MRI visibility and displacement of elective lymph nodes during radiotherapy in head and neck cancer patients

Background and purpose

To decrease the impact of radiotherapy to healthy tissues in the head and neck region, we propose to restrict the elective neck irradiation to elective lymph nodes at risk of containing micro metastases instead of the larger lymph node volumes. To assess whether this new concept is achievable in the clinic, we determined the number, volume changes and displacement of elective lymph nodes during the course of radiotherapy.

Materials and methods

MRI scans of 10 head and neck cancer (HNC) patients were acquired before radiotherapy and in week 2, 3, 4 and 5 during radiotherapy. The weekly delineations of elective lymph nodes inside the lymph node levels (Ib/II/III/IVa/V) were rigidly registered and analyzed regarding number and volume. The displacement of elective lymph nodes was determined by center of mass (COM) distances, vector-based analysis and the isotropic contour expansion of the lymph nodes of the pre-treatment scan or the scan of the previous week in order to geographically cover 95% of the lymph nodes in the scans of the other weeks.

Results

On average, 31 elective lymph nodes in levels Ib-V on each side of the neck were determined. This number remained constant throughout radiotherapy in most lymph node levels. The volume of the elective lymph nodes reduced significantly in all weeks, up to 50% in week 5, compared to the pre-treatment scan. The largest median COM displacements were seen in level V, for example 5.2 mm in week 5 compared to the pre-treatment scan. The displacement of elective lymph nodes was mainly in cranial direction. Geographical coverage was obtained when the lymph node volumes were expanded with 7 mm in case the pre-treatment scan was used and 6.5 mm in case the scan of the previous week was used.

Conclusion

Elective lymph nodes of HNC patients remained visible on MRI and decreased in size during radiotherapy. The displacement of elective lymph nodes differ per lymph node level and were mainly directed cranially. Weekly adaptation does not seem to improve coverage of elective lymph nodes. Based on our findings we expect elective lymph node irradiation is achievable in the clinic.

MRI-based delta-radiomic features for prediction of local control in liver lesions treated with stereotactic body radiation therapy

Real-time magnetic resonance image guided stereotactic ablative radiotherapy (MRgSBRT) is used to treat abdominal tumors. Longitudinal data is generated from daily setup images. Our study aimed to identify delta radiomic texture features extracted from these images to predict for local control in patients with liver tumors treated with MRgSBRT. Retrospective analysis of an IRB-approved database identified patients treated with MRgSBRT for primary liver and secondary metastasis histologies. Daily low field strength (0.35 T) images were retrieved, and the gross tumor volume was identified on each image. Next, images' gray levels were equalized, and 39 s-order texture features were extracted. Delta-radiomics were calculated as the difference between feature values on the initial scan and after delivered biological effective doses (BED, α/β = 10) of 20 Gy and 40 Gy. Then, features were ranked by the Gini Index during training of a random forest model. Finally, the area under the receiver operating characteristic curve (AUC) was estimated using a bootstrapped logistic regression with the top two features. We identified 22 patients for analysis. The median dose delivered was 50 Gy in 5 fractions. The top two features identified after delivery of BED 20 Gy were gray level co-occurrence matrix features energy and gray level size zone matrix based large zone emphasis. The model generated an AUC = 0.9011 (0.752-1.0) during bootstrapped logistic regression. The same two features were selected after delivery of a BED 40 Gy, with an AUC = 0.716 (0.600-0.786). Delta-radiomic features after a single fraction of SBRT predicted local control in this exploratory cohort. If confirmed in larger studies, these features may identify patients with radioresistant disease and provide an opportunity for physicians to alter management much sooner than standard restaging after 3 months. Expansion of the patient database is warranted for further analysis of delta-radiomic features.

The role of multiple anatomical scenarios in plan optimization for carbon ion radiotherapy of pancreatic cancer

PURPOSE /OBJECTIVE

To quantify benefits of robust optimization on multiple 4DCT acquisitions combined with off-line treatment adaptation for neoadjuvant carbon ion therapy (CIRT) of pancreatic cancer.

MATERIAL/METHODS

For 10 previously treated patients, 4DCTs were acquired around -15 (CT_Plan), -5 (RE₁), -1 (RE₂) and +6 (RE₃) days from RT start. Treatment plans were newly optimized to a dose prescription of 38.4 Gy(RBE) (8 fractions) with a constraint of 38 Gy(RBE) to 1% of the gastrointestinal organs at risk volume (D_1%). Three strategies were tested: (A) robust optimization on CT_Plan maximum exhale (0Ex) with 3 mm set-up, 3% range uncertainty, including 30%-inhale; (B) addition of the RE₁-0Ex scenario; (C) plan recalculation at each RE_i and adaptation (RP_i) according to deviation thresholds from clinical goals. The cumulative variation of target coverage and GI-OARs doses was evaluated. Duodenum contours of all 4DCTs of each patient were registered on CT_Plan-0Ex. The capacity of pre-RT acquisitions to predict duodenum position was investigated by computing the intersection of contours at CT_plan, RE₁, or their union, with respect to subsequent 4DCTs and the CTV, coupled with increasing margin.

RESULTS

(A) No recalculation exceeded the D_1% constraint. (B) The inclusion of RE₁-0Ex in the optimization problem improved inter-fraction robustness on a patient-specific basis, but was non-significant on average. (C) Half of the plans would be re-optimized to recover target coverage and/or minimize duodenum dose, at least once. A significant difference was observed between pre-RT duodenum contours when intersecting subsequent contours, either with a margin expansion.

CONCLUSION

Anatomical variations highlighted at multiple RE_i proved that a fast and efficient online adaptation is essential to optimize treatment quality of CIRT for pancreatic cancer.

Online adaptive radiotherapy of anal cancer: Normal tissue sparing, target propagation methods, and first clinical experience

BACKGROUND AND PURPOSE

Online adaptive radiotherapy (oART) potentially spares OARs as PTV margins are reduced. This study evaluates dosimetric benefits, compared to standard non-adaptive radiotherapy (non-ART), target propagation methods, and first clinical treatments of CBCT-guided oART of anal cancer.

MATERIALS AND METHODS

Treatment plans with standard non-ART and reduced oART PTV margins were retrospectively generated for 23 consecutive patients with anal cancer. For five patients randomly selected among the 23 patients, weekly CBCT-guided oART sessions were simulated, where the targets were either deformed or rigidly propagated. Preferred target propagation method and dose to OARs were evaluated. Ten consecutive patients with anal cancer were treated with CBCT-guided oART. Target propagation methods and oART procedure time were evaluated.

RESULTS

For the retrospective treatment plans, oART resulted in median reductions in bowel bag V_45Gy of 11.4 % and bladder V_35Gy of 16.1%. Corresponding values for the simulated sessions were 7.5% and 27.1%. In the simulated sessions, 35% of all targets were deformed while 65% were rigidly propagated. Manual editing and rigid propagation were necessary to obtain acceptable target coverage. In the clinical treatments, the primary and some elective targets were rigidly propagated, while other targets were deformed. The median oART procedure time, measured from CBCT acquisition to completion of plan review and QA, was 23 min.

CONCLUSIONS

Simulated oART reduced the dose to OARs, indicating potential reduction in toxicity. Rigid propagation of targets was necessary to reduce the need for manual edit. Clinical treatments demonstrated that oART of anal cancer is feasible but time-consuming.

Deep learning-based 4D-synthetic CTs from sparse-view CBCTs for dose calculations in adaptive proton therapy

BACKGROUND

Time-resolved 4D cone beam-computed tomography (4D-CBCT) allows a daily assessment of patient anatomy and respiratory motion. However, 4D-CBCTs suffer from imaging artifacts that affect the CT number accuracy and prevent accurate proton dose calculations. Deep learning can be used to correct CT numbers and generate synthetic CTs (sCTs) that can enable CBCT-based proton dose calculations.

