MR guidance in radiotherapy

Prospective evaluation of patient-reported anxiety and experiences with adaptive radiation therapy on an MR-linac

Purpose

An integrated magnetic resonance scanner and linear accelerator (MR-linac) was implemented with daily online adaptive radiation therapy (ART). This study evaluated patient-reported experiences with their overall hospital care as well as treatment in the MR-linac environment.

Methods

Patients pre-screened for MR eligibility and claustrophobia were referred to simulation on a 1.5 T MR-linac. Patient-reported experience measures were captured using two validated surveys. The 15-item MR-anxiety questionnaire (MR-AQ) was administered immediately after the first treatment to rate MR-related anxiety and relaxation. The 40-item satisfaction with cancer care questionnaire rating doctors, radiation therapists, the services and care organization and their outpatient experience was administered immediately after the last treatment using five-point Likert responses. Results were analyzed using descriptive statistics.

Results

205 patients were included in this analysis. Multiple sites were treated across the pelvis and abdomen with a median treatment time per fraction of 46 and 66 min respectively. Patients rated MR-related anxiety as "not at all" (87%), "somewhat" (11%), "moderately" (1%) and "very much so" (1%). Positive satisfaction responses ranged from 78 to 100% (median 93%) across all items. All radiation therapist-specific items were rated positively as 96-100%. The five lowest rated items (range 78-85%) were related to general provision of information, coordination, and communication. Overall hospital care was rated positively at 99%.

Conclusion

In this large, single-institution prospective cohort, all patients had low MR-related anxiety and completed treatment as planned despite lengthy ART treatments with the MR-linac. Patients overall were highly satisfied with their cancer care involving ART using an MR-linac.

MRI-Guided Radiation Therapy-An Emerging and Disruptive Process of Care: Healthcare Economic and Policy Considerations

MRI-guided radiation therapy (MRgRT) is an emerging, innovative technology that provides opportunities to transform and improve the current clinical care process in radiation oncology. As with many new technologies in radiation oncology, careful evaluation from a healthcare economic and policy perspective is required for its successful implementation. In this review article, we describe the current evidence surrounding MRgRT, framing it within the context of value within the healthcare system. Additionally, we highlight areas in which MRgRT may disrupt the current process of care, and discuss the evidence thresholds and timeline required for the widespread adoption of this promising technology.

Synthetic computed tomography based dose calculation in prostate cancer patients with hip prostheses for magnetic resonance imaging-only radiotherapy

Background and purpose

Metallic hip prostheses cause substantial artefacts in both computed tomography (CT) and magnetic resonance (MR) images used in radiotherapy treatment planning (RTP) for prostate cancer patients. The aim of this study was to evaluate the dose calculation accuracy of a synthetic CT (sCT) generation workflow and the improvement in implant visibility using metal artefact reduction sequences.

Materials and methods

The study included 23 patients with prostate cancer who had hip prostheses, of which 10 patients had bilateral hip implants. An in-house protocol was applied to create sCT images for dose calculation comparison. The study compared prostheses volumes and resulting avoidance sectors against planning target volume (PTV) dose uniformity and organs at risk (OAR) sparing.

Results

Median PTV dose difference between sCT and CT-based dose calculation among all patients was 0.1 % (-0.4 to 0.4%) (median(range)). Bladder and rectum differences (V_50Gy) were 0.2 % (-0.3 to 1.1%) and 0.1 % (-0.9 to 0.5%). The median 3D local gamma pass rate for partial arc cases using a Dixon MR sequence was Γ_20%^2mm/2% = 99.9%. For the bilateral full arc cases, using a metal artefact reconstruction sequence, the pass rate was Γ_20%^2mm/2% = 99.0%.

Conclusions

An in-house protocol for generating sCT images for dose calculation provided clinically feasible dose calculation accuracy for prostate cancer patients with hip implants. PTV median dose difference for uni- and bilateral patients with avoidance sectors remained <0.4%. The Outphase images enhanced implant visibility resulting in smaller avoidance sectors, better OAR sparing, and improved PTV uniformity.

Cone beam computed tomography image guidance within a magnetic resonance imaging-only planning workflow

Background and purpose

Magnetic Resonance Imaging (MRI)-only planning workflows offer many advantages but raises challenges regarding image guidance. The study aimed to assess the viability of MRI to Cone Beam Computed Tomography (CBCT) based image guidance for MRI-only planning treatment workflows.

Materials and methods

An MRI matching training package was developed. Ten radiation therapists, with a range of clinical image guidance experience and experience with MRI, completed the training package prior to matching assessment. The matching assessment was performed on four match regions: prostate gold seed, prostate soft tissue, rectum/anal canal and gynaecological. Each match region consisted of five patients, with three CBCTs per patient, resulting in fifteen CBCTs for each match region. The ten radiation therapists performed the CBCT image matching to CT and to MRI for all regions and recorded the match values.

Results

The median inter-observer variation for MRI-CBCT matching and CT-CBCT matching for all regions were within 2 mm and 1 degree. There was no statistically significant association in the inter-observer variation in mean match values and radiation therapist image guidance experience levels. There was no statistically significant association in inter-observer variation in mean match values for MRI experience levels for prostate soft tissue and gynaecological match regions, while there was a statistically significant difference for prostate gold seed and rectum match regions.

Conclusion

The results of this study support the concept that with focussed training, an MRI to CBCT image guidance approach can be successfully implemented in a clinical planning workflow.

A pilot study of MRI radiomics for high-risk prostate cancer stratification in 1.5 T MR-guided radiotherapy

PURPOSE

To investigate the potential value of MRI radiomics obtained from a 1.5 T MRI-guided linear accelerator (MR-LINAC) for D'Amico high-risk prostate cancer (PC) classification in MR-guided radiotherapy (MRgRT).

METHODS

One hundred seventy-six consecutive PC patients underwent 1.5 T MRgRT treatment were retrospectively enrolled. Each patient received one or two pretreatment T₂ -weighted MRI scans on a 1.5 T MR-LINAC. The endpoint was to differentiate high-risk from low/intermediate-risk PC based on D'Amico criteria using MRI-radiomics. Totally 1023 features were extracted from clinical target volume (CTV) and planning target volume (PTV). Intraclass correlation coefficient of scan-rescan repeatability, feature correlation, and recursive feature elimination were used for feature dimension reduction. Least absolute shrinkage and selection operator regression was employed for model construction. Receiver operating characteristic area under the curve (AUC) analysis was used for model performance assessment in both training and testing data.

RESULTS

One hundred and eleven patients fulfilled all criteria were finally included: 76 for training and 35 for testing. The constructed MRI-radiomics models extracted from CTV and PTV achieved the AUC of 0.812 and 0.867 in the training data, without significant difference (P = 0.083). The model performances remained in the testing. The sensitivity, specificity, and accuracy were 85.71%, 64.29%, and 77.14% for the PTV-based model; and 71.43%, 71.43%, and 71.43% for the CTV-based model. The corresponding AUCs were 0.718 and 0.750 (P = 0.091) for CTV- and PTV-based models.

CONCLUSION

MRI-radiomics obtained from a 1.5 T MR-LINAC showed promising results in D'Amico high-risk PC stratification, potentially helpful for the future PC MRgRT. Prospective studies with larger sample sizes and external validation are warranted for further verification.

Determining the reliable feature change in longitudinal radiomics studies: A methodological approach using the reliable change index

PURPOSE

Determination of reliable change of radiomics feature over time is essential and vital in delta-radiomics, but has not yet been rigorously examined. This study attempts to propose a methodological approach using reliable change index (RCI), a statistical metric to determine the reliability of quantitative biomarker changes by accounting for the baseline measurement standard error, in delta-radiomics. The use of RCI was demonstrated with the MRI data acquired from a group of prostate cancer (PCa) patients treated by 1.5 T MRI-guided radiotherapy (MRgRT).

