit for a busy clinic.

Robust optimization of the Gross Tumor Volume compared to conventional Planning Target Volume-based planning in photon Stereotactic Body Radiation Therapy of lung tumors

BACKGROUND

Robust optimization has been suggested as an approach to reduce the irradiated volume in lung Stereotactic Body Radiation Therapy (SBRT). We performed a retrospective planning study to investigate the potential benefits over Planning Target Volume (PTV)-based planning.

MATERIAL AND METHODS

Thirty-nine patients had additional plans using robust optimization with 5-mm isocenter shifts of the Gross Tumor Volume (GTV) created in addition to the PTV-based plan used for treatment. The optimization included the mid-position phase and the extreme breathing phases of the 4D-CT planning scan. The plans were compared for tumor coverage, isodose volumes, and doses to Organs At Risk (OAR). Additionally, we evaluated both plans with respect to observed tumor motion using the peak tumor motion seen on the planning scan and cone-beam CTs.

RESULTS

Statistically significant reductions in irradiated isodose volumes and doses to OAR were achieved with robust optimization, while preserving tumor dose. The reductions were largest for the low-dose volumes and reductions up to 188 ccm was observed. The robust evaluation based on observed peak tumor motion showed comparable target doses between the two planning methods. Accumulated mean GTV-dose was increased by a median of 4.46 Gy and a non-significant increase of 100 Monitor Units (MU) was seen in the robust optimized plans.

INTERPRETATION

The robust plans required more time to prepare, and while it might not be a feasible planning strategy for all lung SBRT patients, we suggest it might be useful for selected patients.

Design and characterisation of a minibeam collimator utilising Monte Carlo simulation and a clinical linear accelerator

Objective.Spatially fractionated radiotherapy is showing promise as a treatment modality. Initial focus was on beams of photons at low energy produced from a synchrotron but more recently research has expanded to include applications in proton therapy. Interest in photon beams remains and this is the focus of this paperApproach.This study presents a 3D printed tungsten minibeam collimator intended to produce peak-to-valley dose ratios (PVDR) of between seven and ten with a 1 MV, bremsstrahlung generated, photon beam. The design of the collimator is motivated by a Monte Carlo study estimating the PVDR for different collimator designs at different energies. This collimator was characterised on a clinical linear accelerator (Elekta VersaHD) as well as an orthovoltage unit.Main results.The performance of the fabricated collimator was measured on Elekta VersaHD running in unflattened mode with a 6 MV beam. On the Elekta VersaHD units the PVDR was measured to be between approximately 1.5 and 2.0 at 3 cm deep. For measurements with the orthovoltage unit PVDRs of greater than 10 were observed at a depth of 4 cm.Significance.The results confirmed that the predictions from simulation could be reproduced on linear accelerators currently in clinical usage, producing PVDRs between 2-2.5. Using the model to predict PVDRs using 1 MV photon beams, the threshold considered to produce enhanced normal tissue dose tolerance (>7) was surpassed. This suggests the possibility of using such techniques with versions of existing Linac technology which have been modified to operate at low energy and high beam currents.

Clinical Outcomes of Online Adaptive Magnetic Resonance-Guided Stereotactic Body Radiotherapy of Adrenal Metastases from a Single Institution

(1) Background: Recent publications foster stereotactic body radiotherapy (SBRT) in patients with adrenal oligometastases or oligoprogression. However, local control (LC) after non-adaptive SBRT shows the potential for improvement. Online adaptive MR-guided SBRT (MRgSBRT) improves tumor coverage and organ-at-risk (OAR) sparing. Long-term results of adaptive MRgSBRT are still sparse. (2) Methods: Adaptive MRgSBRT was performed on a 0.35 T MR-Linac. LC, overall survival (OS), progression-free survival (PFS), overall response rate (ORR), and toxicity were assessed. (3) Results: 35 patients with 40 adrenal metastases were analyzed. The median gross tumor volume was 30.6 cc. The most common regimen was 10 fractions at 5 Gy. The median biologically effective dose (BED10) was 75.0 Gy. Plan adaptation was performed in 98% of all fractions. The median follow-up was 7.9 months. One local failure occurred after 16.6 months, resulting in estimated LC rates of 100% at one year and 90% at two years. ORR was 67.5%. The median OS was 22.4 months, and the median PFS was 5.1 months. No toxicity > CTCAE grade 2 occurred. (4) Conclusions: LC and ORR after adrenal adaptive MRgSBRT were excellent, even in a cohort with comparably large metastases. A BED10 of 75 Gy seems sufficient for improved LC in comparison to non-adaptive SBRT.

Phantoms for Quantitative Body MRI: a review and discussion of the phantom value

In this paper, we review the value of phantoms for body MRI in the context of their uses for quantitative MRI methods research, clinical trials, and clinical imaging. Certain uses of phantoms are common throughout the body MRI community, including measuring bias, assessing reproducibility, and training. In addition to these uses, phantoms in body MRI methods research are used for novel methods development and the design of motion compensation and mitigation techniques. For clinical trials, phantoms are an essential part of quality management strategies, facilitating the conduct of ethically sound, reliable, and regulatorily compliant clinical research of both novel MRI methods and therapeutic agents. In the clinic, phantoms are used for development of protocols, mitigation of cost, quality control, and radiotherapy. We briefly review phantoms developed for quantitative body MRI, and finally, we review open questions regarding the most effective use of a phantom for body MRI.

MU variability in CBCT-guided online adaptive radiation therapy

PURPOSE

CBCT-guided online-adaptive radiotherapy (oART) systems have been made possible by using artificial intelligence and automation to substantially reduce treatment planning time during on-couch adaptive sessions. Evaluating plans generated during an adaptive session presents significant challenges to the clinical team as the planning process gets compressed into a shorter window than offline planning. We identified MU variations up to 30% difference between the adaptive plan and the reference plan in several oART sessions that caused the clinical team to question the accuracy of the oART dose calculation. We investigated the cause of MU variation and the overall accuracy of the dose delivered when MU variations appear unnecessarily large.

METHODS

Dosimetric and adaptive plan data from 604 adaptive sessions of 19 patients undergoing CBCT-guided oART were collected. The analysis included total MU per fraction, planning target volume (PTV) and organs at risk (OAR) volumes, changes in PTV-OAR overlap, and DVH curves. Sessions with MU greater than two standard deviations from the mean were reoptimized offline, verified by an independent calculation system, and measured using a detector array.

RESULTS

MU variations relative to the reference plan were normally distributed with a mean of -1.0% and a standard deviation of 11.0%. No significant correlation was found between MU variation and anatomic changes. Offline reoptimization did not reliably reproduce either reference or on-couch total MUs, suggesting that stochastic effects within the oART optimizer are likely causing the variations. Independent dose calculation and detector array measurements resulted in acceptable agreement with the planned dose.

CONCLUSIONS

MU variations observed between oART plans were not caused by any errors within the oART workflow. Providers should refrain from using MU variability as a way to express their confidence in the treatment planning accuracy. Clinical decisions during on-couch adaptive sessions should rely on validated secondary dose calculations to ensure optimal plan selection.