PURPOSE

In this work, sparse view 4D-CBCTs were converted into 4D-sCT utilizing a deep convolutional neural network (DCNN). 4D-sCTs were evaluated in terms of image quality and dosimetric accuracy to determine if accurate proton dose calculations for adaptive proton therapy workflows of lung cancer patients are feasible.

METHODS

A dataset of 45 thoracic cancer patients was utilized to train and evaluate a DCNN to generate 4D-sCTs, based on sparse view 4D-CBCTs reconstructed from projections acquired with a 3D acquisition protocol. Mean absolute error (MAE) and mean error were used as metrics to evaluate the image quality of single phases and average 4D-sCTs against 4D-CTs acquired on the same day. The dosimetric accuracy was checked globally (gamma analysis) and locally for target volumes and organs-at-risk (OARs) (lung, heart, and esophagus). Furthermore, 4D-sCTs were also compared to 3D-sCTs. To evaluate CT number accuracy, proton radiography simulations in 4D-sCT and 4D-CTs were compared in terms of range errors. The clinical suitability of 4D-sCTs was demonstrated by performing a 4D dose reconstruction using patient specific treatment delivery log files and breathing signals.

RESULTS

4D-sCTs resulted in average MAEs of 48.1 ± 6.5 HU (single phase) and 37.7 ± 6.2 HU (average). The global dosimetric evaluation showed gamma pass ratios of 92.3% ± 3.2% (single phase) and 94.4% ± 2.1% (average). The clinical target volume showed high agreement in D₉₈ between 4D-CT and 4D-sCT, with differences below 2.4% for all patients. Larger dose differences were observed in mean doses of OARs (up to 8.4%). The comparison with 3D-sCTs showed no substantial image quality and dosimetric differences for the 4D-sCT average. Individual 4D-sCT phases showed slightly lower dosimetric accuracy. The range error evaluation revealed that lung tissues cause range errors about three times higher than the other tissues.

CONCLUSION

In this study, we have investigated the accuracy of deep learning-based 4D-sCTs for daily dose calculations in adaptive proton therapy. Despite image quality differences between 4D-sCTs and 3D-sCTs, comparable dosimetric accuracy was observed globally and locally. Further improvement of 3D and 4D lung sCTs could be achieved by increasing CT number accuracy in lung tissues.

Clinical application of a sub-fractionation workflow for intrafraction re-planning during prostate radiotherapy treatment on a 1.5 Tesla MR-Linac: A practical method to mitigate intrafraction motion

BACKGROUND

Intrafraction motion during radiotherapy limits margin reduction and dose escalation. Magnetic resonance (MR)-guided linear accelerators (MR-Linac) have emphasised this issue by enabling intrafraction imaging. We present and clinically apply a new workflow to counteract systematic intrafraction motion during MR-guided stereotactic body radiotherapy (SBRT).

MATERIALS AND METHODS

With the sub-fractionation workflow, the daily dose is delivered in multiple sequential parts (sub-fractions), each adapted to the latest anatomy. As each sub-fractionation treatment plan complies with the dose constraints, no online dose accumulation is required. Imaging and treatment planning are executed in parallel with dose delivery to minimise dead time, enabling an efficient workflow. The workflow was implemented on a 1.5 T MR-Linac and applied in 15 prostate cancer (PCa) patients treated with 5 × 7.25 Gy in two sub-fractions of 3.625 Gy (10 × 3.625 Gy in total). Intrafraction clinical target volume (CTV) motion was determined and compared to a workflow with single-plan delivery. Furthermore, required planning target volume (PTV) margins were determined.

RESULTS

Average on-table time was 42.7 min. Except for two fractions, all fractions were delivered within 60 min. Average intrafraction 3D CTV displacement (±standard deviation) was 1.1 mm (± 0.7) with the sub-fractionation workflow, whereas this was up to 3.5 mm (± 2.4) without sub-fractionation. Calculated PTV margins required with sub-fractionation were 1.0 mm (left-right), 2.4 mm (cranial-caudal), and 2.6 mm (anterior-posterior).

CONCLUSION

Feasibility of the sub-fractionation workflow was demonstrated in 15 PCa patients treated with two sub-fractions on a 1.5 T MR-Linac. The workflow allows for significant PTV margin reduction in these patients by reducing systematic intrafraction motion during SBRT.

Clinical commissioning of an adaptive radiotherapy platform: Results and recommendations

Online adaptive radiotherapy platforms present a unique challenge for commissioning as guidance is lacking and specialized adaptive equipment, such as deformable phantoms, are rare. We designed a novel adaptive commissioning process consisting of end-to-end tests using standard clinical resources. These tests were designed to simulate anatomical changes regularly observed at patient treatments. The test results will inform users of the magnitude of uncertainty from on-treatment changes during the adaptive workflow and the limitations of their systems. We implemented these tests for the cone-beam computed tomography (CT)-based Varian Ethos online adaptive platform. Many adaptive platforms perform online dose calculation on a synthetic CT (synCT). To assess the impact of the synCT generation and online dose calculation on dosimetric accuracy, we conducted end-to-end tests using commonly available equipment: a CIRS IMRT Thorax phantom, PinPoint ionization chamber, Gafchromic film, and bolus. Four clinical scenarios were evaluated: weight gain and weight loss were simulated by adding and removing bolus, internal target shifts were simulated by editing the CTV during the adaptive workflow to displace it, and changes in gas were simulated by removing and reinserting rods in varying phantom locations. The effect of overriding gas pockets during planning was also assessed. All point dose measurements agreed within 2.7% of the calculated dose, with one exception: a scenario simulating gas present in the planning CT, not overridden during planning, and dissipating at treatment. Relative film measurements passed gamma analysis (3%/3 mm criteria) for all scenarios. Our process validated the Ethos dose calculation for online adapted treatment plans. Based on our results, we made several recommendations for our clinical adaptive workflow. This commissioning process used commonly available equipment and, therefore, can be applied in other clinics for their respective online adaptive platforms.

Quality assurance for MRI-only radiation therapy: A voxel-wise population-based methodology for image and dose assessment of synthetic CT generation methods

The quality assurance of synthetic CT (sCT) is crucial for safe clinical transfer to an MRI-only radiotherapy planning workflow. The aim of this work is to propose a population-based process assessing local errors in the generation of sCTs and their impact on dose distribution. For the analysis to be anatomically meaningful, a customized interpatient registration method brought the population data to the same coordinate system. Then, the voxel-based process was applied on two sCT generation methods: a bulk-density method and a generative adversarial network. The CT and MRI pairs of 39 patients treated by radiotherapy for prostate cancer were used for sCT generation, and 26 of them with delineated structures were selected for analysis. Voxel-wise errors in sCT compared to CT were assessed for image intensities and dose calculation, and a population-based statistical test was applied to identify the regions where discrepancies were significant. The cumulative histograms of the mean absolute dose error per volume of tissue were computed to give a quantitative indication of the error for each generation method. Accurate interpatient registration was achieved, with mean Dice scores higher than 0.91 for all organs. The proposed method produces three-dimensional maps that precisely show the location of the major discrepancies for both sCT generation methods, highlighting the heterogeneity of image and dose errors for sCT generation methods from MRI across the pelvic anatomy. Hence, this method provides additional information that will assist with both sCT development and quality control for MRI-based planning radiotherapy.

Statistical evaluation of the effectiveness of dual amplitude-gated stereotactic body radiotherapy using fiducial markers and lung volume

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Approximately 30% of the fiducial markers demonstrated a low correlation on comparing lung volumes.

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Monitoring of lung volume can achieve stable tracking of lung tumors.

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Dual monitoring by employing the marker and lung volume may possibly avoid the deterioration of monitoring accuracy.

Background and purpose

The low tracking accuracy of lung stereotactic body radiotherapy (SBRT) risks reduced treatment efficacy. We used four-dimensional computed tomography (4DCT) images to determine the correlation between changes in fiducial marker positions and lung volume for lung tumors, and we evaluated the effectiveness of the combined use of these images in lung SBRT.