METHODS

Fifty consecutive PCa patients who underwent five-fractionated MRgRT were retrospectively included, and 1023 radiomics features were extracted from the clinical target volume (CTV) and planning target volume (PTV). The two MRI datasets acquired at the first fraction (MRI11 and MRI21) were used to calculate the baseline feature reliability against image acquisition using intraclass correlation coefficient (ICC). The RCI was constructed based on the baseline feature measurement standard deviation, ICC, and feature value differences at two time points between the fifth (MRI51) and the first fraction MRI (MRI11). The reliable change of features was determined in each patient only if the calculated RCI was over 1.96 or smaller than -1.96. The feature changes between MRI51 and MRI11 were correlated to two patient-reported quality-of-life clinical endpoints of urinary domain summary score (UDSS) and bowel domain summary score (BDSS) in 35 patients using the Spearman correlation test. Only the significant correlations between a feature that was reliably changed in ≥7 patients (20%) by RCI and an endpoint were considered as true significant correlations.

RESULTS

The 352 (34.4%) and 386 (37.7%) features among all 1023 features were determined by RCI to be reliably changed in more than five (10%) patients in the CTV and PTV, respectively. Nineteen features were found reliably changed in the CTV and 31 features in the PTV, respectively, in 10 (20%) or more patients. These features were not necessarily associated with significantly different longitudinal feature values (group p-value < 0.05). Most reliably changed features in more than 10 patients had excellent or good baseline test-retest reliability ICC, while none showed poor reliability. The RCI method ruled out the features to be reliably changed when substantial feature measurement bias was presented. After applying the RCI criterion, only four and five true significant correlations were confirmed with UDSS and BDSS in the CTV, respectively, with low true significance correlation rates of 10.8% (4/37) and 17.9% (5/28). No true significant correlations were found in the PTV.

CONCLUSIONS

The RCI method was proposed for delta-radiomics and demonstrated using PCa MRgRT data. The RCI has advantages over some other statistical metrics commonly used in the previous delta-radiomics studies, and is useful to reliably identify the longitudinal radiomics feature change on an individual basis. This proposed RCI method should be helpful for the development of essential feature selection methodology in delta-radiomics.

Analysis of online plan adaptation for 1.5T magnetic resonance-guided stereotactic body radiotherapy (MRgSBRT) of prostate cancer

PURPOSE

To analyze and characterize the online plan adaptation of 1.5T magnetic resonance-guided stereotactic body radiotherapy (MRgSBRT) of prostate cancer (PC).

METHODS

PC patients (n = 107) who received adaptive 1.5 Tesla MRgSBRT were included. Online plan adaptation was implemented by either the adapt-to-position (ATP) or adapt-to-shape (ATS) methods. Patients were assigned to the ATS group if they underwent ≥ 1 ATS fraction (n = 51); the remainder were assigned to the ATP group (n = 56). The online plan adaptation records of 535 (107 × 5) fractions were retrospectively reviewed. Rationales for ATS decision-making were determined and analyzed using predefined criteria. Statistics of ATS fractions were summarized. Associations of patient characteristics and clinical factors with ATS utilization were investigated.

RESULTS

There were 87 (16.3%) ATS fractions and 448 ATP fractions (83.7%). The numbers of ATS adoptions in fractions 1-5 were 29 (29/107, 27.1%), 18 (16.8%), 15 (14.0%), 16 (15.0%), and 9 (8.4%), respectively, with significant differences in adoption frequency between fractions (p = 0.007). Other baseline patient characteristics and clinical factors were not significantly associated with ATS classification (all p > 0.05). Underlying criteria for the determination of ATS implementation comprised anatomical changes (77 fractions in 50 patients) and discrete multiple targets (15 fractions in 3 patients). No ATS utilization was determined using dosimetric or online quality assurance criteria.

CONCLUSIONS

This study contributes to facilitating the establishment of a standardized protocol for online MR-guided adaptive radiotherapy in PC.

Prediction of adaptive strategies based on deformation vector field features for MR-guided adaptive radiotherapy of prostate cancer

BACKGROUND

The selection of adaptive strategies in MR-guided adaptive radiotherapy (MRgART) usually relies on subjective review of anatomical changes. However, this kind of review may lead to improper selection of adaptive strategy for some fractions.

PURPOSE

The purpose of this study was to develop prediction models based on deformation vector field (DVF) features for automatic and accurate strategy selection, using prostate cancer as an example.

METHODS

100 fractions of 20 prostate cancer patients were retrospectively selected in this study. Treatment plans using both adapt to position (ATP) strategy and adapt to shape (ATS) strategy were generated. Optimal adaptive strategy was determined according to dosimetric evaluation. DVFs of the deformable image registration (DIR) of daily MRI and CT simulation scans were extracted. The shape, first order statistics, and spatial features were extracted from the DVFs, subjected to further selection using the minimum redundancy maximum relevance (mRMR) method. The number of features (F_n ) was hyper-tuned using bootstrapping method, and then F_n indicating a peak area under the curve (AUC) value was used to construct three prediction models.

RESULTS

According to subjective review, the ATS strategy was adopted for all 100 fractions. However, the evaluation results showed that the ATP strategy could have met the clinical requirements for 23 (23%) fractions. The three prediction models showed high prediction performance, with the best performing model achieving an AUC value of 0.896, corresponding accuracy (ACC), sensitivity (SEN) and specificity (SPC) of 0.9, 0.958, and 0.667, respectively. The features used to construct prediction models included four features extracted from y direction of DVF (DVF_y ) and mask, one feature from z direction of DVF (DVF_z ). It indicated that the deformation along the anterior-posterior direction had a greater impact on determining the adaptive strategy than other directions.

CONCLUSIONS

DVF-feature-based models could accurately predict the adaptive strategy and avoid unnecessary selection of time-consuming ATS strategy, which consequently improves the efficiency of the MRgART process.

Monte Carlo-Based Radiobiological Investigation of the Most Optimal Ion Beam Forming SOBP for Particle Therapy

Proton (p) and carbon (C) ion beams are in clinical use for cancer treatment, although other particles such as He, Be, and B ions have more recently gained attention. Identification of the most optimal ion beam for radiotherapy is a challenging task involving, among others, radiobiological characterization of a beam, which is depth-, energy-, and cell type- dependent. This study uses the FLUKA and MCDS Monte Carlo codes in order to estimate the relative biological effectiveness (RBE) for several ions of potential clinical interest such as p, ⁴He, ⁷Li, ¹⁰Be, ¹⁰B, and ¹²C forming a spread-out Bragg peak (SOBP). More specifically, an energy spectrum of the projectiles corresponding to a 5-cm SOBP at a depth of 8 cm was used. All secondary particles produced by the projectiles were considered and RBE was determined based on radiation-induced Double Strand Breaks (DSBs), as calculated by MCDS. In an attempt to identify the most optimal ion beam, using the latter data, biological optimization was performed and the obtained depth-dose distributions were inter-compared. The results showed that ¹²C ions are more effective inside the SOBP region, which comes at the expense of higher dose values at the tail (i.e., after the SOBP). In contrast, p beams exhibit a higher DSOPB/DEntrance ratio, if physical doses are considered. By performing a biological optimization in order to obtain a homogeneous biological dose (i.e., dose × RBE) in the SOBP, the corresponding advantages of p and ¹²C ions are moderated. ⁷Li ions conveniently combine a considerably lower dose tail and a DSOPB/DEntrance ratio similar to ¹²C. This work contributes towards identification of the most optimal ion beam for cancer therapy. The overall results of this work suggest that ⁷Li ions are of potential interest, although more studies are needed to demonstrate the relevant advantages. Future work will focus on studying more complex beam configurations.

High grade glioma radiation therapy on a high field 1.5 Tesla MR-Linac - workflow and initial experience with daily adapt-to-position (ATP) MR guidance: A first report

PURPOSE

This study reports the workflow and initial clinical experience of high grade glioma (HGG) radiotherapy on the 1.5 T MR-Linac (MRL), with a focus on the temporal variations of the tumor and feasibility of multi-parametric image (mpMRI) acquisition during routine treatment workflow.

MATERIALS AND METHODS

Ten HGG patients treated with radiation within the first year of the MRL's clinical operation, between October 2019 and August 2020, were identified from a prospective database. Workflow timings were recorded and online adaptive plans were generated using the Adapt-To-Position (ATP) workflow. Temporal variation within the FLAIR hyperintense region (FHR) was assessed by the relative FHR volumes (n = 281 contours) and migration distances (maximum linear displacement of the volume). Research mpMRIs were acquired on the MRL during radiation and changes in selected functional parameters were investigated within the FHR.