The feasibility of CT simulation-free adaptive radiation therapy

BACKGROUND

Novel on-board CBCT allows for improved image quality and Hounsfield unit accuracy. When coupled with online adaptive tools, this may have potential to allow for simulation and treatment to be completed in a single on-table session.

PURPOSE

To study the feasibility of a high-efficiency radiotherapy treatment workflow without the use of a separate session for simulation imaging. The dosimetric accuracy, overall efficiency, and technical feasibility were used to evaluate the clinical potential of CT simulation-free adaptive radiotherapy.

METHODS

Varian's Ethos adaptive radiotherapy treatment platform was upgraded with a novel CBCT system, HyperSight which reports image quality and Hounsfield unit accuracy specifications comparable to standard fan-beam CT. Using in-house developed MATLAB software, CBCT images were imported into the system and used for planning. Two test cases were completed on anthropomorphic phantoms equipped with small volume ion chambers (cross-calibrated to an ADCL traceable dose standard) to evaluate the feasibility and accuracy of the workflows. A simulated palliative spine treatment was planned with 8 Gy in one fraction, and an intact prostate treatment was planned with 60 Gy in 20 fractions. The CBCTs were acquired using HyperSight with default thorax and pelvis imaging protocols and reconstructed using an iterative algorithm with scatter removal, iCBCT Acuros. CBCTs were used for contouring and planning, and treatment was delivered via an online adaptive workflow. In addition, an external dosimetry audit was completed using only on-board CBCT imaging in an end-to-end head and neck phantom irradiation.

RESULTS

An extended-field CBCT acquisition can be acquired in 12 s, in addition to the time for longitudinal table shifts, and reconstructed in approximately 1 min. The superior-inferior extent for the CBCT planning images was 38.2 cm, which captured the full extent of relevant anatomy. The contouring and treatment planning for the spine and prostate were completed in 30 and 18 min, respectively. The dosimetric agreement between ion chamber measurements and the treatment plan was within a range of -1.4 to 1.6%, and a mean and standard deviation of 0.41 ± 1.16%. All metrics used in the external audit met the passing criteria, and the dosimetric comparison between fan-beam and CBCT techniques had a gamma passing rate of 99.0% with a criteria of 2%/2 mm.

CONCLUSION

Using an in-house workflow, CT simulation-free radiation therapy was shown to be feasible with acceptable workflow efficiency and dosimetric accuracy. This approach may be particularly applicable for urgent palliative treatments. With the availability of software to enable this workflow, and the continued advancement of on-treatment adaptation, single-visit radiation therapy may replace current practice for some clinical indications.

Manganese-derived biomaterials for tumor diagnosis and therapy

Manganese (Mn) is widely recognized owing to its low cost, non-toxic nature, and versatile oxidation states, leading to the emergence of various Mn-based nanomaterials with applications across diverse fields, particularly in tumor diagnosis and therapy. Systematic reviews specifically addressing the tumor diagnosis and therapy aspects of Mn-derived biomaterials are lacking. This review comprehensively explores the physicochemical characteristics and synthesis methods of Mn-derived biomaterials, emphasizing their role in tumor diagnostics, including magnetic resonance imaging, photoacoustic and photothermal imaging, ultrasound imaging, multimodal imaging, and biodetection. Moreover, the advantages of Mn-based materials in tumor treatment applications are discussed, including drug delivery, tumor microenvironment regulation, synergistic photothermal, photodynamic, and chemodynamic therapies, tumor immunotherapy, and imaging-guided therapy. The review concludes by providing insights into the current landscape and future directions for Mn-driven advancements in the field, serving as a comprehensive resource for researchers and clinicians.

Time is NTCP: Should we maximize patient throughput or perform online adaptation on proton therapy systems?

BACKGROUND

Compared to conventional radiotherapy (XT), proton therapy (PT) may improve normal tissue complication probabilities (NTCP). However, PT typically requires higher adaptation rates due to an increased sensitivity to anatomical changes. Systematic online adaptation may address this issue, but it requires additional replanning time, decreasing patient throughput. Therefore, less patients would benefit in such case from PT for a given machine capacity, with results in worse NTCP.

AIM

To investigate the trade-off between PT patient throughput and NTCP gain as a function of the time needed for adaptation.

METHODS

A retrospective database of 14 lung patients with two repeated 4DCTs was used to compare NTCP values between XT and PT for NTCP2ym (2-year mortality), NTCPdysphagia and NTCPpneumonitis. Four scenarios were considered for PT: no adaptation using clinical robustness parameters (4D robust optimization, 3 % range error and PTV-equivalent setup errors); systematic online adaptation with clinical robustness parameters; setup errors reduced to 4 mm and to 2 mm. Dose was accumulated on the planning CT. The number of patients treated with PT depended on the extra time needed for adaptation, assuming an 8-hours capacity (assuming 14 patients a day; thus minimum 34.2 min per treatment session if there is no or instantaneous adaptation).

RESULTS

Baseline NTCP gains (PT against XT without adaptation) equaled 6.9 %, 6.1 %, and 7.7 % for NTCP2ym, NTCPdysphagia and NTCPpneumonitis, respectively. Using instantaneous online adaptation and setup errors of 2 mm, the overall gains were then 10.7 %, 13.6 % and 12.4 %. Taking into account loss of capacity, 13.7 min was the maximum extra-time allowed to complete adaptation and maintain an advantage on all three metrics for the 2-mm setup error scenario.

CONCLUSION

This study highlights the critical importance of keeping short online adaptation times when using systems with limited capacity like PT.

Challenges and opportunities in the development and clinical implementation of artificial intelligence based synthetic computed tomography for magnetic resonance only radiotherapy

Synthetic computed tomography (sCT) generated from magnetic resonance imaging (MRI) can serve as a substitute for planning CT in radiation therapy (RT), thereby removing registration uncertainties associated with multi-modality imaging pairing, reducing costs and patient radiation exposure. CE/FDA-approved sCT solutions are nowadays available for pelvis, brain, and head and neck, while more complex deep learning (DL) algorithms are under investigation for other anatomic sites. The main challenge in achieving a widespread clinical implementation of sCT lies in the absence of consensus on sCT commissioning and quality assurance (QA), resulting in variation of sCT approaches across different hospitals. To address this issue, a group of experts gathered at the ESTRO Physics Workshop 2022 to discuss the integration of sCT solutions into clinics and report the process and its outcomes. This position paper focuses on aspects of sCT development and commissioning, outlining key elements crucial for the safe implementation of an MRI-only RT workflow.

The Evolving Role of Artificial Intelligence in Radiotherapy Treatment Planning-A Literature Review

This paper examines the integration of artificial intelligence (AI) in radiotherapy for cancer treatment. The importance of radiotherapy in cancer management and its time-intensive planning process make AI adoption appealing especially with the escalating demand for radiotherapy. This review highlights the efficacy of AI across medical domains, where it surpasses human capabilities in areas such as cardiology and dermatology. Focusing on radiotherapy, the paper details AI's applications in target segmentation, dose optimization, and outcome prediction. It discusses adaptive radiotherapy's benefits and AI's potential to enhance patient outcomes with much improved treatment accuracy. The paper explores ethical concerns, including data privacy and bias, stressing the need for robust guidelines. Educating healthcare professionals and patients about AI's role is crucial as it acknowledges potential job-role changes and concerns about patients' trust in the use of AI. Overall, the integration of AI in radiotherapy holds transformative potential in streamlining processes, improving outcomes, and reducing costs. AI's potential to reduce healthcare costs underscores its significance with impactful change globally. However, successful implementation hinges on addressing ethical and logistical challenges and fostering collaboration among healthcare professionals and patient population data sets for its optimal utilization. Rigorous education, collaborative efforts, and global data sharing will be the compass guiding its' success in radiotherapy and healthcare.