Materials and methods

Data of 30 patients who underwent fiducial marker placement were retrospectively analyzed. We calculated the motion amplitudes of the center of gravity coordinates of the lung tumor and fiducial markers in each phase and the ipsilateral, contralateral, and bilateral lung volumes using 4DCT. Moreover, we calculated the cross-correlation coefficient between the fiducial marker position and the lung volume changes waveform for the motion amplitude waveform of the lung tumor over three gating windows (all phases, ≤2 mm³, and ≤3 mm³).

Results

Compared with the lung volume, approximately 30 % of the fiducial markers demonstrated a low correlation with the lung tumor. In the ≤2 mm³ and ≤3 mm³ gating windows, the cross-correlation coefficients between the lung tumor and the optimal marker (r > 0.9: 83 % and 86 %) were significantly different for all fiducial markers (r > 0.9: 39 %, 53 %) and the ipsilateral (r > 0.9: 35 % and 40 %), contralateral (r > 0.9: 44 % and 41 %), and bilateral (r > 0.9: 39 % and 45 %) lung volumes.

Conclusions

Some of the fiducial markers showed a low correlation with the lung tumor. This study indicated that the combined use of lung volume monitoring can improve tracking accuracy.

Knowledge-based planning for multi-isocenter VMAT total marrow irradiation

Purpose

Total marrow irradiation (TMI) involves optimization of extremely large target volumes and requires extensive clinical experience and time for both treatment planning and delivery. Although volumetric modulated arc therapy (VMAT) achieves substantial reduction in treatment delivery time, planning process still presents a challenge due to use of multiple isocenters and multiple overlapping arcs. We developed and evaluated a knowledge-based planning (KBP) model for VMAT-TMI to address these clinical challenges.

Methods

Fifty-one patients previously treated in our clinic were selected for the model training, while 22 patients from another clinic were used as a test set. All plans used a 3-isocenter to cover sub-target volumes of head and neck (HN), chest, and pelvis. Chest plan was performed first and then used as the base dose for both the HN and pelvis plans to reduce hot spots around the field junctions. This resulted in a wide range of dose-volume histograms (DVH). To address this, plans without the base-dose plan were optimized and added to the library to train the model.

Results

KBP achieved our clinical goals (95% of PTV receives 100% of Rx) in a single day, which used to take 4-6 days of effort without KBP. Statistically significant reductions with KBP were observed in the mean dose values to brain, lungs, oral cavity and lenses. KBP substantially improved 105% dose spillage (14.1% ± 2.4% vs 31.8% ± 3.8%), conformity index (1.51 ± 0.06 vs 1.81 ± 0.12) and homogeneity index (1.25 ± 0.02 vs 1.33 ± 0.03).

Conclusions

KBP improved dosimetric performance with uniform quality. It reduced dependence on planner experience and achieved a factor of 5 reduction in planning time to produce quality plans to allow its wide-spread clinical implementation.

Same-day consultation, simulation and lung Stereotactic Ablative Radiotherapy delivery on a Magnetic Resonance-linac

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A same-day consultation and lung SABR workflow was introduced, and experience in 10 patients reported.

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A detailed simulation procedure and the use of real-time cine magnetic resonance imaging enabled accurate treatment delivery.

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All patients reported satisfaction with the procedure, which improved patient convenience.

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On average, at least 94.4% (5th percentile) of the GTV was always located inside the PTV during beam-on.

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System-latency for triggering a beam-off event comprised 5.3% of the delivery time.

Background and Purpose

Magnetic resonance-guided radiotherapy (MRgRT) with real-time intra-fraction tumor motion monitoring allows for high precision Stereotactic Ablative Radiotherapy (SABR). This study aimed to investigate the clinical feasibility, patient satisfaction and delivery accuracy of single-fraction MR-guided SABR in a single day (one-stop-shop, OSS).

Methods and Materials

Ten patients with small lung tumors eligible for single fraction treatments were included. The OSS procedure consisted of consultation, treatment simulation, treatment planning and delivery. Following SABR delivery, patients completed a reported experience measure (PREM) questionnaire. Prescribed doses ranged 28–34 Gy. Median GTV was 2.2 cm³ (range 1.3–22.9 cm³). A gating boundary of 3 mm, and PTV margin of 5 mm around the GTV, were used with auto-beam delivery control. Accuracy of SABR delivery was studied by analyzing delivered MR-cines reconstructed from machine log files.

Results

All 10 patients completed the OSS procedure in a single day, and all reported satisfaction with the process. Median time for the treatment planning step and the whole procedure were 2.8 h and 6.6 h, respectively. With optimization of the procedure, treatment could be completed in half a day. During beam-on, the 3 mm tracking boundary encompassed between 78.0 and 100 % of the GTV across all patients, with corresponding PTV values being 94.4–100 % (5th-95th percentiles). On average, system-latency for triggering a beam-off event comprised 5.3 % of the delivery time. Latency reduced GTV coverage by an average of −0.3 %. Duty-cycles during treatment delivery ranged from 26.1 to 64.7 %.

Conclusions

An OSS procedure with MR-guided SABR for lung cancer led to good patient satisfaction. Gated treatment delivery was highly accurate with little impact of system-latency.

2-Dimensional IMRT dose audit: An Indonesian multicenter study

Intensity modulated radiation therapy (IMRT) is an advanced technique in radiation therapy delivery. IMRT depends on the accuracy of the multileaf collimator during treatment. Hence, the actual dose distribution can deviate from the treatment planning system's calculation. This study aimed to perform a multicentre planar dosimetry audit of radiotherapy centres in Indonesia, using the structure sets from AAPM TG-119. The gamma index used to evaluate the dose distribution was 3%/3 mm and 3%/2 mm. We observed 100% gamma index passing rates mostly in the 3%/3 mm evaluations. The gamma index passing rates dropped in the 3%/2 mm analysis. Most of the radiotherapy centres participating in this audit satisfied each criterion's tolerance limit of the action level. This study may become a first result for the next multicenter IMRT audit by using a standardized protocol.

Predicting radiotherapy-induced xerostomia in head and neck cancer patients using day-to-day kinetics of radiomics features

Background and purpose

The images acquired during radiotherapy for image-guidance purposes could be used to monitor patient-specific response to irradiation and improve treatment personalisation. We investigated whether the kinetics of radiomics features from daily mega-voltage CT image-guidance scans (MVCT) improve prediction of moderate-to-severe xerostomia compared to dose/volume parameters in radiotherapy of head-and-neck cancer (HNC).

Materials and Methods

All included HNC patients (N = 117) received 30 or more fractions of radiotherapy with daily MVCTs. Radiomics features were calculated on the contra-lateral parotid glands of daily MVCTs. Their variations over time after each complete week of treatment were used to predict moderate-to-severe xerostomia (CTCAEv4.03 grade ≥ 2) at 6, 12 and 24 months post-radiotherapy. After dimensionality reduction, backward/forward selection was used to generate combinations of predictors.Three types of logistic regression model were generated for each follow-up time: 1) a pre-treatment reference model using dose/volume parameters, 2) a combination of dose/volume and radiomics-based predictors, and 3) radiomics-based predictors. The models were internally validated by cross-validation and bootstrapping and their performance evaluated using Area Under the Curve (AUC) on separate training and testing sets.

Results

Moderate-to-severe xerostomia was reported by 46 %, 33 % and 26 % of the patients at 6, 12 and 24 months respectively. The selected models using radiomics-based features extracted at or before mid-treatment outperformed the dose-based models with an AUCtrain/AUCtest of 0.70/0.69, 0.76/0.74, 0.86/0.86 at 6, 12 and 24 months, respectively.

Conclusion

Our results suggest that radiomics features calculated on MVCTs from the first half of the radiotherapy course improve prediction of moderate-to-severe xerostomia in HNC patients compared to a dose-based pre-treatment model.

Radiomics artificial intelligence modelling for prediction of local control for colorectal liver metastases treated with radiotherapy

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Computed tomography imaging contains quantifiable information to characterize colorectal liver metastases.