RESULTS

All patients completed radiotherapy to a median dose of 60 Gy (range, 54-60 Gy) in 30 fractions (range, 30-33), receiving a total of 287 fractions on the MRL. The mean in-room time per fraction with or without post-beam research imaging was 42.9 minutes (range, 25.0-69.0 minutes) and 37.3 minutes (range, 24.0-51.0 minutes), respectively. Three patients (30%) required re-planning between fractions 9 to 12 due to progression of tumor and/or edema identified on daily MRL imaging. At the 10, 20, and 30-day post-first fraction time points 3, 3, and 4 patients, respectively, had a FHR volume that changed by at least 20% relative to the first fraction. Research mpMRIs were successfully acquired on the MRL. The median apparent diffusion coefficient (ADC) within the FHR and the volumes of FLAIR were significantly correlated when data from all patients and time points were pooled (R=0.68, p<.001).

CONCLUSION

We report the first clinical series of HGG patients treated with radiotherapy on the MRL. The ATP workflow and treatment times were clinically acceptable, and daily online MRL imaging triggered adaptive re-planning for selected patients. Acquisition of mpMRIs was feasible on the MRL during routine treatment workflow. Prospective clinical outcomes data is anticipated from the ongoing UNITED phase 2 trial to further refine the role of MR-guided adaptive radiotherapy.

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.

To see or not to see: Evaluation of magnetic resonance imaging sequences for use in MR Linac-based radiotherapy treatment

BACKGROUND/PURPOSE

This work evaluated the suitability of MR derived sequences for use in online adaptive RT workflows on a 1.5 Tesla (T) MR-Linear Accelerator (MR Linac).

MATERIALS/METHODS

Non-patient volunteers were recruited to an ethics approved MR Linac imaging study. Participants attended 1-3 imaging sessions in which a combination of DIXON, 2D and 3D volumetric T1 and T2 weighted images were acquired axially, with volunteers positioned using immobilisation devices typical for radiotherapy to the anatomical region being scanned. Images from each session were appraised by three independent reviewers to determine optimal sequences over six anatomical regions: head and neck, female and male pelvis, thorax (lung), thorax (breast/chest wall) and abdomen. Site specific anatomical structures were graded by the perceived ability to accurately contour a typical organ at risk. Each structure was independently graded on a 4-point Likert scale as 'Very Clear', 'Clear', 'Unclear' or 'Not visible' by observers, consisting of radiographers (therapeutic and diagnostic) and clinicians.

RESULTS

From July 2019 to September 2019, 18 non-patient volunteers underwent 24 imaging sessions in the following anatomical regions: head and neck (n=3), male pelvis (n=4), female pelvis (n=5), lung/oesophagus (n=5) abdomen (n=4) and chest wall/breast (n=3). T2 sequences were the most preferred for perceived ability to contour anatomy in both male and female pelvis. For all other sites T1 weighted DIXON sequences were most favourable.

CONCLUSION

This study has determined the preferential sequence selection for organ visualisation, as a pre-requisite to our institution adopting MR-guided radiotherapy for a more diverse range of disease sites.

Improving liver tumor image contrast and synthesizing novel tissue contrasts by adaptive multiparametric MRI fusion

Purpose

Multiparametric MRI contains rich and complementary anatomical and functional information, which is often utilized separately. This study aims to propose an adaptive multiparametric MRI (mpMRI) fusion method and examine its capability in improving tumor contrast and synthesizing novel tissue contrasts among liver cancer patients.

Methods

An adaptive mpMRI fusion method was developed with five components: image pre-processing, fusion algorithm, database, adaptation rules, and fused MRI. Linear-weighted summation algorithm was used for fusion. Weight-driven and feature-driven adaptations were designed for different applications. A clinical-friendly graphic-user-interface (GUI) was developed in Matlab and used for mpMRI fusion. Twelve liver cancer patients and a digital human phantom were included in the study. Synthesis of novel image contrast and enhancement of image signal and contrast were examined in patient cases. Tumor contrast-to-noise ratio (CNR) and liver signal-to-noise ratio (SNR) were evaluated and compared before and after mpMRI fusion.

Results

The fusion platform was applicable in both XCAT phantom and patient cases. Novel image contrasts, including enhancement of soft-tissue boundary, vertebral body, tumor, and composition of multiple image features in a single image were achieved. Tumor CNR improved from -1.70 ± 2.57 to 4.88 ± 2.28 (p < 0.0001) for T1-w, from 3.39 ± 1.89 to 7.87 ± 3.47 (p < 0.01) for T2-w, and from 1.42 ± 1.66 to 7.69 ± 3.54 (p < 0.001) for T2/T1-w MRI. Liver SNR improved from 2.92 ± 2.39 to 9.96 ± 8.60 (p < 0.05) for DWI. The coefficient of variation (CV) of tumor CNR lowered from 1.57, 0.56, and 1.17 to 0.47, 0.44, and 0.46 for T1-w, T2-w and T2/T1-w MRI, respectively.

Conclusion

A multiparametric MRI fusion method was proposed and a prototype was developed. The method showed potential in improving clinically relevant features such as tumor contrast and liver signal. Synthesis of novel image contrasts including the composition of multiple image features into single image set was achieved.

Delineation uncertainties of tumour volumes on MRI of head and neck cancer patients

•

Role of target delineation uncertainties in head and neck cancer patients.

•

Knowing contouring variations for MRI allows better adaptation of MRLinac for H&N cancers.

•

An interobserver variation for GTV among 8 observers was below 2 mm using MRI.

•

Variability between observers might improve using other imaging modalities.

Background

During the last decade, radiotherapy using MR Linac has gone from research to clinical implementation for different cancer locations. For head and neck cancer (HNC), target delineation based only on MR images is not yet standard, and the utilisation of MRI instead of PET/CT in radiotherapy planning is not well established. We aimed to analyse the inter-observer variation (IOV) in delineating GTV (gross tumour volume) on MR images only for patients with HNC.

Material/methods

32 HNC patients from two independent departments were included. Four clinical oncologists from Denmark and four radiation oncologists from Australia had independently contoured primary tumour GTVs (GTV-T) and nodal GTVs (GTV-N) on T2-weighted MR images obtained at the time of treatment planning. Observers were provided with sets of images, delineation guidelines and patient synopsis. Simultaneous truth and performance level estimation (STAPLE) reference volumes were generated for each structure using all observer contours. The IOV was assessed using the DICE Similarity Coefficient (DSC) and mean absolute surface distance (MASD).

Results

32 GTV-Ts and 68 GTV-Ns were contoured per observer. The median MASD for GTV-Ts and GTV-Ns across all patients was 0.17 cm (range 0.08–0.39 cm) and 0.07 cm (range 0.04–0.33 cm), respectively. Median DSC relative to a STAPLE volume for GTV-Ts and GTV-Ns across all patients were 0.73 and 0.76, respectively. A significant correlation was seen between median DSCs and median volumes of GTV-Ts (Spearman correlation coefficient 0.76, p < 0.001) and of GTV-Ns (Spearman correlation coefficient 0.55, p < 0.001).

Conclusion

Contouring GTVs in patients with HNC on MRI showed that the median IOV for GTV-T and GTV-N was below 2 mm, based on observes from two separate radiation departments. However, there are still specific regions in tumours that are difficult to resolve as either malignant tissue or oedema that potentially could be improved by further training in MR-only delineation.