Machine Learning in Spine Oncology: A Narrative Review

STUDY DESIGN

Narrative Review.

OBJECTIVE

Machine learning (ML) is one of the latest advancements in artificial intelligence used in medicine and surgery with the potential to significantly impact the way physicians diagnose, prognose, and treat spine tumors. In the realm of spine oncology, ML is utilized to analyze and interpret medical imaging and classify tumors with incredible accuracy. The authors present a narrative review that specifically addresses the use of machine learning in spine oncology.

METHODS

This study was conducted in accordance with the Preferred Reporting Items of Systematic Reviews and Meta-Analysis (PRISMA) methodology. A systematic review of the literature in the PubMed, EMBASE, Web of Science, Scopus, and Cochrane Library databases since inception was performed to present all clinical studies with the search terms '[[Machine Learning] OR [Artificial Intelligence]] AND [[Spine Oncology] OR [Spine Cancer]]'. Data included studies that were extracted and included algorithms, training and test size, outcomes reported. Studies were separated based on the type of tumor investigated using the machine learning algorithms into primary, metastatic, both, and intradural. A minimum of 2 independent reviewers conducted the study appraisal, data abstraction, and quality assessments of the studies.

RESULTS

Forty-five studies met inclusion criteria out of 480 references screened from the initial search results. Studies were grouped by metastatic, primary, and intradural tumors. The majority of ML studies relevant to spine oncology focused on utilizing a mixture of clinical and imaging features to risk stratify mortality and frailty. Overall, these studies showed that ML is a helpful tool in tumor detection, differentiation, segmentation, predicting survival, predicting readmission rates of patients with either primary, metastatic, or intradural spine tumors.

CONCLUSION

Specialized neural networks and deep learning algorithms have shown to be highly effective at predicting malignant probability and aid in diagnosis. ML algorithms can predict the risk of tumor recurrence or progression based on imaging and clinical features. Additionally, ML can optimize treatment planning, such as predicting radiotherapy dose distribution to the tumor and surrounding normal tissue or in surgical resection planning. It has the potential to significantly enhance the accuracy and efficiency of health care delivery, leading to improved patient outcomes.

Quantitative, real-time scintillation imaging for experimental comparison of different dose and dose rate estimations in UHDR proton pencil beams

BACKGROUND

Ultra-high dose rate radiotherapy (UHDR-RT) has demonstrated normal tissue sparing capabilities, termed the FLASH effect; however, available dosimetry tools make it challenging to characterize the UHDR beams with sufficiently high concurrent spatial and temporal resolution. Novel dosimeters are needed for safe clinical implementation and improved understanding of the effect of UHDR-RT.

PURPOSE

Ultra-fast scintillation imaging has been shown to provide a unique tool for spatio-temporal dosimetry of conventional cyclotron pencil beam scanning (PBS) deliveries, indicating the potential use for characterization of UHDR PBS proton beams. The goal of this work is to introduce this novel concept and demonstrate its capabilities in recording high-resolution dose rate maps at FLASH-capable proton beam currents, as compared to log-based dose rate calculation, internally developed UHDR beam simulation, and a fast point detector (EDGE diode).

METHODS

The light response of a scintillator sheet located at isocenter and irradiated by PBS proton fields (40-210 nA, 250 MeV) was imaged by an ultra-fast iCMOS camera at 4.5-12 kHz sampling frequency. Camera sensor and image intensifier gain were optimized to maximize the dynamic range; the camera acquisition rate was also varied to evaluate the optimal sampling frequency. Large field delivery enabled flat field acquisition for evaluation of system response homogeneity. Image intensity was calibrated to dose with film and the recorded spatio-temporal data was compared to a PPC05 ion chamber, log-based reconstruction, and EDGE diode. Dose and dose rate linearity studies were performed to evaluate agreement under various beam conditions. Calculation of full-field mean and PBS dose rate maps were calculated to highlight the importance of high resolution, full-field information in UHDR studies.

RESULTS

Camera response was linear with dose (R2 = 0.997) and current (R22 = 0.98) in the range from 2-22 Gy and 40-210 nA, respectively, when compared to ion chamber readings. The deviation of total irradiation time calculated with the imaging system from the log file recordings decreased from 0.07% to 0.03% when imaging at 12 kfps versus 4.5 kfps. Planned and delivered spot positions agreed within 0.2 ± $\pm$ 0.1 mm and total irradiation time agreed within 0.2 ± $\pm$ 0.2 ms when compared with the log files, indicating the high concurrent spatial and temporal resolution. For all deliveries, the PBS dose rate measured at the diode location agreed between the imaging and the diode within 3% ± $\pm$ 2% and with the simulation within 5% ± $\pm$ 3% CONCLUSIONS: Full-field mapping of dose and dose rate is imperative for complete understanding of UHDR PBS proton dose delivery. The high linearity and various spatiotemporal metric reporting capabilities confirm the continued use of this camera system for UHDR beam characterization, especially for spatially resolved dose rate information.

Single institution experience of MRI-guided radiotherapy for thoracic tumors and clinical characteristics impacting treatment duty cycle

Introduction

MRI-guided radiotherapy (MRgRT) allows for direct motion management and real-time radiation treatment plan adaptation. We report our institutional experience using low strength 0.35T MRgRT for thoracic malignancies, and evaluate changes in treatment duty cycle between first and final MRgRT fractions.

Methods

All patients with intrathoracic tumors treated with MRgRT were included. The primary reason for MRgRT (adjacent organ at risk [OAR] vs. motion management [MM] vs. other) was recorded. Tumor location was classified as central (within 2cm of tracheobronchial tree) vs. non-central, and further classified by the Expanded HILUS grouping. Gross tumor volume (GTV) motion, planning target volume expansions, dose/fractionation, treatment plan time, and total delivery time were extracted from the treatment planning system. Treatment plan time was defined as the time for beam delivery, including multileaf collimator (MLC) motion, and gantry rotation. Treatment delivery time was defined as the time from beam on to completion of treatment, including treatment plan time and patient respiratory breath holds. Duty cycle was calculated as treatment plan time/treatment delivery time. Duty cycles were compared between first and final fraction using a two-sample t-test.