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Shape, texture, and intensity statistical features quantified the computed tomography liver volume.

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An artificial intelligence model to predict local progression from radiomic features was developed with high accuracy.

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Maximum dosage and textural coarseness of liver volume were features with highest predictive value.

Background and Purpose

Prognostic assessment of local therapies for colorectal liver metastases (CLM) is essential for guiding management in radiation oncology. Computed tomography (CT) contains liver texture information which may be predictive of metastatic environments. To investigate the feasibility of analyzing CT texture, we sought to build an automated model to predict progression-free survival using CT radiomics and artificial intelligence (AI).

Materials and Methods

Liver CT scans and outcomes for N = 97 CLM patients treated with radiotherapy were retrospectively obtained. A survival model was built by extracting 108 radiomic features from liver and tumor CT volumes for a random survival forest (RSF) to predict local progression. Accuracies were measured by concordance indices (C-index) and integrated Brier scores (IBS) with 4-fold cross-validation. This was repeated with different liver segmentations and radiotherapy clinical variables as inputs to the RSF. Predictive features were identified by perturbation importances.

Results

The AI radiomics model achieved a C-index of 0.68 (CI: 0.62–0.74) and IBS below 0.25 and the most predictive radiomic feature was gray tone difference matrix strength (importance: 1.90 CI: 0.93–2.86) and most predictive treatment feature was maximum dose (importance: 3.83, CI: 1.05–6.62). The clinical data only model achieved a similar C-index of 0.62 (CI: 0.56–0.69), suggesting that predictive signals exist in radiomics and clinical data.

Conclusions

The AI model achieved good prediction accuracy for progression-free survival of CLM, providing support that radiomics or clinical data combined with machine learning may aid prognostic assessment and management.

Independent validation of a dysphagia dose response model for the selection of head and neck cancer patients to proton therapy

Background and purpose

The model based approach involves the use of normal tissue complication models for selection of head and neck cancer patients to proton therapy. Our goal was to validate the clinical utility of the related dysphagia model using an independent patient cohort.

Materials and Methods

A dataset of 277 head and neck cancer (pharynx and larynx) patients treated with (chemo)radiotherapy between 2019 and 2021 was acquired. For the evaluation of the model discrimination we used statistical metrics such as the sensitivity, specificity and the area under the receiver operating characteristic curve. After the validation we evaluated if the dysphagia model can be improved using the closed testing procedure, the Brier and the Hosmer-Lemeshow score.

Results

The performance of the original normal tissue complication probability model for dysphagia grade II-IV at 6 months was good (AUC = 0.80). According to the graphical calibration assessment, the original model showed underestimated dysphagia risk predictions. The closed testing procedure indicated that the model had to be updated and selected a revised model with new predictor coefficients as an optimal model. The revised model had also satisfactory discrimination (AUC = 0.83) with improved calibration.

Conclusion

The validation of the normal tissue complication probability model for grade II-IV dysphagia was successful in our independent validation cohort. However, the closed testing procedure indicated that the model should be updated with new coefficients.

Gender-related and geographic trends in interactions between radiotherapy professionals on Twitter

Background and purpose

Twitter presence in academia has been linked to greater research impact which influences career progression. The purpose of this study was to analyse Twitter activity of the radiotherapy community around ESTRO congresses with a focus on gender-related and geographic trends.

Materials and methods

Tweets, re-tweets and replies, here designated as interactions, around the ESTRO congresses held in 2012-2021 were collected. Twitter activity was analysed temporally and, for the period 2016-2021, the geographical span of the ESTRO Twitter network was studied. Tweets and Twitter users collated during the 10 years analysed were ranked based on number of 'likes', 're-tweets' and followers, considered as indicators of leadership/influence. Gender representation was assessed for the top-end percentiles.

Results

Twitter activity around ESTRO congresses was multiplied by 60 in 6 years growing from 150 interactions in 2012 to a peak of 9097 in 2018. In 2020, during the SARS-CoV-2 pandemic, activity dropped by 60 % to reach 2945 interactions and recovered to half the pre-pandemic level in 2021. Europe, North America and Oceania were strongly connected and remained the main contributors. While overall, 58 % of accounts were owned by men, this proportion increased towards top liked/re-tweeted tweets and most-followed profiles to reach up to 84 % in the top-percentiles.

Conclusion

During the SARS-CoV-2 pandemic, Twitter activity around ESTRO congresses substantially decreased. Men were over-represented on the platform and in most popular tweets and influential accounts. Given the increasing importance of social media presence in academia the gender-based biases observed may help in understanding the gender gap in career progression.

Evaluating the Effectiveness of Deep Learning Contouring across Multiple Radiotherapy Centres

Background and purpose

Deep learning contouring (DLC) has the potential to decrease contouring time and variability of organ contours. This work evaluates the effectiveness of DLC for prostate and head and neck across four radiotherapy centres using a commercial system.

Materials and methods

Computed tomography scans of 123 prostate and 310 head and neck patients were evaluated. Besides one head and neck model, generic DLC models were used. Contouring time using centres' existing clinical methods and contour editing time after DLC were compared. Timing was evaluated using paired and non-paired studies. Commercial software or in-house scripts assessed dice similarity coefficient (DSC) and distance to agreement (DTA). One centre assessed head and neck inter-observer variability.

Results

The mean contouring time saved for prostate structures using DLC compared to the existing clinical method was 5.9 ± 3.5 min. The best agreement was shown for the femoral heads (median DSC 0.92 ± 0.03, median DTA 1.5 ± 0.3 mm) and the worst for the rectum (median DSC 0.68 ± 0.04, median DTA 4.6 ± 0.6 mm). The mean contouring time saved for head and neck structures using DLC was 16.2 ± 8.6 min. For one centre there was no DLC time-saving compared to an atlas-based method. DLC contours reduced inter-observer variability compared to manual contours for the brainstem, left parotid gland and left submandibular gland.

Conclusions

Generic prostate and head and neck DLC models can provide time-savings which can be assessed with paired or non-paired studies to integrate with clinical workload. Reducing inter-observer variability potential has been shown.

Experience With Normal Breathhold Planning Scans for Radiosurgery of Moving Targets With Live Tracking

PURPOSE

Utilization of breathhold scans with live tracking has a long track record of good published outcomes for stereotactic body radiation therapy (SBRT) and is recommended by the manufacturer of the Synchrony tracking system. However, the popularity of four-dimensional computed tomography (4DCT) scans challenges the validity of the breathhold scan with live tracking technique. Although this study is not intended to prove the superiority of either method, we demonstrate the feasibility of using the breathhold scans with a phantom test and clinical examples.

METHODS

A 4DCT of a perfect sphere was scanned at 20 breaths per minute and compared to a 4DCT of a small lung tumor in one patient and a 4DCT of a larger renal tumor in another patient, as well as to fiducial matching in a patient with pancreatic cancer. Normal exhale and normal inhale breathhold CT scans were performed for the pancreatic cancer patient, combined with Synchrony tracking on CyberKnife (Sunnyvale, CA: Accuray) for treatment.

RESULTS

The 4DCT scan of the phantom exhibited considerable apparent deformation, which must be entirely due to imaging artifact since the perfect sphere in the phantom is known to be completely rigid. The 4DCT of the lung and renal tumors in patients had similar apparent deformation. Usually in patients, from 4DCT alone, it is difficult to determine how much was due to deformation and how much was due to artifact. Fiducial positions in the final normal exhale and normal inhale breathhold scans for Synchrony matched each other within 1mm for the pancreatic cancer patient.

CONCLUSION

We demonstrated the feasibility of breathhold scans with Synchrony live tracking, as recommended by the manufacturer. More studies will be needed to determine whether this method is better than using a 4DCT.

Adoption of respiratory motion management in radiation therapy

Background and Purpose

A survey on the patterns of practice of respiratory motion management (MM) was distributed to 111 radiation therapy facilities to inform the development of an end-to-end dosimetry audit including respiratory motion.