A Prospective Study of Stereotactic Body Radiotherapy (SBRT) with Concomitant Whole-Pelvic Radiotherapy (WPRT) for High-Risk Localized Prostate Cancer Patients Using 1.5 Tesla Magnetic Resonance Guidance: The Preliminary Clinical Outcome

Background: Conventionally fractionated whole-pelvic nodal radiotherapy (WPRT) improves clinical outcome compared to prostate-only RT in high-risk prostate cancer (HR-PC). MR-guided stereotactic body radiotherapy (MRgSBRT) with concomitant WPRT represents a novel radiotherapy (RT) paradigm for HR-PC, potentially improving online image guidance and clinical outcomes. This study aims to report the preliminary clinical experiences and treatment outcome of 1.5 Tesla adaptive MRgSBRT with concomitant WPRT in HR-PC patients. Materials and methods: Forty-two consecutive HR-PC patients (72.5 ± 6.8 years) were prospectively enrolled, treated by online adaptive MRgSBRT (8 Gy(prostate)/5 Gy(WPRT) × 5 fractions) combined with androgen deprivation therapy (ADT) and followed up (median: 251 days, range: 20−609 days). Clinical outcomes were measured by gastrointestinal (GI) and genitourinary (GU) toxicities according to the Common Terminology Criteria for Adverse Events (CTCAE) Scale v. 5.0, patient-reported quality of life (QoL) with EPIC (Expanded Prostate Cancer Index Composite) questionnaire, and prostate-specific antigen (PSA) responses. Results: All MRgSBRT fractions achieved planning objectives and dose specifications of the targets and organs at risk, and they were successfully delivered. The maximum cumulative acute GI/GU grade 1 and 2 toxicity rates were 19.0%/81.0% and 2.4%/7.1%, respectively. The subacute (>30 days) GI/GU grade 1 and 2 toxicity rates were 21.4%/64.3% and 2.4%/2.4%, respectively. No grade 3 toxicities were reported. QoL showed insignificant changes in urinary, bowel, sexual, and hormonal domain scores during the follow-up period. All patients had early post-MRgSBRT biochemical responses, while biochemical recurrence (PSA nadir + 2 ng/mL) occurred in one patient at month 18. Conclusions: To our knowledge, this is the first prospective study that showed the clinical outcomes of MRgSBRT with concomitant WPRT in HR-PC patients. The early results suggested favorable treatment-related toxicities and encouraging patient-reported QoLs, but long-term follow-up is needed to confirm our early results.

Development of a GPU-superposition Monte Carlo code for fast dose calculation in magnetic fields

Objective. To develop and validate a graphics processing unit (GPU) based superposition Monte Carlo (SMC) code for efficient and accurate dose calculation in magnetic fields. Approach. A series of mono-energy photons ranging from 25 keV to 7.7 MeV were simulated with EGSnrc in a water phantom to generate particle tracks database. SMC physics was extended with charged particle transport in magnetic fields and subsequently programmed on GPU as gSMC. Optimized simulation scheme was designed by combining variance reduction techniques to relieve the thread divergence issue in general GPU-MC codes and improve the calculation efficiency. The gSMC code’s dose calculation accuracy and efficiency were assessed through both phantoms and patient cases. Main results. gSMC accurately calculated the dose in various phantoms for both B = 0 T and B = 1.5 T, and it matched EGSnrc well with a root mean square error of less than 1.0% for the entire depth dose region. Patient cases validation also showed a high dose agreement with EGSnrc with 3D gamma passing rate (2%/2 mm) large than 97% for all tested tumor sites. Combined with photon splitting and particle track repeating techniques, gSMC resolved the thread divergence issue and showed an efficiency gain of 186–304 relative to EGSnrc with 10 CPU threads. Significance. A GPU-superposition Monte Carlo code called gSMC was developed and validated for dose calculation in magnetic fields. The developed code’s high calculation accuracy and efficiency make it suitable for dose calculation tasks in online adaptive radiotherapy with MR-LINAC.

AAPM Task Group Report 303 endorsed by the ABS: MRI Implementation in HDR Brachytherapy-Considerations from Simulation to Treatment

The Task Group (TG) on Magnetic Resonance Imaging (MRI) Implementation in High Dose Rate (HDR) Brachytherapy - Considerations from Simulation to Treatment, TG 303, was constituted by the American Association of Physicists in Medicine's (AAPM's) Science Council under the direction of the Therapy Physics Committee, the Brachytherapy Subcommittee, and the Working Group on Brachytherapy Clinical Applications. The TG was charged with developing recommendations for commissioning, clinical implementation, and on-going quality assurance (QA). Additionally, the TG was charged with describing HDR brachytherapy (BT) workflows and evaluating practical consideration that arise when implementing MR imaging. For brevity, the report is focused on the treatment of gynecologic and prostate cancer. The TG report provides an introduction and rationale for MRI implementation in BT, a review of previous publications on topics including available applicators, clinical trials, previously published BT related TG reports, and new image guided recommendations beyond CT based practices. The report describes MRI protocols and methodologies, including recommendations for the clinical implementation and logical considerations for MR imaging for HDR BT. Given the evolution from prescriptive to risk-based QA,¹ an example of a risk-based analysis using MRI-based, prostate HDR BT is presented. In summary, the TG report is intended to provide clear and comprehensive guidelines and recommendations for commissioning, clinical implementation, and QA for MRI-based HDR BT that may be utilized by the medical physics community to streamline this process. This report is endorsed by the American Brachytherapy Society (ABS). This article is protected by copyright. All rights reserved.

Acquisition repeatability of MRI radiomics features in the head and neck: a dual-3D-sequence multi-scan study

Radiomics has increasingly been investigated as a potential biomarker in quantitative imaging to facilitate personalized diagnosis and treatment of head and neck cancer (HNC), a group of malignancies associated with high heterogeneity. However, the feature reliability of radiomics is a major obstacle to its broad validity and generality in application to the highly heterogeneous head and neck (HN) tissues. In particular, feature repeatability of radiomics in magnetic resonance imaging (MRI) acquisition, which is considered a crucial confounding factor of radiomics feature reliability, is still sparsely investigated. This study prospectively investigated the acquisition repeatability of 93 MRI radiomics features in ten HN tissues of 15 healthy volunteers, aiming for potential magnetic resonance-guided radiotherapy (MRgRT) treatment of HNC. Each subject underwent four MRI acquisitions with MRgRT treatment position and immobilization using two pulse sequences of 3D T1-weighed turbo spin-echo and 3D T2-weighed turbo spin-echo on a 1.5 T MRI simulator. The repeatability of radiomics feature acquisition was evaluated in terms of the intraclass correlation coefficient (ICC), whereas within-subject acquisition variability was evaluated in terms of the coefficient of variation (CV). The results showed that MRI radiomics features exhibited heterogeneous acquisition variability and uncertainty dependent on feature types, tissues, and pulse sequences. Only a small fraction of features showed excellent acquisition repeatability (ICC > 0.9) and low within-subject variability. Multiple MRI scans improved the accuracy and confidence of the identification of reliable features concerning MRI acquisition compared to simple test-retest repeated scans. This study contributes to the literature on the reliability of radiomics features with respect to MRI acquisition and the selection of reliable radiomics features for use in modeling in future HNC MRgRT applications.

Characterizing magnetically focused contamination electrons by off-axis irradiation on an inline MRI-Linac

Purpose

The aim of this study is to investigate off‐axis irradiation on the Australian MRI‐Linac using experiments and Monte Carlo simulations. Simulations are used to verify experimental measurements and to determine the minimum offset distance required to separate electron contamination from the photon field.

Methods

Dosimetric measurements were performed using a microDiamond detector, Gafchromic^® EBT3 film, and MOSkin^TM. Three field sizes were investigated including 1.9 × 1.9, 5.8 × 5.8, and 9.7 × 9.6 cm². Each field was offset a maximum distance, approximately 10 cm, from the central magnetic axis (isocenter). Percentage depth doses (PDDs) were collected at a source‐to‐surface distance (SSD) of 1.8 m for fields collimated centrally and off‐axis. PDD measurements were also acquired at isocenter for each off‐axis field to measure electron contamination. Monte Carlo simulations were used to verify experimental measurements, determine the minimum field offset distance, and demonstrate the use of a spoiler to absorb electron contamination.

Results

Off‐axis irradiation separates the majority of electron contamination from an x‐ray beam and was found to significantly reduce in‐field surface dose. For the 1.9 × 1.9, 5.8 × 5.8, and 9.7 × 9.6 cm² field, surface dose was reduced from 120.9% to 24.9%, 229.7% to 39.2%, and 355.3% to 47.3%, respectively. Monte Carlo simulations generally were within experimental error to MOSkin^TM and microDiamond, and used to determine the minimum offset distance, 2.1 cm, from the field edge to isocenter. A water spoiler 2 cm thick was shown to reduce electron contamination dose to near zero.

Conclusions

Experimental and simulation data were acquired for a range of field sizes to investigate off‐axis irradiation on an inline MRI‐Linac. The skin sparing effect was observed with off‐axis irradiation, a feature that cannot be achieved to the same extent with other methods, such as bolusing, for beams at isocenter.