Results

Twenty-seven patients with thoracic tumors (16 non-small cell lung cancer and 11 thoracic metastases) were treated with MRgRT between 12/2021 and 06/2023. Fifteen patients received MRgRT due to OAR and 11 patients received MRgRT for motion management. 11 patients had central tumors and all were treated with MRgRT due to OAR risk. The median dose/fractionation was 50 Gy/5 fractions. For patients treated due to OAR (n=15), 80% had at least 1 adapted fraction during their course of radiotherapy. There was no plan adaptation for patients treated due to motion management (n=11). Mean GTV motion was significantly higher for patients treated due to motion management compared to OAR (16.1mm vs. 6.5mm, p=0.011). Mean duty cycle for fraction 1 was 54.2% compared to 62.1% with final fraction (p=0.004). Mean fraction 1 duty cycle was higher for patients treated due to OAR compared to patients treated for MM (61% vs. 45.0%, p=0.012).

Discussion

Duty cycle improved from first fraction to final fraction possibly due to patient familiarity with treatment. Duty cycle was improved for patients treated due to OAR risk, likely due to more central location and thus decreased target motion.

Deep learning automatic semantic segmentation of glioblastoma multiforme regions on multimodal magnetic resonance images

OBJECTIVES

In patients having naïve glioblastoma multiforme (GBM), this study aims to assess the efficacy of Deep Learning algorithms in automating the segmentation of brain magnetic resonance (MR) images to accurately determine 3D masks for 4 distinct regions: enhanced tumor, peritumoral edema, non-enhanced/necrotic tumor, and total tumor.

MATERIAL AND METHODS

A 3D U-Net neural network algorithm was developed for semantic segmentation of GBM. The training dataset was manually delineated by a group of expert neuroradiologists on MR images from the Brain Tumor Segmentation Challenge 2021 (BraTS2021) image repository, as ground truth labels for diverse glioma (GBM and low-grade glioma) subregions across four MR sequences (T1w, T1w-contrast enhanced, T2w, and FLAIR) in 1251 patients. The in-house test was performed on 50 GBM patients from our cohort (PerProGlio project). By exploring various hyperparameters, the network's performance was optimized, and the most optimal parameter configuration was identified. The assessment of the optimized network's performance utilized Dice scores, precision, and sensitivity metrics.

RESULTS

Our adaptation of the 3D U-net with additional residual blocks demonstrated reliable performance on both the BraTS2021 dataset and the in-house PerProGlio cohort, employing only T1w-ce sequences for enhancement and non-enhanced/necrotic tumor models and T1w-ce + T2w + FLAIR for peritumoral edema and total tumor. The mean Dice scores (training and test) were 0.89 and 0.75; 0.75 and 0.64; 0.79 and 0.71; and 0.60 and 0.55, for total tumor, edema, enhanced tumor, and non-enhanced/necrotic tumor, respectively.

CONCLUSIONS

The results underscore the high precision with which our network can effectively segment GBM tumors and their distinct subregions. The level of accuracy achieved agrees with the coefficients recorded in previous GBM studies. In particular, our approach allows model specialization for each of the different tumor subregions employing only those MR sequences that provide value for segmentation.

Magnetic resonance image-guided adaptive radiotherapy enables safe CTV-to-PTV margin reduction in prostate cancer: a cine MRI motion study

Introduction

We aimed to establish if stereotactic body radiotherapy to the prostate can be delivered safely using reduced clinical target volume (CTV) to planning target volume (PTV) margins on the 1.5T MR-Linac (MRL) (Elekta, Stockholm, Sweden), in the absence of gating.

Methods

Cine images taken in 3 orthogonal planes during the delivery of prostate SBRT with 36.25 Gray (Gy) in 5 fractions on the MRL were analysed. Using the data from 20 patients, the percentage of radiotherapy (RT) delivery time where the prostate position moved beyond 1, 2, 3, 4 and 5 mm in the left-right (LR), superior-inferior (SI), anterior-posterior (AP) and any direction was calculated.

Results

The prostate moved less than 3 mm in any direction for 90% of the monitoring period in 95% of patients. On a per-fraction basis, 93% of fractions displayed motion in all directions within 3 mm for 90% of the fraction delivery time. Recurring motion patterns were observed showing that the prostate moved with shallow drift (most common), transient excursions and persistent excursions during treatment.

Conclusion

A 3 mm CTV-PTV margin is safe to use for the treatment of 5 fraction prostate SBRT on the MRL, without gating. In the context of gating this work suggests that treatment time will not be extensively lengthened when an appropriate gating window is applied.

Clinical effects of re-evaluating a lung SBRT failure mode and effects analysis in a radiotherapy department

PURPOSE

The increasing complexity of radiation treatments can hinder its clinical success. This study aimed to better understand evolving risks by re-evaluating a Failure Mode and Effects Analysis (FMEA) in lung SBRT.

METHODS

An experienced multidisciplinary team conducted an FMEA and made a reassessment 3 years later. A process map was developed with potential failure modes (FMs) identified. High-risk FMs and their possible causes and corrective actions were determined. The initial FMEA analysis was compared to gain a deeper perspective.

RESULTS

We identified 232 FMs. The high-risk processes were plan approval, target contouring, and patient evaluation. The corrective measures were based on stricter standardization of plan approval, pre-planning peer review, and a supporting pretreatment checklist, which substantially reduced the risk priority number in the revised FMEA. In the FMEA reassessment, we observed that the increased complexity and number of patients receiving lung SBRT conditioned a more substantial presence of human factors and communication errors as causal conditions and a potential wrong dose as a final effect.

CONCLUSIONS

Conducting a lung SBRT FMEA analysis has identified high-risk conditions that have been effectively mitigated in an FMEA reanalysis. Plan approval has shown to be a weak link in the process. The increasing complexity of treatments and patient numbers have shifted causal factors toward human failure and communication errors. The potential of a wrong dose as a final effect augments in this scenario. We propose that digital and artificial intelligence options are needed to mitigate potential errors in high-complexity and high-risk RT scenarios.

Commissioning of a novel PET-Linac for biology-guided radiotherapy (BgRT)

BACKGROUND

Biology-guided radiotherapy (BgRT) is a novel radiotherapy delivery technique that utilizes the tumor itself to guide dynamic delivery of treatment dose to the tumor. The RefleXion X1 system is the first radiotherapy system developed to deliver SCINTIX® BgRT. The X1 is characterized by its split arc design, employing two 90-degree positron emission tomography (PET) arcs to guide therapeutic radiation beams in real time, currently cleared by FDA to treat bone and lung tumors.

PURPOSE

This study aims to comprehensively evaluate the capabilities of the SCINTIX radiotherapy delivery system by evaluating its sensitivity to changes in PET contrast, its adaptability in the context of patient motion, and its performance across a spectrum of prescription doses.

METHODS

A series of experimental scenarios, both static and dynamic, were designed to assess the SCINTIX BgRT system's performance, including an end-to-end test. These experiments involved a range of factors, including changes in PET contrast, motion, and prescription doses. Measurements were performed using a custom-made ArcCHECK insert which included a 2.2 cm spherical target and a c-shape structure that can be filled with a PET tracer with varying concentrations. Sinusoidal and cosine4 motion patterns, simulating patient breathing, was used to test the SCINTIX system's ability to deliver BgRT during motion-induced challenges. Each experiment was evaluated against specific metrics, including Activity Concentration (AC), Normalized Target Signal (NTS), and Biology Tracking Zone (BTZ) bounded dose-volume histogram (bDVH) pass rates. The accuracy of the delivered BgRT doses on ArcCHECK and EBT-XD film were evaluated using gamma 3%/2 mm and 3%/3 mm analysis.