Materials and methods

The survey (distributed via REDCap) asked facilities to provide information specific to the combinations of MM techniques (breath-hold gating – BHG, internal target volume – ITV, free-breathing gating – FBG, mid-ventilation – MidV, tumour tracking – TT), sites treated (thorax, upper abdomen, lower abdomen), and fractionation regimes (conventional, stereotactic ablative body radiation therapy – SABR) used in their clinic.

Results

The survey was completed by 78% of facilities, with 98% of respondents indicating that they used at least one form of MM. The ITV approach was common to all MM-users, used for thoracic treatments by 89% of respondents, and upper and lower abdominal treatments by 38%. BHG was the next most prevalent (41% of MM users), with applications in upper abdominal and thoracic treatment sites (28% vs 25% respectively), but minimal use in the lower abdomen (9%). FBG and TT were utilised sparingly (17%, 7% respectively), and MidV was not selected at all.

Conclusions

Two distinct treatment workflows (including use of motion limitation, imaging used for motion assessment, dose calculation, and image guidance procedures) were identified for the ITV and BHG MM techniques, to form the basis of the initial audit. Thoracic SABR with the ITV approach was common to nearly all respondents, while upper abdominal SABR using BHG stood out as more technically challenging. Other MM techniques were sparsely used, but may be considered for future audit development.

Clinical implementation and validation of an automated adaptive workflow for proton therapy

Background and purpose

Treatment quality of proton therapy can be monitored by repeat-computed tomography scans (reCTs). However, manual re-delineation of target contours can be time-consuming. To improve the workflow, we implemented an automated reCT evaluation, and assessed if automatic target contour propagation would lead to the same clinical decision for plan adaptation as the manual workflow.

Materials and methods

This study included 79 consecutive patients with a total of 250 reCTs which had been manually evaluated. To assess the feasibility of automated reCT evaluation, we propagated the clinical target volumes (CTVs) deformably from the planning-CT to the reCTs in a commercial treatment planning system. The dose-volume-histogram parameters were extracted for manually re-delineated (CTV_manual) and deformably mapped target contours (CTV_auto). It was compared if CTV_manual and CTV_auto both satisfied/failed the clinical constraints. Duration of the reCT workflows was also recorded.

Results

In 92% (N = 229) of the reCTs correct flagging was obtained. Only 4% (N = 9) of the reCTs presented with false negatives (i.e., at least one clinical constraint failed for CTV_manual, but all constraints were satisfied for CTV_auto), while 5% (N = 12) of the reCTs led to a false positive. Only for one false negative reCT a plan adaption was made in clinical practice, i.e., only one adaptation would have been missed, suggesting that automated reCT evaluation was possible. Clinical introduction hereof led to a time reduction of 49 h (from 65 to 16 h).

Conclusion

Deformable target contour propagation was clinically acceptable. A script-based automatic reCT evaluation workflow has been introduced in routine clinical practice.

What is the optimal input information for deep learning-based pre-treatment error identification in radiotherapy?

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The choice of dose comparison method impacts deep learning error identification accuracy most.

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Simple dose comparison methods are more beneficial than gamma analysis and alternative methods.

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Mean/standard deviation normalization and high image resolution improve error identification.

Background and purpose

Deep learning (DL) provides high sensitivity for detecting and identifying errors in pre-treatment radiotherapy quality assurance (QA). This work’s objective was to systematically evaluate the impact of different dose comparison and image preprocessing methods on DL model performance for error identification in pre-treatment QA.

Materials and methods

For 53 volumetric modulated arc therapy (VMAT) and 69 stereotactic body radiotherapy (SBRT) treatment plans of lung cancer patients, mechanical errors were simulated (MLC leaf positions, monitor unit scaling, collimator rotation). Two classification levels were assessed: error type (Level 1) and error magnitude (Level 2). Portal dose images with and without errors were compared using standard (gamma analysis), simple (absolute/relative dose difference, ratio) and alternative (distance-to-agreement, structural similarity index, gradient) dose comparison methods. For preprocessing, different normalization methods (min/max and mean/standard deviation) and image resolutions (32 × 32, 64 × 64 and 128 × 128) were evaluated. All possible combinations of classification level, dose comparison, normalization method and image size resulted in 144 input datasets for DL networks for error identification.

Results

Average accuracy was highest for simple dose comparison methods (Level 1: 97.7%, Level 2: 78.1%) while alternative methods scored lowest (Level 1: 91.6%, Level 2: 71.2%). Mean/stdev normalization particularly improved Level 2 classification. Higher image resolution improved error identification, although for SBRT lower image resolution was also sufficient.

Conclusions

The choice of dose comparison method has the largest impact on error identification for pre-treatment QA using DL, compared to image preprocessing. Model performance can improve by using simple dose comparison methods, mean/stdev normalization and high image resolution.

DOSIMETRIC VERIFICATION OF INTENSITY MODULATED RADIOTHERAPY (IMRT) TREATMENT PLANS FOR PROSTATE CANCER PATIENTS

Intensity modulated radiotherapy (IMRT) has become widely used as a standard radiation therapy technique for the treatment of localized prostate cancer. The transition from conformal radiotherapy (3D CRT) to a more complex IMRT technique triggered the need for more thorough verification of the accuracy in the dose delivery. In this work we present the clinical workflow and the results of patient specific quality assurance (PSQA) procedures for 40 prostate cancer patients who have been treated with step and shot IMRT ever since its implementation in our routine clinical practice. PSQA procedures include dosimetric verification of each treatment plan with dedicated rotational phantom and high-resolution matrix detector system Octavius 4D (PTW Freiburg) that allows three-dimensional comparison of the calculated and delivered radiation dose distribution. Our results proved the compliance with the universal tolerance limits recommended for those procedures (1), assuring the safety of the treatment and providing the possibility for the adoption of more stringent constraints in the future.

Feasibility, Method and Early Outcome of Image-Guided Volumetric Modulated Arc Radiosurgery Followed by Resection for AJCC Stage IIA–IIIB High-Risk Large Intraocular Melanoma

Simple Summary

The aim of this trial was to define one optimal contemporary treatment procedure for large intraocular melanoma. Radiosurgery is a highly effective treatment in cancer. In this trial, all consecutive patients with large intraocular melanoma treated with multimodality treatment, comprising 4D image-guided volumetric modulated arc radiosurgery procedure followed by resection, were evaluated. In the short-term follow-up there was no clinical toxicity due to external beam radiation therapy, and no local tumor recurrence. In 98% of the cases, the eye bulb could be maintained with partial residual visual acuity in the mean follow-up of 18 months. The outcome estimates one optimal treatment procedure for high-risk, large intraocular melanoma, with excellent results in the first follow-up.

Abstract

The main objective of this prospective observational study was the characterization of the feasibility and early outcome of image-guided (IG) volumetric modulated arc (VMAT) radiosurgery (SRS) followed by resection for patients with large intraocular melanoma. Our study included consecutive patients with unfavorable-risk melanoma, enrolled in an ophthalmic oncology center. IG-VMAT-SRS was applied by high-resolution 4D image guidance and monitoring. Current stereotactic technique parameters were evaluated for comparison. Side effects and eye function, based on a 5-point CTC assessment score, were quantified. In patients with tumors located more than 0.7–1 mm apart from the optic nerve, partial to complete volume-sparing of the optic nerve head could be achieved. In 95.5% of this subgroup, the vitality of the optic nerve and vision could be preserved by the multimodality-treatment approach (mean follow-up: 18 months (7.5–36 months)). The advanced technology of stereotactic radiotherapy demonstrated the achievability of steep dose gradients around the high-dose volume, with 4D-IG-VMAT dose application. These results enforce IG-VMAT-SRS followed by resection as one of the major therapeutic options for patients with large intraocular melanoma. The combination of 4D-IG high-precision SRS and resection provides an effective treatment for large intraocular melanoma, with few side effects, and enables an eye bulb and even vision preserving modus operandi.