MR-guided radiotherapy for prostate cancer: state of the art and future perspectives

Advances in radiotherapy technology have increased precision of treatment delivery and in some tumour types, improved cure rates and decreased side effects. A new generation of radiotherapy machines, hybrids of an MRI scanner and a linear accelerator, has the potential to further transform the practice of radiation therapy in some cancers. Facilitating superior image quality and the ability to change the dose distribution online on a daily basis (termed "daily adaptive replanning"), MRI-guided radiotherapy machines allow for new possibilities including increasing dose, for hard to treat cancers, and more selective sparing of healthy tissues, where toxicity reduction is the key priority.These machines have already been used to treat most types of cancer, although experience is still in its infancy. This review summarises the potential and current evidence for MRI-guided radiotherapy, with a predominant focus on prostate cancer. Current advantages and disadvantages are discussed including a realistic appraisal of the likely potential to improve patient outcomes. In addition, horizon scanning for near-term possibilities for research and development will hopefully delineate the potential role for this technology over the next decade.

Clinical implementation and feasibility of long-course fractionated MR-guided chemoradiotherapy for patients with esophageal cancer: an R-IDEAL stage 1b/2a evaluation of technical innovation

•

Online MR-guided long-course fractionated chemoradiotherapy for patients with esophageal cancer was feasible in 7 out of 9 patients.

•

Median treatment time was 53 min per fraction.

•

MRgRT resulted in a reduction in mean heart dose (12%) and mean lung dose (26%) compared to CBCT-guided radiotherapy.

•

Limited intrafraction motion was observed during dose delivery.

Purpose

This R-Ideal stage 1b/2a study describes the workflow and feasibility of long-course fractionated online adaptive MR-guided chemoradiotherapy with reduced CTV-to-PTV margins on the 1.5T MR-Linac for patients with esophageal cancer.

Methods

Patients with esophageal cancer scheduled to undergo chemoradiation were treated on a 1.5T MR-Linac. Daily MR-images were acquired for online contour adaptation and replanning. Contours were manually adapted to match the daily anatomy and an isotropic CTV-to-PTV margin of 6 mm was applied. Time was recorded for all individual steps in the workflow. Feasibility and patient tolerability were defined as on-table time of ≤60 min and completion of >95% of the fractions on the MR-Linac, respectively. Positioning verification and post-treatment MRIs were retrospectively analyzed and dosimetric parameters were compared to standard non-adaptive conventional treatment plans.

Results

Nine patients with esophageal cancer were treated with chemoradiation; eight patients received 41.4 Gy in 23 fractions and one received 50.4 Gy in 28 fractions. Four patients received all planned fractions on the MR-Linac, whereas for two patients >5% of fractions were rescheduled to a conventional linac for reasons of discomfort. A total of 183 (86%) of 212 scheduled fractions were successfully delivered on the MR-Linac. Three fractions ended prematurely due to technical issues and 26 fractions were rescheduled on a conventional linac due to MR-Linac downtime (n = 10), logistical reasons (n = 3) or discomfort (n = 13).

The median time per fraction was 53 min (IQR = 3 min). Daily adapted MR-Linac plans had similar target coverage, whereas dose to the organs-at-risk was significantly reduced compared to conventional treatment (26% and 12% reduction in mean lung and heart dose, respectively).

Conclusion

Daily online adaptive fractionated chemoradiotherapy with reduced PTV margins is moderately feasible for esophageal cancer and results in better sparing of heart and lungs. Future studies should focus on further optimization and acceleration of the current workflow.

Multi parametric magnetic resonance imaging for radiation treatment planning

In recent years, multi-parametric magnetic resonance imaging (MpMRI) has played a major role in radiation therapy treatment planning. The superior soft tissue contrast, functional or physiological imaging capabilities and the flexibility of site-specific image sequence development has placed MpMRI at the forefront. In this article, the present status of MpMRI for external beam radiation therapy planning is reviewed. Common MpMRI sequences, preprocessing and QA strategies are briefly discussed, and various image registration techniques and strategies are addressed. Image segmentation methods including automatic segmentation and deep learning techniques for organs at risk and target delineation are reviewed. Due to the advancement in MRI guided online adaptive radiotherapy, treatment planning considerations addressing MRI only planning are also discussed. This article is protected by copyright. All rights reserved.

A narrative review of MRI acquisition for MR-guided-radiotherapy in prostate cancer

Magnetic resonance guided radiotherapy (MRgRT), enabled by the clinical introduction of the integrated MRI and linear accelerator (MR-LINAC), is a novel technique for prostate cancer (PCa) treatment, promising to further improve clinical outcome and reduce toxicity. The role of prostate MRI has been greatly expanded from the traditional PCa diagnosis to also PCa screening, treatment and surveillance. Diagnostic prostate MRI has been relatively familiar in the community, particularly with the development of Prostate Imaging - Reporting and Data System (PI-RADS). But, on the other hand, the use of MRI in the emerging clinical practice of PCa MRgRT, which is substantially different from that in PCa diagnosis, has been so far sparsely presented in the medical literature. This review attempts to give a comprehensive overview of MRI acquisition techniques currently used in the clinical workflows of PCa MRgRT, from treatment planning to online treatment guidance, in order to promote MRI practice and research for PCa MRgRT. In particular, the major differences in the MRI acquisition of PCa MRgRT from that of diagnostic prostate MRI are demonstrated and explained. Limitations in the current MRI acquisition for PCa MRgRT are analyzed. The future developments of MRI in the PCa MRgRT are also discussed.

Patterns of Care, Tolerability, and Safety of the First Cohort of Patients Treated on a Novel High-Field MR-Linac Within the MOMENTUM Study: Initial Results From a Prospective Multi-Institutional Registry

PURPOSE

High-field magnetic resonance-linear accelerators (MR-Linacs), linear accelerators combined with a diagnostic magnetic resonance imaging (MRI) scanner and online adaptive workflow, potentially give rise to novel online anatomic and response adaptive radiation therapy paradigms. The first high-field (1.5T) MR-Linac received regulatory approval in late 2018, and little is known about clinical use, patient tolerability of daily high-field MRI, and toxicity of treatments. Herein we report the initial experience within the MOMENTUM Study (NCT04075305), a prospective international registry of the MR-Linac Consortium.

METHODS AND MATERIALS

Patients were included between February 2019 and October 2020 at 7 institutions in 4 countries. We used descriptive statistics to describe the patterns of care, tolerability (the percentage of patients discontinuing their course early), and safety (grade 3-5 Common Terminology Criteria for Adverse Events v.5 acute toxicity within 3 months after the end of treatment).

RESULTS

A total 943 patients participated in the MOMENTUM Study, 702 of whom had complete baseline data at the time of this analysis. Patients were primarily male (79%) with a median age of 68 years (range, 22-93) and were treated for 39 different indications. The most frequent indications were prostate (40%), oligometastatic lymph node (17%), brain (12%), and rectal (10%) cancers. The median number of fractions was 5 (range, 1-35). Six patients discontinued MR-Linac treatments, but none due to an inability to tolerate repeated high-field MRI. Of the 415 patients with complete data on acute toxicity at 3-month follow-up, 18 (4%) patients experienced grade 3 acute toxicity related to radiation. No grade 4 or 5 acute toxicity related to radiation was observed.

CONCLUSIONS

In the first 21 months of our study, patterns of care were diverse with respect to clinical utilization, body sites, and radiation prescriptions. No patient discontinued treatment due to inability to tolerate daily high-field MRI scans, and the acute radiation toxicity experience was encouraging.