RESULTS

In static scenarios, the X1 system consistently demonstrated precision and robustness in SCINTIX dose delivery. The end-to-end delivery to the spherical target yielded good results, with AC and NTS values surpassing the critical thresholds of 5 kBq/mL and 2, respectively. Furthermore, bDVH analysis consistently confirmed 100% pass rates. These results were reaffirmed in scenarios involving changes in PET contrast, emphasizing the system's ability to adapt to varying PET avidities. Gamma analysis with 3%/2 mm (10% dose threshold) criteria consistently achieved pass rates > 91.5% for the static tests. In dynamic SCINTIX delivery scenarios, the X1 system exhibited adaptability under conditions of motion. Sinusoidal and cosine4 motion patterns resulted in 3%/3 mm gamma pass rates > 87%. Moreover, the comparison with gated stereotactic body radiotherapy (SBRT) delivery on a conventional c-arm Linac resulted in 93.9% gamma pass rates and used as comparison to evaluate the interplay effect. The 1 cm step shift tests showed low overall gamma pass rates of 60.3% in ArcCHECK measurements, while the doses in the PTV agreed with the plan with 99.9% for 3%/3 mm measured with film.

CONCLUSIONS

The comprehensive evaluation of the X1 radiotherapy delivery system for SCINTIX BgRT demonstrated good agreement for the static tests. The system consistently achieved critical metrics and delivered the BgRT doses per plan. The motion tests demonstrated its ability to co-localize the dose where the PET signal is and deliver acceptable BgRT dose distributions.

[Does radiation therapy for prostate cancer increase the risk of second cancers?]

PURPOSE

The increased risk of second cancer after prostate radiotherapy is a debated clinical concern. The objective of the study was to assess the risk of occurrence of second cancers after prostate radiation therapy based on the analysis the literature, and to identify potential factors explaining the discrepancies in results between studies.

MATERIALS AND METHODS

A review of the literature was carried out, comparing the occurrence of second cancers in patients all presenting with prostate cancer, treated or not by radiation.

RESULTS

This review included 30 studies reporting the occurrence of second cancers in 2,112,000 patients treated or monitored for localized prostate cancer, including 1,111,000 by external radiation therapy and 103,000 by brachytherapy. Regarding external radiation therapy, the average follow-up was 7.3years. The majority of studies (80%) involving external radiation therapy, compared to no external radiation therapy, showed an increased risk of second cancers with a hazard ratio ranging from 1.13 to 4.9, depending on the duration of the follow-up. The median time to the occurrence of these second cancers after external radiotherapy ranged from 4 to 6years. An increased risk of second rectal and bladder cancer was observed in 52% and 85% of the studies, respectively. Considering a censoring period of more than 10 years after irradiation, 57% and 100% of the studies found an increased risk of rectal and bladder cancer, without any impact in overall survival. Studies of brachytherapy did not show an increased risk of second cancer. However, these comparative studies, most often old and retrospective, had many methodological biases.

CONCLUSION

Despite numerous methodological biases, prostate external radiation therapy appears associated with a moderate increase in the risk of second pelvic cancer, in particular bladder cancer, without impacting survival. Brachytherapy does not increase the risk of a second cancer.

Gross failure rates and failure modes for a commercial AI-based auto-segmentation algorithm in head and neck cancer patients

PURPOSE

Artificial intelligence (AI) based commercial software can be used to automatically delineate organs at risk (OAR), with potential for efficiency savings in the radiotherapy treatment planning pathway, and reduction of inter- and intra-observer variability. There has been little research investigating gross failure rates and failure modes of such systems.

METHOD

50 head and neck (H&N) patient data sets with "gold standard" contours were compared to AI-generated contours to produce expected mean and standard deviation values for the Dice Similarity Coefficient (DSC), for four common H&N OARs (brainstem, mandible, left and right parotid). An AI-based commercial system was applied to 500 H&N patients. AI-generated contours were compared to manual contours, outlined by an expert human, and a gross failure was set at three standard deviations below the expected mean DSC. Failures were inspected to assess reason for failure of the AI-based system with failures relating to suboptimal manual contouring censored. True failures were classified into 4 sub-types (setup position, anatomy, image artefacts and unknown).

RESULTS

There were 24 true failures of the AI-based commercial software, a gross failure rate of 1.2%. Fifteen failures were due to patient anatomy, four were due to dental image artefacts, three were due to patient position and two were unknown. True failure rates by OAR were 0.4% (brainstem), 2.2% (mandible), 1.4% (left parotid) and 0.8% (right parotid).

CONCLUSION

True failures of the AI-based system were predominantly associated with a non-standard element within the CT scan. It is likely that these non-standard elements were the reason for the gross failure, and suggests that patient datasets used to train the AI model did not contain sufficient heterogeneity of data. Regardless of the reasons for failure, the true failure rate for the AI-based system in the H&N region for the OARs investigated was low (∼1%).

Evaluation of Deep Learning Clinical Target Volumes Auto-Contouring for Magnetic Resonance Imaging-Guided Online Adaptive Treatment of Rectal Cancer

Purpose

Segmentation of clinical target volumes (CTV) on medical images can be time-consuming and is prone to interobserver variation (IOV). This is a problem for online adaptive radiation therapy, where CTV segmentation must be performed every treatment fraction, leading to longer treatment times and logistic challenges. Deep learning (DL)-based auto-contouring has the potential to speed up CTV contouring, but its current clinical use is limited. One reason for this is that it can be time-consuming to verify the accuracy of CTV contours produced using auto-contouring, and there is a risk of bias being introduced. To be accepted by clinicians, auto-contouring must be trustworthy. Therefore, there is a need for a comprehensive commissioning framework when introducing DL-based auto-contouring in clinical practice. We present such a framework and apply it to an in-house developed DL model for auto-contouring of the CTV in rectal cancer patients treated with MRI-guided online adaptive radiation therapy.

Methods and Materials

The framework for evaluating DL-based auto-contouring consisted of 3 steps: (1) Quantitative evaluation of the model's performance and comparison with IOV; (2) Expert observations and corrections; and (3) Evaluation of the impact on expected volumetric target coverage. These steps were performed on independent data sets. The framework was applied to an in-house trained nnU-Net model, using the data of 44 rectal cancer patients treated at our institution.

Results

The framework established that the model's performance after expert corrections was comparable to IOV, and although the model introduced a bias, this had no relevant impact on clinical practice. Additionally, we found a substantial time gain without reducing quality as determined by volumetric target coverage.

Conclusions

Our framework provides a comprehensive evaluation of the performance and clinical usability of target auto-contouring models. Based on the results, we conclude that the model is eligible for clinical use.

Error detection using a multi-channel hybrid network with a low-resolution detector in patient-specific quality assurance

PURPOSE

This study aimed to develop a hybrid multi-channel network to detect multileaf collimator (MLC) positional errors using dose difference (DD) maps and gamma maps generated from low-resolution detectors in patient-specific quality assurance (QA) for Intensity Modulated Radiation Therapy (IMRT).