Functional lung imaging in thoracic tumor radiotherapy: Application and progress

Radiotherapy plays an irreplaceable and unique role in treating thoracic tumors, but the occurrence of radiation-induced lung injury has limited the increase in tumor target doses and has influenced patients’ quality of life. However, the introduction of functional lung imaging has been incorporating functional lungs into radiotherapy planning. The design of the functional lung protection plan, while meeting the target dose requirements and dose limitations of the organs at risk (OARs), minimizes the radiation dose to the functional lung, thus reducing the occurrence of radiation-induced lung injury. In this manuscript, we mainly reviewed the lung ventilation or/and perfusion functional imaging modalities, application, and progress, as well as the results based on the functional lung protection planning in thoracic tumors. In addition, we also discussed the problems that should be explored and further studied in the practical application based on functional lung radiotherapy planning.

Assessment of intrafractional prostate motion and its dosimetric impact in MRI-guided online adaptive radiotherapy with gating

PURPOSE

This study aimed to evaluate the intrafractional prostate motion captured during gated magnetic resonance imaging (MRI)-guided online adaptive radiotherapy for prostate cancer and analyze its impact on the delivered dose as well as the effect of gating.

METHODS

Sagittal 2D cine-MRI scans were acquired at 4 Hz during treatment at a ViewRay MRIdian (ViewRay Inc., Oakwood Village, OH, USA) MR linac. Prostate shifts in anterior-posterior (AP) and superior-inferior (SI) directions were extracted separately. Using the static dose cloud approximation, the planned fractional dose was shifted according to the 2D gated motion (residual motion in gating window) to estimate the delivered dose by superimposing and averaging the shifted dose volumes. The dose of a hypothetical non-gated delivery was reconstructed similarly using the non-gated motion. For the clinical target volume (CTV), rectum, and bladder, dose-volume histogram parameters of the planned and reconstructed doses were compared.

RESULTS

In total, 174 fractions (15.7 h of cine-MRI) from 10 patients were evaluated. The average (±1 σ) non-gated prostate motion was 0.6 ± 1.0 mm in the AP and 0.0 ± 0.6 mm in the SI direction with respect to the centroid position of the gating boundary. 95% of the shifts were within [-3.5, 2.7] mm in the AP and [-2.9, 3.2] mm in the SI direction. For the gated treatment and averaged over all fractions, CTV D_98% decreased by less than 2% for all patients. The rectum and the bladder D_2% increased by less than 3% and 0.5%, respectively. Doses reconstructed for gated and non-gated delivery were similar for most fractions.

CONCLUSION

A pipeline for extraction of prostate motion during gated MRI-guided radiotherapy based on 2D cine-MRI was implemented. The 2D motion data enabled an approximate estimation of the delivered dose. For the majority of fractions, the benefit of gating was negligible, and clinical dosimetric constraints were met, indicating safety of the currently adopted gated MRI-guided treatment workflow.

Dosimetric impact of intrafraction motion under abdominal compression during MR-guided SBRT for (Peri-) pancreatic tumors

Objective. Intrafraction motion is a major concern for the safety and effectiveness of high dose stereotactic body radiotherapy (SBRT) in the upper abdomen. In this study, the impact of the intrafraction motion on the delivered dose was assessed in a patient group that underwent MR-guided radiotherapy for upper abdominal malignancies with an abdominal corset. Approach. Fast online 2D cine MRI was used to extract tumor motion during beam-on time. These tumor motion profiles were combined with linac log files to reconstruct the delivered dose in 89 fractions of MR-guided SBRT in twenty patients. Aside the measured tumor motion, motion profiles were also simulated for a wide range of respiratory amplitudes and drifts, and their subsequent dosimetric impact was calculated in every fraction. Main results. The average (SD) D 99% of the gross tumor volume (GTV), relative to the planned D 99%, was 0.98 (0.03). The average (SD) relative D 0.5cc of the duodenum, small bowel and stomach was 0.99 (0.03), 1.00 (0.03), and 0.97 (0.05), respectively. No correlation of respiratory amplitude with dosimetric impact was observed. Fractions with larger baseline drifts generally led to a larger uncertainty of dosimetric impact on the GTV and organs at risk (OAR). The simulations yielded that the delivered dose is highly dependent on the direction of on baseline drift. Especially in anatomies where the OARs are closely abutting the GTV, even modest LR or AP drifts can lead to substantial deviations from the planned dose. Significance. The vast majority of the fractions was only modestly impacted by intrafraction motion, increasing our confidence that MR-guided SBRT with abdominal compression can be safely executed for patients with abdominal tumors, without the use of gating or tracking strategies.

The first reported case of a patient with pancreatic cancer treated with cone beam computed tomography-guided stereotactic adaptive radiotherapy (CT-STAR)

BACKGROUND

Online adaptive stereotactic radiotherapy allows for improved target and organ at risk (OAR) delineation and inter-fraction motion management via daily adaptive planning. The use of adaptive SBRT for the treatment of pancreatic cancer (performed until now using only MRI or CT on rails-guided adaptive radiotherapy), has yielded promising outcomes. Herein we describe the first reported case of cone beam CT-guided stereotactic adaptive radiotherapy (CT-STAR) for the treatment of pancreatic cancer.

CASE PRESENTATION

A 61-year-old female with metastatic pancreatic cancer presented for durable palliation of a symptomatic primary pancreatic mass. She was prescribed 35 Gy/5 fractions utilizing CT-STAR. The patient was simulated utilizing an end-exhale CT with intravenous and oral bowel contrast. Both initial as well as daily adapted plans were created adhering to a strict isotoxicity approach in which coverage was sacrificed to meet critical luminal gastrointestinal OAR hard constraints. Kilovoltage cone beam CTs were acquired on each day of treatment and the radiation oncologist edited OAR contours to reflect the patient's anatomy-of-the-day. The initial and adapted plan were compared using dose volume histogram objectives, and the superior plan was delivered. Use of the initial treatment plan would have resulted in nine critical OAR hard constraint violations. The adapted plans achieved hard constraints in all five fractions for all four critical luminal gastrointestinal structures.

CONCLUSIONS

We report the successful treatment of a patient with pancreatic cancer treated with CT-STAR. Prior to this treatment, the delivery of ablative adaptive radiotherapy for pancreatic cancer was limited to clinics with MR-guided and CT-on-rails adaptive SBRT technology and workflows. CT-STAR is a promising modality with which to deliver stereotactic adaptive radiotherapy for pancreatic cancer.

OpenKBP-Opt: an international and reproducible evaluation of 76 knowledge-based planning pipelines

Objective.To establish an open framework for developing plan optimization models for knowledge-based planning (KBP).Approach.Our framework includes radiotherapy treatment data (i.e. reference plans) for 100 patients with head-and-neck cancer who were treated with intensity-modulated radiotherapy. That data also includes high-quality dose predictions from 19 KBP models that were developed by different research groups using out-of-sample data during the OpenKBP Grand Challenge. The dose predictions were input to four fluence-based dose mimicking models to form 76 unique KBP pipelines that generated 7600 plans (76 pipelines × 100 patients). The predictions and KBP-generated plans were compared to the reference plans via: the dose score, which is the average mean absolute voxel-by-voxel difference in dose; the deviation in dose-volume histogram (DVH) points; and the frequency of clinical planning criteria satisfaction. We also performed a theoretical investigation to justify our dose mimicking models.Main results.The range in rank order correlation of the dose score between predictions and their KBP pipelines was 0.50-0.62, which indicates that the quality of the predictions was generally positively correlated with the quality of the plans. Additionally, compared to the input predictions, the KBP-generated plans performed significantly better (P< 0.05; one-sided Wilcoxon test) on 18 of 23 DVH points. Similarly, each optimization model generated plans that satisfied a higher percentage of criteria than the reference plans, which satisfied 3.5% more criteria than the set of all dose predictions. Lastly, our theoretical investigation demonstrated that the dose mimicking models generated plans that are also optimal for an inverse planning model.Significance.This was the largest international effort to date for evaluating the combination of KBP prediction and optimization models. We found that the best performing models significantly outperformed the reference dose and dose predictions. In the interest of reproducibility, our data and code is freely available.