Contrast-enhanced proton radiographic sensitivity limits for tumor detection

Purpose: Proton radiography may guide proton therapy cancer treatments with beam's-eye-view anatomical images and a proton-based estimation of proton stopping power. However, without contrast enhancement, proton radiography will not be able to distinguish tumor from tissue. To provide this contrast, functionalized, high- Z nanoparticles that specifically target a tumor could be injected into a patient before imaging. We conducted this study to understand the ability of gold, as a high- Z , biologically compatible tracer, to differentiate tumors from surrounding tissue. Approach: Acrylic and gold phantoms simulate a tumor tagged with gold nanoparticles (AuNPs). Calculations correlate a given thickness of gold to levels of tumor AuNP uptake reported in the literature. An identity, × 3 , and × 7 proton magnifying lens acquired lens-refocused proton radiographs at the 800-MeV LANSCE proton beam. The effects of gold in the phantoms, in terms of percent density change, were observed as changes in measured transmission. Variable areal densities of acrylic modeled the thickness of the human body. Results: A 1 - μ m -thick gold strip was discernible within 1 cm of acrylic, an areal density change of 0.2%. Behind 20 cm of acrylic, a 40 - μ m gold strip was visible. A 1-cm-diameter tumor tagged with 1 × 10 5 50-nm AuNPs per cell has an amount of contrast agent embedded within it that is equivalent to a 65 - μ m thickness of gold, an areal density change of 0.63% in a tissue thickness of 20 cm, which is expected to be visible in a typical proton radiograph. Conclusions: We indicate that AuNP-enhanced proton radiography might be a feasible technology to provide image-guidance to proton therapy, potentially reducing off-target effects and sparing nearby tissue. These data can be used to develop treatment plans and clinical applications can be derived from the simulations.

MR SIGnature MAtching (MRSIGMA) with retrospective self-evaluation for real-time volumetric motion imaging

Objective. MR SIGnature MAtching (MRSIGMA) is a real-time volumetric MRI technique to image tumor and organs at risk motion in real-time for radiotherapy applications, where a dictionary of high-resolution 3D motion states and associated motion signatures are computed first during offline training and real-time 3D imaging is performed afterwards using fast signature-only acquisition and signature matching. However, the lack of a reference image with similar spatial resolution and temporal resolution introduces significant challenges forin vivovalidation.Approach. This work proposes a retrospective self-validation for MRSIGMA, where the same data used for real-time imaging are used to create a non-real-time reference for comparison. MRSIGMA with self-validation is tested in patients with liver tumors using quantitative metrics defined on the tumor and nearby organs-at-risk structures. The dice coefficient between contours defined on the real-time MRSIGMA and non-real-time reference was used to assess motion imaging performance.Main Results. Total latency (including signature acquisition and signature matching) was between 250 and 314 ms, which is sufficient for organs affected by respiratory motion. Mean ± standard deviation dice coefficient over time was 0.74 ± 0.03 for patients imaged without contrast agent and 0.87 ± 0.03 for patients imaged with contrast agent, which demonstrated high-performance real-time motion imaging.Signficance. MRSIGMA with self-evaluation provides a means to perform real-time volumetric MRI for organ motion tracking with quantitative performance measures.

The Impact of Intra-thoracic Anatomical Changes upon the Delivery of Lung Stereotactic Ablative Radiotherapy

AIMS

So far, the impact of intra-thoracic anatomical changes (ITACs) on patients treated with stereotactic ablative radiotherapy (SABR) for early-stage non-small cell lung cancer is unknown. Studying these is important, as ITACs have the potential to impact the workflow and reduce treatment quality. The aim of this study was to assess and categorise ITACs, as detected on cone beam computed tomography scans (CBCT), and their subsequent impact upon treatment in lung cancer patients treated with SABR.

MATERIALS AND METHODS

CBCTs from 100 patients treated with SABR for early non-small cell lung cancer were retrospectively reviewed. The presence of the following ITACs was assessed: atelectasis, infiltrative change, pleural effusion, baseline shift and gross tumour volume (GTV) increase and decrease. ITACs were graded using a traffic light protocol. This was adapted from a tool previously developed to assesses potential target undercoverage or organ at risk overdose. The frequency of physics or clinician review was noted. A linear mixed effects model was used to assess the relationship between ITAC grade and set-up time (time from first CBCT to beam delivery).

RESULTS

ITACs were observed in 22% of patients. Twenty-one per cent of these were categorised as 'red', implying a risk of underdosage to the GTV. Most were 'yellow' (51%), indicating little impact upon planning target volume coverage of the GTV. Physics or clinician review was required in 10% of all treatment fractions overall. Three patients needed their treatment replanned. The mixed effect model analysis showed that ITACs cause a significant prolongation of set-up time (Χ2(3) = 9.22, P = 0.02).

CONCLUSION

Most ITACs were minor, but associated with unplanned physics or clinician review, representing a potentially significant resource burden. ITACs also had a significant impact upon set-up time, with consequences for the wider workflow and intra-fraction motion. Detailed guidance on the management of ITACs is needed to provide support for therapeutic radiographers delivering lung SABR.

1.5T Magnetic Resonance-Guided Stereotactic Body Radiotherapy for Localized Prostate Cancer: Preliminary Clinical Results of Clinician- and Patient-Reported Outcomes

BACKGROUND

Magnetic resonance-guided stereotactic body radiotherapy (MRgSBRT) offers the potential for achieving better prostate cancer (PC) treatment outcomes. This study reports the preliminary clinical results of 1.5T MRgSBRT in localized PC, based on both clinician-reported outcome measurement (CROM) and patient-reported outcome measurement (PROM).

METHODS

Fifty-one consecutive localized PC patients were prospectively enrolled with a median follow-up of 199 days. MRgSBRT was delivered in five fractions of 7.25-8 Gy with daily online adaptation. Clinician-reported gastrointestinal (GI) and genitourinary (GU) adverse events based on the Common Terminology Criteria for Adverse Events (CTCAE) Scale v. 5.0 were assessed. The Expanded Prostate Cancer Index Composite Questionnaire was collected at baseline, 1 month, and every 3 months thereafter. Serial prostate-specific antigen measurements were longitudinally recorded.

RESULTS

The maximum cumulative clinician-reported grade ≥ 2 acute GU and GI toxicities were 11.8% (6/51) and 2.0% (1/51), respectively, while grade ≥ 2 subacute GU and GI toxicities were 2.3% (1/43) each. Patient-reported urinary, bowel, and hormonal domain summary scores were reduced at 1 month, then gradually returned to baseline levels, with the exception of the sexual domain. Domain-specific subscale scores showed similar longitudinal changes. All patients had early post-MRgSBRT biochemical responses.

CONCLUSIONS

The finding of low toxicity supports the accumulation of clinical evidence for 1.5T MRgSBRT in localized PC.

Reliability of MRI radiomics features in MR-guided radiotherapy for prostate cancer: Repeatability, reproducibility, and within-subject agreement

PURPOSE

The MR-guided radiotherapy (MRgRT) images on the integrated MRI and linear accelerator (MR-LINAC) might facilitate radiomics analysis for longitudinal treatment response assessment. However, the reliability of MRgRT radiomics features is largely unknown. This study aims to investigate MRgRT radiomics feature reliability acquired using a standardized 3D-T2W-TSE sequence in terms of repeatability, reproducibility, and within-subject feature agreement on a 1.5T MR-simulator and a 1.5T MR-LINAC for prostate cancer (PC).

METHODS

Twenty-six consecutive PC patients who underwent one MRI-simulator scan and two MR-LINAC scans before dose delivery were retrospectively included. The three MRI datasets were rigidly co-registered. 1023 first-order and texture radiomics features were extracted with different intensity bin widths for each scan in the manually segmented clinical target volume (CTV) and planning target volume (PTV) by an experienced radiation oncologist. Intraclass correlation coefficient (ICC) was used to evaluate feature repeatability between MR-LINAC scans and reproducibility between MRI-simulator and MR-LINAC scans. The within-subject feature value agreements were evaluated using Bland-Altman analysis. The impact of inter-observer segmentation on the radiomics feature reliability was also examined based on the second manual segmentation of CTV and PTV by an MRI researcher.

RESULTS

Based on the segmentation by the radiation oncologist and the default bin width of 25, 9.6%, 24.1%, 49.6%, and 16.8% of the total 1023 features exhibited excellent (ICC > 0.9), good (0.9 > ICC > 0.75), moderate (0.75 > ICC > 0.5), and poor (ICC < 0.5) repeatability in the CTV, and 9.2%, 26.8%, 50.5%, and 13.5% in the PTV, respectively. For reproducibility, the corresponding feature percentages were 8.9%, 19.7%, 41.9%, and 29.6% in the CTV, and 8.4%, 17.8%, 47.9%, and 26% in the PTV. Feature reliability was not notably influenced by intensity bin width for discretization. BA analysis revealed wide 95% limit-of-agreements and substantial biases of feature values between CTV and PTV and between any two MRI scans. The features even with excellent ICC were still subjected to considerable inter-scan feature variations in each individual subject. The analysis on the second segmentation by the MRI researcher showed insignificantly different feature repeatability and reproducibility in terms of ICC values.