METHODS

A total of 68 plans with 358 beams of IMRT were included in this study. The MLC leaf positions of all control points in the original IMRT plans were modified to simulate four types of errors: shift error, opening error, closing error, and random error. These modified plans were imported into the treatment planning system (TPS) to calculate the predicted dose, while the PTW seven29 phantom was utilized to obtain the measured dose distributions. Based on the measured and predicted dose, DD maps and gamma maps, both with and without errors, were generated, resulting in a dataset with 3222 samples. The network's performance was evaluated using various metrics, including accuracy, sensitivity, specificity, precision, F1-score, ROC curves, and normalized confusion matrix. Besides, other baseline methods, such as single-channel hybrid network, ResNet-18, and Swin-Transformer, were also evaluated as a comparison.

RESULTS

The experimental results showed that the multi-channel hybrid network outperformed other methods, demonstrating higher average precision, accuracy, sensitivity, specificity, and F1-scores, with values of 0.87, 0.89, 0.85, 0.97, and 0.85, respectively. The multi-channel hybrid network also achieved higher AUC values in the random errors (0.964) and the error-free (0.946) categories. Although the average accuracy of the multi-channel hybrid network was only marginally better than that of ResNet-18 and Swin Transformer, it significantly outperformed them regarding precision in the error-free category.

CONCLUSION

The proposed multi-channel hybrid network exhibits a high level of accuracy in identifying MLC errors using low-resolution detectors. The method offers an effective and reliable solution for promoting quality and safety of IMRT QA.

Characterization of a flexible a-Si:H detector for in vivo dosimetry in therapeutic x-ray beams

BACKGROUND

The increasing use of complex and high dose-rate treatments in radiation therapy necessitates advanced detectors to provide accurate dosimetry. Rather than relying on pre-treatment quality assurance (QA) measurements alone, many countries are now mandating the use of in vivo dosimetry, whereby a dosimeter is placed on the surface of the patient during treatment. Ideally, in vivo detectors should be flexible to conform to a patient's irregular surfaces.

PURPOSE

This study aims to characterize a novel hydrogenated amorphous silicon (a-Si:H) radiation detector for the dosimetry of therapeutic x-ray beams. The detectors are flexible as they are fabricated directly on a flexible polyimide (Kapton) substrate.

METHODS

The potential of this technology for application as a real-time flexible detector is investigated through a combined dosimetric and flexibility study. Measurements of fundamental dosimetric quantities were obtained including output factor (OF), dose rate dependence (DPP), energy dependence, percentage depth dose (PDD), and angular dependence. The response of the a-Si:H detectors investigated in this study are benchmarked directly against commercially available ionization chambers and solid-state diodes currently employed for QA practices.

RESULTS

The a-Si:H detectors exhibit remarkable dose linearities in the direct detection of kV and MV therapeutic x-rays, with calibrated sensitivities ranging from (0.580 ± 0.002) pC/cGy to (19.36 ± 0.10) pC/cGy as a function of detector thickness, area, and applied bias. Regarding dosimetry, the a-Si:H detectors accurately obtained OF measurements that parallel commercially available detector solutions. The PDD response closely matched the expected profile as predicted via Geant4 simulations, a PTW Farmer ionization chamber and a PTW ROOS chamber. The most significant variation in the PDD performance was 5.67%, observed at a depth of 3 mm for detectors operated unbiased. With an external bias, the discrepancy in PDD response from reference data was confined to ± 2.92% for all depths (surface to 250 mm) in water-equivalent plastic. Very little angular dependence is displayed between irradiations at angles of 0° and 180°, with the most significant variation being a 7.71% decrease in collected charge at a 110° relative angle of incidence. Energy dependence and dose per pulse dependence are also reported, with results in agreement with the literature. Most notably, the flexibility of a-Si:H detectors was quantified for sample bending up to a radius of curvature of 7.98 mm, where the recorded photosensitivity degraded by (-4.9 ± 0.6)% of the initial device response when flat. It is essential to mention that this small bending radius is unlikely during in vivo patient dosimetry. In a more realistic scenario, with a bending radius of 15-20 mm, the variation in detector response remained within ± 4%. After substantial bending, the detector's photosensitivity when returned to a flat condition was (99.1 ± 0.5)% of the original response.

CONCLUSIONS

This work successfully characterizes a flexible detector based on thin-film a-Si:H deposited on a Kapton substrate for applications in therapeutic x-ray dosimetry. The detectors exhibit dosimetric performances that parallel commercially available dosimeters, while also demonstrating excellent flexibility results.

Technical feasibility of novel immunostimulatory low-dose radiation for polymetastatic disease with CBCT-based online adaptive and conventional approaches

PURPOSE

A workflow/planning strategy delivering low-dose radiation therapy (LDRT) (1 Gy) to all polymetastatic diseases using conventional planning/delivery (Raystation/Halcyon = "conventional") and the AI-based Ethos online adaptive RT (oART) platform is developed/evaluated.

METHODS

Using retrospective data for ten polymetastatic non-small cell lung cancer patients (5-52 lesions each) with PET/CTs, gross tumor volumes (GTVs) were delineated using PET standardized-uptake-value (SUV) thresholding. A 1 cm uniform expansion of GTVs to account for setup/contour uncertainty and organ motion-generated planning target volumes (PTVs). Dose optimization/calculation used the diagnostic CT from PET/CT. Dosimetric objectives were: Dmin,0.03cc ≥ 95% (acceptable variation (Δ) ≥ 90%), V100% ≥ 95% (Δ ≥ 90%), and D0.03cc ≤ 120% (Δ ≤ 125%). Additionally, online adaptation was simulated. When available, subsequent diagnostic CT was used to represent on-treatment CBCT. Otherwise, the CT from PET/CT used for initial planning was deformed to simulate clinically representative changes.

RESULTS

All initial plans generated, both for Raystation and Ethos, achieved clinical goals within acceptable variation. For all patients, Dmin,0.03cc ≥ 95%, V100% ≥ 95%, and D0.03cc ≤ 120% goals were achieved for 84.8%/99.5%, 97.7%/98.7%, 97.4%/92.3%, in conventional/Ethos plans, respectively. The ratio of 50% isodose volume to PTV volume (R50%), maximum dose at 2 cm from PTV (D2cm), and the ratio of the 100% isodose volume to PTV volume (conformity index) in Raystation/Ethos plans were 7.9/5.9; 102.3%/88.44%; and 0.99/1.01, respectively. In Ethos, online adapted plans maintained PTV coverage whereas scheduled plans often resulted in geographic misses due to changes in tumor size, patient position, and body habitus. The average total duration of the oART workflow was 26:15 (min:sec) ranging from 6:43 to 57:30. The duration of each oART workflow step as a function of a number of targets showed a low correlation coefficient for influencer generation and editing (R2 = 0.04 and 0.02, respectively) and high correlation coefficient for target generation, target editing and plan generation (R2 = 0.68, 0.63 and 0.69, respectively).