Application of Hydrogels as Carrier in Tumor Therapy: A Review

Cancer is one of the most intractable diseases in the world because of its high recurrence rate, high metastasis rate and high lethality rate. Traditional chemotherapy, radiotherapy and surgery have unsatisfactory therapeutic effects and cause many severe side effects at the same time. Hydrogel is a new type of biomaterial with the advantages of good biocompatibility and easy degradation, which can be used as a carrier of functional nanomaterials for tumor therapy. Herein, we represent the progress of hydrogels with different skeletons and their application as carrier in tumor treatment. The hydrogels are listed as polyethylene glycol-based hydrogels, chitosan-based hydrogels, peptide-based hydrogels, hyaluronic acid-based hydrogels, steroid-based hydrogels and other hydrogels by skeletons, and their properties, modifications and toxicities were introduced. Some representative applications of combined hydrogels with nanomaterial for chemotherapy, photodynamic therapy, photothermal therapy, sonodynamic therapy, chemodynamic therapy and synergistic therapy are highlighted.

A comprehensive quality assurance procedure for 4D CT commissioning and periodic QA

PURPOSE

The 4D computed tomography (CT) simulation is an essential procedure for tumors exhibiting breathing-induced motion. However, to date there are no established guidelines to assess the characteristics of existing systems and to describe meaningful performance. We propose a commissioning quality assurance (QA) protocol consisting of measurements and acquisitions that assess the mechanical and computational operation for 4D CT with both phase and amplitude-based reconstructions, for regular and irregular respiratory patterns.

METHODS

The 4D CT scans of a QUASAR motion phantom were acquired for both regular and irregular breathing patterns. The hardware consisted of the Canon Aquilion Exceed LB CT scanner used in conjunction with the Anzai laser motion monitoring system. The nominal machine performance and reconstruction were demonstrated with measurements using regular breathing patterns. For irregular breathing patterns the performance was quantified through the analysis of the target motion in the superior and inferior directions, and the volume of the internal target volume (ITV). Acquisitions were performed using multiple pitches and the reconstructions were performed using both phase and amplitude-based binning.

RESULTS

The target was accurately captured during regular breathing. For the irregular breathing, the measured ITV exceeded the nominal ITV parameters in all scenarios, but all deviations were less than the reconstructed slice thickness. The mismatch between the nominal pitch and the actual breathing rate did not affect markedly the size of the ITV. Phase and normalized amplitude binning performed similarly.

CONCLUSIONS

We demonstrated a framework for measuring and quantifying the initial performance of 4D CT simulation scans that can also be applied during periodic QAs. The regular breathing provided confidence that the hardware and the software between the systems performs adequately. The irregular breathing data suggest that the system may be expected to capture in excess the target motion and geometry, but the deviation is expected to be within the slice thickness.

Development of a 3D CNN-based AI Model for Automated Segmentation of the Prostatic Urethra

RATIONALE AND OBJECTIVE

The combined use of prostate cancer radiotherapy and MRI planning is increasingly being used in the treatment of clinically significant prostate cancers. The radiotherapy dosage quantity is limited by toxicity in organs with de-novo genitourinary toxicity occurrence remaining unperturbed. Estimation of the urethral radiation dose via anatomical contouring may improve our understanding of genitourinary toxicity and its related symptoms. Yet, urethral delineation remains an expert-dependent and time-consuming procedure. In this study, we aim to develop a fully automated segmentation tool for the prostatic urethra.

MATERIALS AND METHODS

This study incorporated 939 patients' T2-weighted MRI scans (train/validation/test/excluded: 657/141/140/1 patients), including in-house and public PROSTATE-x datasets, and their corresponding ground truth urethral contours from an expert genitourinary radiologist. The AI model was developed using MONAI framework and was based on a 3D-UNet. AI model performance was determined by Dice score (volume-based) and the Centerline Distance (CLD) between the prediction and ground truth centers (slice-based). All predictions were compared to ground truth in a systematic failure analysis to elucidate the model's strengths and weaknesses. The Wilcoxon-rank sum test was used for pair-wise comparison of group differences.

RESULTS

The overall organ-adjusted Dice score for this model was 0.61 and overall CLD was 2.56 mm. When comparing prostates with symmetrical (n = 117) and asymmetrical (n = 23) benign prostate hyperplasia (BPH), the AI model performed better on symmetrical prostates compared to asymmetrical in both Dice score (0.64 vs. 0.51 respectively, p < 0.05) and mean CLD (2.3 mm vs. 3.8 mm respectively, p < 0.05). When calculating location-specific performance, the performance was highest at the apex and lowest at the base location of the prostate for Dice and CLD. Dice location dependence: symmetrical (Apex, Mid, Base: 0.69 vs. 0.67 vs. 0.54 respectively, p < 0.05) and asymmetrical (Apex, Mid, Base: 0.68 vs. 0.52 vs. 0.39 respectively, p < 0.05). CLD location dependence: symmetrical (Apex, Mid, Base: 1.43 mm vs. 2.15 mm vs. 3.28 mm, p < 0.05) and asymmetrical (Apex, Mid, Base: 1.83 mm vs. 3.1 mm vs. 6.24 mm, p < 0.05).

CONCLUSION

We developed a fully automated prostatic urethra segmentation AI tool yielding its best performance in prostate glands with symmetric BPH features. This system can potentially be used to assist treatment planning in patients who can undergo whole gland radiation therapy or ablative focal therapy.

In vivo dosimetry in pelvic brachytherapy

ADVANCES IN KNOWLEDGE

This paper describes the potential role for in vivo dosimetry in the reduction of uncertainties in pelvic brachytherapy, the pertinent factors for consideration in clinical practice, and the future potential for in vivo dosimetry in the personalisation of brachytherapy.

Impact of intrafraction changes in delivered dose of the day for prostate cancer patients treated with stereotactic body radiotherapy via MR-Linac

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Beam on MR acquisition on the MR-Linac can be used to compute DDOTD.

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Intrafraction motion via volumetric variability of OARs can impact dosimetry.

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Computation of the DDOTD may help inform prospective fractions for SBRT prostate.

Purpose

The purpose of this study is to evaluate the impact of intrafraction pelvic motion by comparing the adapted plan dose (APD) and the computed delivered dose of the day (DDOTD) for patients with prostate cancer (PCa) treated with SBRT on the MR-Linac.

Methods

Twenty patients with PCa treated with MR-guided adaptive SBRT were included. A 9-field IMRT distribution was adapted based on the anatomy of the day to deliver a total prescription dose of 3000 cGy in 5 fractions to the prostate plus a 5 mm isotropic margin. Prostate, bladder, and rectum were re-contoured on the MR-image acquired during treatment delivery (MR_BO). DDOTD was computed by propagating the dose from the daily adapted plan generated during treatment onto the MR_BO.

Results

Target coverage was met for all fractions, however, computed DDOTD was significantly less than the APD (p < 0.05). During an average treatment of 53 min, mean bladder volume increased by 116%, which led to a significant decrease in the DDOTD bladder D40% (p < 0.001). However, DDOTD to bladder 5 cc was significantly higher (p < 0.001) than APD. Rectum intrafraction changes were observed based on a volume change of −20% to 83% and presence of significant dose changes from APD to DDOTD for rectum D20% (p < 0.05) and D1cc (p < 0.0001).

Conclusions

Intrafraction motion observed during prostate SBRT treatment on the MR-Linac have dosimetric impacts on both the target and organs at risk. Post-treatment computation using DDOTD may inform adaptation beyond anatomic changes in subsequent treatment fractions to best capitalize on MR-Linac technology and widen the therapeutic index of SBRT for PCa.