CONCLUSIONS

Only a small proportion of features exhibited excellent/good repeatability and reproducibility, highlighting the importance of reliable MRgRT feature selection. The within-subject feature values were subjected to considerable inter-scan variations, imposing a challenge on the determination of the smallest detectable change in future MRgRT delta-radiomics studies.

Deep learning based synthetic-CT generation in radiotherapy and PET: A review

Recently,deep learning (DL)-based methods for the generation of synthetic computed tomography (sCT) have received significant research attention as an alternative to classical ones. We present here a systematic review of these methods by grouping them into three categories, according to their clinical applications: (i) to replace computed tomography in magnetic resonance (MR) based treatment planning, (ii) facilitate cone-beam computed tomography based image-guided adaptive radiotherapy, and (iii) derive attenuation maps for the correction of positron emission tomography. Appropriate database searching was performed on journal articles published between January 2014 and December 2020. The DL methods' key characteristics were extracted from each eligible study, and a comprehensive comparison among network architectures and metrics was reported. A detailed review of each category was given, highlighting essential contributions, identifying specific challenges, and summarizing the achievements. Lastly, the statistics of all the cited works from various aspects were analyzed, revealing the popularity and future trends and the potential of DL-based sCT generation. The current status of DL-based sCT generation was evaluated, assessing the clinical readiness of the presented methods.

Task group 284 report: magnetic resonance imaging simulation in radiotherapy: considerations for clinical implementation, optimization, and quality assurance

The use of dedicated magnetic resonance simulation (MR-SIM) platforms in Radiation Oncology has expanded rapidly, introducing new equipment and functionality with the overall goal of improving the accuracy of radiation treatment planning. However, this emerging technology presents a new set of challenges that need to be addressed for safe and effective MR-SIM implementation. The major objectives of this report are to provide recommendations for commercially available MR simulators, including initial equipment selection, siting, acceptance testing, quality assurance, optimization of dedicated radiation therapy specific MR-SIM workflows, patient-specific considerations, safety, and staffing. Major contributions include guidance on motion and distortion management as well as MRI coil configurations to accommodate patients immobilized in the treatment position. Examples of optimized protocols and checklists for QA programs are provided. While the recommendations provided here are minimum requirements, emerging areas and unmet needs are also highlighted for future development.

Clinical assessment of geometric distortion for a 0.35T MR-guided radiotherapy system

Purpose

To estimate the overall spatial distortion on clinical patient images for a 0.35 T MR‐guided radiotherapy system.

Methods

Ten patients with head‐and‐neck cancer underwent CT and MR simulations with identical immobilization. The MR images underwent the standard systematic distortion correction post‐processing. The images were rigidly registered and landmark‐based analysis was performed by an anatomical expert. Distortion was quantified using Euclidean distance between each landmark pair and tagged by tissue interface: bone‐tissue, soft tissue, or air‐tissue. For baseline comparisons, an anthropomorphic phantom was imaged and analyzed.

Results

The average spatial discrepancy between CT and MR landmarks was 1.15 ± 1.14 mm for the phantom and 1.46 ± 1.78 mm for patients. The error histogram peaked at 0–1 mm. 66% of the discrepancies were <2 mm and 51% <1 mm. In the patient data, statistically significant differences (p‐values < 0.0001) were found between the different tissue interfaces with averages of 0.88 ± 1.24 mm, 2.01 ± 2.20 mm, and 1.41 ± 1.56 mm for the air/tissue, bone/tissue, and soft tissue, respectively. The distortion generally correlated with the in‐plane radial distance from the image center along the longitudinal axis of the MR.

Conclusion

Spatial distortion remains in the MR images after systematic distortion corrections. Although the average errors were relatively small, large distortions observed at bone/tissue interfaces emphasize the need for quantitative methods for assessing and correcting patient‐specific spatial distortions.

The first internal electromagnetic motion monitoring implementation for stereotactic liver radiotherapy in China: procedures and preliminary results

BACKGROUND

Respiratory motion may compromise the dose delivery accuracy in liver stereotactic body radiation therapy (SBRT). Motion management can improve treatment delivery. However, external surrogate signal may be unstable and inaccurate. This study reports the first case of liver SBRT based on internal electromagnetic motion monitoring (Calypso, Varian Medical Systems, USA) in China.

MATERIALS AND METHODS

The patient with a primary liver cancer was treated with respiratory-gated SBRT guided by three implanted electromagnetic transponders. The treatment was carried out in breath-hold end-exhale with beam-on when the centroid of the three transponders drifted within 5 mm (left-right (LR), anterior-posterior (AP) and cranio-caudal (CC) directions) from the planned position. The motion monitoring treatments were delivered in breath-hold end-exhale mode with the energy of 6 MV in FFF mode with 1200 monitor units (MU) per minute. For each fraction, QA results, intertransponder distances, geometric checks as well as tumor motion logs were explicitly recorded.

RESULTS

Comparing with the plan data, distance variances between each two transponders were - 0.56 ± 0.32 mm, 0.17 ± 0.33 mm and - 0.82 ± 0.68 mm. Geometric residual, the pitch, roll and yaw angles were 0.48 ± 0.21 mm (threshold 2.0 mm), 2.17° ± 1.85° (threshold 10°), - 2.42° ± 1.51° (threshold 10°) and 1.67° ± 1.07° (threshold 10°), respectively. The delivery time of the five fields were 13.8 s, 13.1 s, 11.2 s, 11.6 s, and 11.6 s with the average value of 12.3 ± 1.1 s. Treatment duration of each fraction ranged from 6.2 to 21.4 min, with the average value of 11.3 ± 5.0 min.

CONCLUSIONS

The first case of liver SBRT patient of China based on internal electromagnetic motion monitoring was performed. The system had a high tracking accuracy, and it did not delay the treatment time. In addition, the patient did not show any severe side effects except for grade I myelotoxicity. The internal electromagnetic motion monitoring system provides a real-time and direct way to track liver tumor targets.

Rapid 4D-MRI reconstruction using a deep radial convolutional neural network: Dracula

BACKGROUND AND PURPOSE

4D and midposition MRI could inform plan adaptation in lung and abdominal MR-guided radiotherapy. We present deep learning-based solutions to overcome long 4D-MRI reconstruction times while maintaining high image quality and short scan times.

METHODS

Two 3D U-net deep convolutional neural networks were trained to accelerate the 4D joint MoCo-HDTV reconstruction. For the first network, gridded and joint MoCo-HDTV-reconstructed 4D-MRI were used as input and target data, respectively, whereas the second network was trained to directly calculate the midposition image. For both networks, input and target data had dimensions of 256 × 256 voxels (2D) and 16 respiratory phases. Deep learning-based MRI were verified against joint MoCo-HDTV-reconstructed MRI using the structural similarity index (SSIM) and the naturalness image quality evaluator (NIQE). Moreover, two experienced observers contoured the gross tumour volume and scored the images in a blinded study.

RESULTS

For 12 subjects, previously unseen by the networks, high-quality 4D and midposition MRI (1.25 × 1.25 × 3.3 mm3) were each reconstructed from gridded images in only 28 seconds per subject. Excellent agreement was found between deep-learning-based and joint MoCo-HDTV-reconstructed MRI (average SSIM ≥ 0.96, NIQE scores 7.94 and 5.66). Deep-learning-based 4D-MRI were clinically acceptable for target and organ-at-risk delineation. Tumour positions agreed within 0.7 mm on midposition images.

CONCLUSION

Our results suggest that the joint MoCo-HDTV and midposition algorithms can each be approximated by a deep convolutional neural network. This rapid reconstruction of 4D and midposition MRI facilitates online treatment adaptation in thoracic or abdominal MR-guided radiotherapy.