CONCLUSIONS

This study demonstrates feasibility of conventional planning/treatment with Raystation/Halcyon and highlights efficiency gains when utilizing semi-automated planning/online-adaptive treatment with Ethos for immunostimulatory LDRT conformally delivered to all sites of polymetastatic disease.

Organs-at-risk dose and normal tissue complication probability with dynamic trajectory radiotherapy (DTRT) for head and neck cancer

We compared dynamic trajectory radiotherapy (DTRT) to state-of-the-art volumetric modulated arc therapy (VMAT) for 46 head and neck cancer cases. DTRT had lower dose to salivary glands and swallowing structure, resulting in lower predicted xerostomia and dysphagia compared to VMAT. DTRT is deliverable on C-arm linacs with high dosimetric accuracy.

Artificial Intelligence and the future of radiotherapy planning: The Australian radiation therapists prepare to be ready

The use of artificial intelligence (AI) solutions is rapidly changing the way radiation therapy tasks, traditionally relying on human skills, are approached by enabling fast automation. This evolution represents a paradigm shift in all aspects of the profession, particularly for treatment planning applications, opening up opportunities but also causing concerns for the future of the multidisciplinary team. In Australia, radiation therapists (RTs), largely responsible for both treatment planning and delivery, are discussing the impact of the introduction of AI and the potential developments in the future of their role. As medical physicists, who are part of the multidisciplinary team, in this editorial we reflect on the considerations of RTs, and on the implications of this transition to AI.

Fast and accurate 3-D spine MRI segmentation using FastCleverSeg

Accurate and efficient segmenting of vertebral bodies, muscles, and discs is crucial for analyzing various spinal diseases. However, traditional methods are either laborious and time-consuming (manual segmentation) or require extensive training data (fully automatic segmentation). FastCleverSeg, our proposed semi-automatic segmentation approach, addresses those limitations by significantly reducing user interaction while maintaining high accuracy. First, we reduce user interaction by requiring the manual annotation of only two or three slices. Next, we automatically Estimate the Annotation on Intermediary Slices (EANIS) using traditional computer vision/graphics concepts. Finally, our proposed method leverages improved voxel weight balancing to achieve fast and precise volumetric segmentation in the segmentation process. Experimental evaluations on our assembled diverse MRI databases comprising 179 patients (60 male, 119 female), demonstrate a remarkable 25 ms (30 ms standard deviation) processing time and a significant reduction in user interaction compared to existing approaches. Importantly, FastCleverSeg maintains or surpasses the segmentation quality of competing methods, achieving a Dice score of 94%. This invaluable tool empowers physicians to efficiently generate reliable ground truths, expediting the segmentation process and paving the way for future integration with deep learning approaches. In turn, this opens exciting possibilities for future fully automated spine segmentation.

Femoral osteoporosis prediction model using autosegmentation and machine learning analysis with PyRadiomics on abdomen-pelvic computed tomography (CT)

Background

With the advancement of artificial intelligence technology and radiomics analysis, opportunistic prediction of osteoporosis with computed tomography (CT) is a new paradigm in osteoporosis screening. This study aimed to assess the diagnostic performance of osteoporosis prediction by the combination of autosegmentation of the proximal femur and machine learning analysis with a reference standard of dual-energy X-ray absorptiometry (DXA).

Methods

Abdomen-pelvic CT scans were retrospectively analyzed from 1,122 patients who received both DXA and abdomen-pelvic computed tomography (APCT) scan from January 2018 to December 2020. The study cohort consisted of a training cohort and a temporal validation cohort. The left proximal femur was automatically segmented, and a prediction model was built by machine-learning analysis using a random forest (RF) analysis and 854 PyRadiomics features. The technical success rate of autosegmentation, diagnostic test, area under the receiver operator characteristics curve (AUC), and precision recall curve (AUC-PR) analysis were used to analyze the training and validation cohorts.

Results

The osteoporosis prevalence of the training and validation cohorts was 24.5%, and 10.3%, respectively. The technical success rate of autosegmentation of the proximal femur was 99.7%. In the diagnostic test, the training and validation cohorts showed 78.4% vs. 63.3% sensitivity, 89.4% vs. 98.1% specificity. The prediction performance to identify osteoporosis within the groups used for training and validation cohort was high and the AUC and AUC-PR to forecast the occurrence of osteoporosis within the training and validation cohorts were 90.8% [95% confidence interval (CI), 88.4-93.2%] vs. 78.0% (95% CI, 76.0-79.9%) and 94.6% (95% CI, 89.3-99.8%) vs. 88.8% (95% CI, 86.2-91.5%), respectively.

Conclusions

The osteoporosis prediction model using autosegmentation of proximal femur and machine-learning analysis with PyRadiomics features on APCT showed excellent diagnostic feasibility and technical success.

AAPM Task Group 334: A guidance document to using radiotherapy immobilization devices and accessories in an MR environment

Use of magnetic resonance (MR) imaging in radiation therapy has increased substantially in recent years as more radiotherapy centers are having MR simulators installed, requesting more time on clinical diagnostic MR systems, or even treating with combination MR linear accelerator (MR-linac) systems. With this increased use, to ensure the most accurate integration of images into radiotherapy (RT), RT immobilization devices and accessories must be able to be used safely in the MR environment and produce minimal perturbations. The determination of the safety profile and considerations often falls to the medical physicist or other support staff members who at a minimum should be a Level 2 personnel as per the ACR. The purpose of this guidance document will be to help guide the user in making determinations on MR Safety labeling (i.e., MR Safe, Conditional, or Unsafe) including standard testing, and verification of image quality, when using RT immobilization devices and accessories in an MR environment.

Detection of early pulmonary emphysema by multi-contrast x-ray Talbot-Lau interferometer

BACKGROUND

Pulmonary emphysema is a part of chronic obstructive pulmonary disease, which is an irreversible chronic respiratory disease. In order to avoid further damage to lung tissue, early diagnosis and treatment of pulmonary emphysema is essential.

PURPOSE

Early pulmonary emphysema diagnosis is difficult with conventional radiographic imaging. Recently, x-ray phase contrast imaging has proved to be an effective and promising imaging strategy for soft tissue, due to its high sensitivity and multi-contrast. The aim of this study is to diagnose pulmonary emphysema early utilizing an x-ray Talbot-Lau interferometer (TLI).

METHODS

We successfully established the mouse model of emphysema by porcine pancreatic elastase treatment, and then used the established x-ray TLI to perform imaging experiments on the mice with different treatment time. The traditional absorption CT and phase contrast CT were obtained simultaneously through TLI. The CT results and histopathology of mice lung in different treatment time were quantitatively analyzed.

RESULTS

By imaging mice lungs, it can be found that phase contrast has higher sensitivity than absorption contrast in early pulmonary emphysema. The results show that the phase contrast signal could distinguish the pulmonary emphysema earlier than the conventional attenuation signal, which can be consistent with histological images. Through the quantitative analysis of pathological section and phase contrast CT, it can be found that there is a strong linear correlation.

CONCLUSIONS

In this study, we quantitatively analyze mean linear intercept of histological sections and CT values of mice. The results show that the phase contrast signal has higher imaging sensitivity than the attenuation signal. X-ray TLI multi-contrast imaging is proved as a potential diagnostic method for early pulmonary emphysema in mice.