News in magnetic resonance imaging use for radiation oncology

The purpose of this article is to give a summary of the progress of magnetic resonance imaging (MRI) in radiotherapy. MRI is an important imaging modality for treatment planning in radiotherapy. However, the registration step with the simulation scanner can be a source of errors, motivating the implementation of all-MRI simulation methods and new accelerators coupled with on-board MRI. First, practical MRI imaging for radiotherapy is detailed, but also the importance of a coherent imaging workflow incorporating all imaging modalities. Second, future evolutions and research domains such as quantitative imaging biomarkers, MRI-only pseudo computed tomography and radiomics are discussed. Finally, the application of MRI during radiotherapy treatment is reviewed: the use of MR-linear accelerators. MRI is increasingly integrated into radiotherapy. Advances in diagnostic imaging can thus benefit radiotherapy, but specific radiotherapy constraints lead to additional challenges and require close collaboration between radiologists, radiation oncologists, technologists and physicists. The integration of quantitative imaging biomarkers in the radiotherapy process will result in mutual benefit for diagnostic imaging and radiotherapy. MRI-guided radiotherapy has already been used for several years in clinical routine. Abdominopelvic neoplasias (pancreas, liver, prostate) are the preferred locations for treatment because of their favourable contrast in MRI, their movement during irradiation and their proximity to organs at risk of radiation exposure, making the tracking and daily adaptation of the plan essential. MRI has emerged as an increasingly necessary imaging modality for radiotherapy planning. Inclusion of patients in clinical trials evaluating new MRI-guided radiotherapy techniques and associated quantitative imaging biomarkers will be necessary to assess the benefits.

[What do we need to deliver "online" adapted radiotherapy treatment plans?]

During the joint SFRO/SFPM session of the 2019 congress, a state of the art of adaptive radiotherapy announced a strong impact in our clinical practice, in particular with the availability of treatment devices coupled to an MRI system. Three years later, it seems relevant to take stock of adaptive radiotherapy in practice, and especially the "online" strategy because it is indeed more and more accessible with recent hardware and software developments, such as coupled accelerators to a three-dimensional imaging device and algorithms based on artificial intelligence. However, the deployment of this promising strategy is complex because it contracts the usual time scale and upsets the usual organizations. So what do we need to deliver adapted treatment plans with an "online" strategy?

Application of Artificial Intelligence Methods for Imaging of Spinal Metastasis

Spinal metastasis is the most common malignant disease of the spine. Recently, major advances in machine learning and artificial intelligence technology have led to their increased use in oncological imaging. The purpose of this study is to review and summarise the present evidence for artificial intelligence applications in the detection, classification and management of spinal metastasis, along with their potential integration into clinical practice. A systematic, detailed search of the main electronic medical databases was undertaken in concordance with the PRISMA guidelines. A total of 30 articles were retrieved from the database and reviewed. Key findings of current AI applications were compiled and summarised. The main clinical applications of AI techniques include image processing, diagnosis, decision support, treatment assistance and prognostic outcomes. In the realm of spinal oncology, artificial intelligence technologies have achieved relatively good performance and hold immense potential to aid clinicians, including enhancing work efficiency and reducing adverse events. Further research is required to validate the clinical performance of the AI tools and facilitate their integration into routine clinical practice.

History of Technological Advancements towards MR-Linac: The Future of Image-Guided Radiotherapy

Image-guided radiotherapy (IGRT) enables optimal tumor targeting and sparing of organs-at-risk, which ultimately results in improved outcomes for patients. Magnetic resonance imaging (MRI) revolutionized diagnostic imaging with its superior soft tissue contrast, high spatiotemporal resolution, and freedom from ionizing radiation exposure. Over the past few years there has been burgeoning interest in MR-guided radiotherapy (MRgRT) to overcome current challenges in X-ray-based IGRT, including but not limited to, suboptimal soft tissue contrast, lack of efficient daily adaptation, and incremental exposure to ionizing radiation. In this review, we present an overview of the technologic advancements in IGRT that led to MRI-linear accelerator (MRL) integration. Our report is organized in three parts: (1) a historical timeline tracing the origins of radiotherapy and evolution of IGRT, (2) currently available MRL technology, and (3) future directions and aspirations for MRL applications.

Evaluation of auto-segmentation for EBRT planning structures using deep learning-based workflow on cervical cancer

Deep learning (DL) based approach aims to construct a full workflow solution for cervical cancer with external beam radiation therapy (EBRT) and brachytherapy (BT). The purpose of this study was to evaluate the accuracy of EBRT planning structures derived from DL based auto-segmentation compared with standard manual delineation. Auto-segmentation model based on convolutional neural networks (CNN) was developed to delineate clinical target volumes (CTVs) and organs at risk (OARs) in cervical cancer radiotherapy. A total of 300 retrospective patients from multiple cancer centers were used to train and validate the model, and 75 independent cases were selected as testing data. The accuracy of auto-segmented contours were evaluated using geometric and dosimetric metrics including dice similarity coefficient (DSC), 95% hausdorff distance (95%HD), jaccard coefficient (JC) and dose-volume index (DVI). The correlation between geometric metrics and dosimetric difference was performed by Spearman’s correlation analysis. The right and left kidney, bladder, right and left femoral head showed superior geometric accuracy (DSC: 0.88–0.93; 95%HD: 1.03 mm–2.96 mm; JC: 0.78–0.88), and the Bland–Altman test obtained dose agreement for these contours (P > 0.05) between manual and DL based methods. Wilcoxon’s signed-rank test indicated significant dosimetric differences in CTV, spinal cord and pelvic bone (P < 0.001). A strong correlation between the mean dose of pelvic bone and its 95%HD (R = 0.843, P < 0.001) was found in Spearman’s correlation analysis, and the remaining structures showed weak link between dosimetric difference and all of geometric metrics. Our auto-segmentation achieved a satisfied agreement for most EBRT planning structures, although the clinical acceptance of CTV was a concern. DL based auto-segmentation was an essential component in cervical cancer workflow which would generate the accurate contouring.

Advances and potential of optical surface imaging in radiotherapy

This article reviews the recent advancements and future potential of optical surface imaging (OSI) in clinical applications as a four-dimensional (4D) imaging modality for surface-guided radiotherapy (SGRT), including OSI systems, clinical SGRT applications, and OSI-based clinical research. The OSI is a non-ionizing radiation imaging modality, offering real-time 3D surface imaging with a large field of view (FOV), suitable for in-room interactive patient setup, and real-time motion monitoring at any couch rotation during radiotherapy. So far, most clinical SGRT applications have focused on treating superficial breast cancer or deep-seated brain cancer in rigid anatomy, because the skin surface can serve as tumor surrogates in these two clinical scenarios, and the procedures for breast treatments in free-breathing (FB) or at deep-inspiration breath-hold (DIBH), and for cranial stereotactic radiosurgery (SRS) and radiotherapy (SRT) are well developed. When using the skin surface as a body-position surrogate, SGRT promises to replace the traditional tattoo/laser-based setup. However, this requires new SGRT procedures for all anatomical sites and new workflows from treatment simulation to delivery. SGRT studies in other anatomical sites have shown slightly higher accuracy and better performance than a tattoo/laser-based setup. In addition, radiographical image-guided radiotherapy (IGRT) is still necessary, especially for stereotactic body radiotherapy (SBRT). To go beyond the external body surface and infer an internal tumor motion, recent studies have shown the clinical potential of OSI-based spirometry to measure dynamic tidal volume as a tumor motion surrogate, and Cherenkov surface imaging to guide and assess treatment delivery. As OSI provides complete datasets of body position, deformation, and motion, it offers an opportunity to replace fiducial-based optical tracking systems. After all, SGRT has great potential for further clinical applications. In this review, OSI technology, applications, and potential are discussed since its first introduction to radiotherapy in 2005, including technical characterization, different commercial systems, and major clinical applications, including conventional SGRT on top of tattoo/laser-based alignment and new SGRT techniques attempting to replace tattoo/laser-based setup. The clinical research for OSI-based tumor tracking is reviewed, including OSI-based spirometry and OSI-guided tumor tracking models. Ongoing clinical research has created more SGRT opportunities for clinical applications beyond the current scope.