CycleSeg: Simultaneous synthetic CT generation and unsupervised segmentation for MR-only radiotherapy treatment planning of prostate cancer

BACKGROUND

MR-only radiotherapy treatment planning is an attractive alternative to conventional workflow, reducing scan time and ionizing radiation. It is crucial to derive the electron density map or synthetic CT (sCT) from MR data to perform dose calculations to enable MR-only treatment planning. Automatic segmentation of relevant organs in MR images can accelerate the process by preventing the time-consuming manual contouring step. However, the segmentation label is available only for CT data in many cases.

PURPOSE

We propose CycleSeg, a unified framework that generates sCT and corresponding segmentation from MR images without access to MR segmentation labels METHODS: CycleSeg utilizes the CycleGAN formulation to perform unpaired synthesis of sCT and image alignment. To enable MR (sCT) segmentation, CycleSeg incorporates unsupervised domain adaptation by using a pseudo-labeling approach with feature alignment in semantic segmentation space. In contrast to previous approaches that perform segmentation on MR data, CycleSeg could perform segmentation on both MR and sCT. Experiments were performed with data from prostate cancer patients, with 78/7/10 subjects in the training/validation/test sets, respectively.

RESULTS

CycleSeg showed the best sCT generation results, with the lowest mean absolute error of 102.2 and the lowest Fréchet inception distance of 13.0. CycleSeg also performed best on MR segmentation, with the highest average dice score of 81.0 and 81.1 for MR and sCT segmentation, respectively. Ablation experiments confirmed the contribution of the proposed components of CycleSeg.

CONCLUSION

CycleSeg effectively synthesized CT and performed segmentation on MR images of prostate cancer patients. Thus, CycleSeg has the potential to expedite MR-only radiotherapy treatment planning, reducing the prescribed scans and manual segmentation effort, and increasing throughput.

How Long Does Contouring Really Take? Results of the Royal College of Radiologists Contouring Surveys

AIMS

The success and safety of modern radiotherapy relies on accurate contouring. Understanding the time taken to complete radiotherapy contours is critical to informing workforce planning and, in the context of a workforce shortfall, advocating for investment in technology and multi-professional skills mix. We aimed to quantify the time taken to delineate target volumes for radical radiotherapy.

MATERIALS AND METHODS

The Royal College of Radiologists circulated two electronic surveys via email to all clinical oncology consultants in the UK. The individual case survey requested anonymous data regarding the next five patients contoured for radical radiotherapy. The second survey collected data on respondents' usual practice in radiotherapy contouring.

RESULTS

The median time to contour one radiotherapy case was 85 minutes (IQR = 50-131 minutes). Marked variability between and within tumour sites was evident: paediatric cancers took the most time (median = 210 minutes, IQR = 87.5 minutes), followed by head and neck and gynaecological cancers (median = 120 minutes, IQR = 71 and 72.5 minutes respectively). Breast cancer contouring required the least time (median = 43 minutes, IQR = 60 minutes). Radiotherapy technique, inclusion of nodes and 4D CT planning were associated with longer contouring times. A non-medical professional was involved in contouring in 65% of cases, but clinical oncology consultants were involved in target volume delineation in 90% of cases, and OARs in 74%. Peer review took place in 46% of cases with 56% of consultants reporting no time for peer review in their job plan.

CONCLUSION

Contouring for radical radiotherapy is complex and time-consuming, and despite increasing involvement of non-medical professionals, clinical oncology consultants remain the primary practitioners. Peer review practice is variable and time is often a limiting factor. Many factors influence the time required for contouring, and departments should take these factors and the need for peer-review into account when developing job plans.

Definitive Radiotherapy for Stage I Gastric Mucosa-Associated Lymphoid Tissue Lymphoma: A Retrospective Cohort of Unique-Dose Administration of 30 Gy in 15 Fractions and Analysis of Remission Duration

Background

Gastric mucosa-associated lymphoid tissue (MALT) lymphoma constitutes a significant proportion of primary stomach lymphomas. The optimal dosage for radiotherapy and standardized follow-up protocols are yet to be universally established. This study focuses on stage I gastric MALT lymphoma patients, presenting clinical outcomes of radiotherapy with a unique dose of 30 Gy in 15 fractions and analyzing remission time.

Methods

A retrospective cohort study, approved by the institutional review board, included consecutive stage I gastric MALT lymphoma patients undergoing curative radiotherapy between 2008 and 2022. Staging followed the Lugano Modification of the Ann Arbor Staging System. The prescribed dose was uniform dose of 30 Gy in 15 fractions.

Results

Fifty-three patients were eligible, with a median age of 63 years. All achieved complete remission (CR), with a median CR time of 3.9 months. At a median follow-up of 56.8 months, no deaths occurred, and three recurrences were noted. The 5-year overall survival, local control survival, and disease-free survival rates were 100%, 100%, and 97.7%, respectively. No severe acute adverse events were observed.

Conclusion

The study demonstrates sustained and favorable long-term disease control with a 30 Gy dose in 15 fractions for stage I gastric MALT lymphoma. Comparisons with existing literature highlight the efficacy and safety of radiotherapy in achieving durable remission. Ongoing efforts explore dose reduction and technological advancements to minimize toxicity. This study emphasizes the importance of awaiting clinical response confirmation to validate these outcomes in patients with gastric MALT lymphoma.

A Randomised Phase II Trial to Evaluate the Feasibility of Radiotherapy Dose Escalation, Facilitated by Intensity-Modulated Arc Radiotherapy Techniques, in High-Risk Neuroblastoma

BACKGROUND AND PURPOSE

For high-risk neuroblastoma, planning target volume coverage is often compromised to respect adjacent kidney tolerance. This trial investigated whether intensity-modulated arc radiotherapy techniques (IMAT) could facilitate dose escalation better than conventional techniques.

MATERIALS AND METHODS

Children with high-risk abdominal neuroblastoma referred for radiotherapy to the primary tumour site and involved regional lymph nodes were randomised to receive either standard dose (21 Gy in 14 fractions) or escalated dose (36 Gy in 24 fractions) radiotherapy. Dual planning with both a conventional anterior-posterior parallel opposed pair radiotherapy technique and an IMAT technique was performed. The quality of target volume and organ-at-risk delineation, and dosimetric plans, were externally reviewed. Dosimetric parameters were used to judge the superior technique for treatment. This feasibility trial was not powered to detect improvement in outcome with dose escalation.

RESULTS

Between 2017 and 2020, 50 patients were randomised and dual-planned. The IMAT technique was judged more favourable in 48 patients. In all patients randomised to receive 36 Gy, IMAT would have permitted delivery of the full dose (median D50% 36.0 Gy, inter-quartile range 36.0-36.1 Gy) to the target volume, whereas dose compromise would have been required with conventional planning (median D50% 35.6 Gy, inter-quartile range 28.7-35.9 Gy).

CONCLUSION

IMAT facilitates safe dose escalation to 36 Gy in patients receiving radiotherapy for neuroblastoma. The value of dose escalation is now being evaluated in a current prospective phase III randomised trial.