CTV-to-PTV margin assessment for esophageal cancer radiotherapy based on an accumulated dose analysis

PURPOSE

This study aimed to assess the smallest clinical target volume (CTV) to planned target volume (PTV) margins for esophageal cancer radiotherapy using daily online registration to the bony anatomy that yield full dosimetric coverage over the course of treatment.

METHODS

29 esophageal cancer patients underwent six T2-weighted MRI scans at weekly intervals. An online bone-match image-guided radiotherapy treatment of five fractions was simulated for each patient. Multiple conformal treatment plans with increasing margins around the CTV were created for each patient. Then, the dose was warped to obtain an accumulated dose per simulated fraction. Full target coverage by 95% of the prescribed dose was assessed as a function of margin expansion in six directions. If target coverage in a single direction was accomplished, then the respective margin remained fixed for the subsequent dose plans. Margins in uncovered directions were increased in a new dose plan until full target coverage was achieved.

RESULTS

The smallest set of CTV-to-PTV margins that yielded full dosimetric CTV coverage was 8 mm in posterior and right direction, 9 mm in anterior and cranial direction and 10 mm in left and caudal direction for 27 out of 29 patients. In two patients the curvature of the esophagus considerably changed between fractions, which required a 17 and 23 mm margin in right direction.

CONCLUSION

Accumulated dose analysis revealed that CTV-to-PTV treatment margins of 8, 9 and 10 mm in posterior & right, anterior & cranial and left & caudal direction, respectively, are sufficient to account for interfraction tumor variations over the course of treatment when applying a daily online bone match. However, two patients with extreme esophageal interfraction motion were insufficiently covered with these margins and were identified as patients requiring replanning to achieve full target coverage.

Quantitative assessment of acquisition imaging parameters on MRI radiomics features: a prospective anthropomorphic phantom study using a 3D-T2W-TSE sequence for MR-guided-radiotherapy

Background

MRI pulse sequences and imaging parameters substantially influence the variation of MRI radiomics features, thus impose a critical challenge on MRI radiomics reproducibility and reliability. This study aims to prospectively investigate the impact of various imaging parameters on MRI radiomics features in a 3D T2-weighted (T2W) turbo-spin-echo (TSE) pulse sequence for MR-guided-radiotherapy (MRgRT).

Methods

An anthropomorphic phantom was scanned using a 3D-T2W-TSE MRgRT sequence at 1.5T under a variety of acquisition imaging parameter changes. T1 and T2 relaxation times of the phantom were also measured. 93 first-order and texture radiomics features in the original and 14 transformed images, yielding 1,395 features in total, were extracted from 10 volumes-of-interest (VOIs). The percentage deviation (d%) of radiomics feature values from the baseline values and intra-class correlation coefficient (ICC) with the baseline were calculated. Robust radiomics features were identified based on the excellent agreement of radiomics feature values with the baseline, i.e., the averaged d% <5% and ICC >0.90 in all VOIs for all imaging parameter variations.

Results

The radiomics feature values changed considerably but to different degrees with different imaging parameter adjustments, in the ten VOIs. The deviation d% ranged from 0.02% to 321.3%, with a mean of 12.5% averaged for all original features in all ten VOIs. First-order and GLCM features were generally more robust to imaging parameters than other features in the original images. There were also significantly different radiomics feature values (ANOVA, P<0.001) between the original and the transformed images, exhibiting quite different robustness to imaging parameters. 330 out of 1395 features (23.7%) robust to imaging parameters were identified. GLCM and GLSZM features had the most (42.5%, 153/360) and least (3.8%, 9/240) robust features in the original and transformed images, respectively.

Conclusions

This study helps better understand the quantitative dependence of radiomics feature values on imaging parameters in a 3D-T2W-TSE sequence for MRgRT. Imaging parameter heterogeneity should be considered as a significant source of radiomics variability and uncertainty, which must be well harmonized for reliable clinical use. The identified robust features to imaging parameters are helpful for the pre-selection of radiomics features for reliable radiomics modeling.

Initial clinical experience of patient-specific QA of treatment delivery in online adaptive radiotherapy using a 1.5 T MR-Linac

Purpose. This study aims to evaluate the performance of a commercial 1.5 T MR-Linac by analyzing its patient-specific quality assurance (QA) data collected during one full year of clinical operation.Methods and Materials. The patient-specific QA system consisted of offline delivery QA (DQA) and online calculation-based QA. Offline DQA was based on ArcCHECK-MR combined with an ionization chamber. Online QA was performed using RadCalc that calculated and compared the point dose calculation with the treatment planning system (TPS). A total of 24 patients with 189 treatment fractions were enrolled in this study. Gamma analysis was performed and the threshold that encompassed 95% of QA results (T95) was reported. The plan complexity metric was calculated for each plan and compared with the dose measurements to determine whether any correlation existed.Results. All point dose measurements were within 5% deviation. The mean gamma passing rates of the group data were found to be 96.8 ± 4.0% and 99.6 ± 0.7% with criteria of 2%/2mm and 3%/3mm, respectively. T95 of 87.4% and 98.2% was reported for the overall group with the two passing criteria, respectively. No statistically significant difference was found between adaptive treatments with adapt-to-position (ATP) and adapt-to-shape (ATS), whilst the category of pelvis data showed a better passing rate than other sites. Online QA gave a mean deviation of 0.2 ± 2.2%. The plan complexity metric was positively correlated with the mean dose difference whilst the complexity of the ATS cohort had larger variations than the ATP cohort.Conclusions. A patient-specific QA system based on ArcCHECK-MR, solid phantom and ionization chamber has been well established and implemented for validation of treatment delivery of a 1.5 T MR-Linac. Our QA data obtained over one year confirms that good agreement between TPS calculation and treatment delivery was achieved.

Cross-modality deep learning: Contouring of MRI data from annotated CT data only

PURPOSE

Online adaptive radiotherapy would greatly benefit from the development of reliable auto-segmentation algorithms for organs-at-risk and radiation targets. Current practice of manual segmentation is subjective and time-consuming. While deep learning-based algorithms offer ample opportunities to solve this problem, they typically require large datasets. However, medical imaging data are generally sparse, in particular annotated MR images for radiotherapy. In this study, we developed a method to exploit the wealth of publicly available, annotated CT images to generate synthetic MR images, which could then be used to train a convolutional neural network (CNN) to segment the parotid glands on MR images of head and neck cancer patients.

METHODS

Imaging data comprised 202 annotated CT and 27 annotated MR images. The unpaired CT and MR images were fed into a 2D CycleGAN network to generate synthetic MR images from the CT images. Annotations of axial slices of the synthetic images were generated by propagating the CT contours. These were then used to train a 2D CNN. We assessed the segmentation accuracy using the real MR images as test dataset. The accuracy was quantified with the 3D Dice similarity coefficient (DSC), Hausdorff distance (HD), and mean surface distance (MSD) between manual and auto-generated contours. We benchmarked the approach by a comparison to the interobserver variation determined for the real MR images, as well as to the accuracy when training the 2D CNN to segment the CT images.

RESULTS

The determined accuracy (DSC: 0.77±0.07, HD: 18.04±12.59mm, MSD: 2.51±1.47mm) was close to the interobserver variation (DSC: 0.84±0.06, HD: 10.85±5.74mm, MSD: 1.50±0.77mm), as well as to the accuracy when training the 2D CNN to segment the CT images (DSC: 0.81±0.07, HD: 13.00±7.61mm, MSD: 1.87±0.84mm).

CONCLUSIONS

The introduced cross-modality learning technique can be of great value for segmentation problems with sparse training data. We anticipate using this method with any nonannotated MRI dataset to generate annotated synthetic MR images of the same type via image style transfer from annotated CT images. Furthermore, as this technique allows for fast adaptation of annotated datasets from one imaging modality to another, it could prove useful for translating between large varieties of MRI contrasts due to differences in imaging protocols within and between institutions.

DeepDose: a robust deep learning-based dose engine for abdominal tumours in a 1.5 T MRI radiotherapy system

We present a robust deep learning-based framework for dose calculations of abdominal tumours in a 1.5 T MRI radiotherapy system. For a set of patient plans, a convolutional neural network is trained on the dose of individual multi-leaf-collimator segments following the DeepDose framework. It can then be used to predict the dose distribution per segment for a set of patient anatomies. The network was trained using data from three anatomical sites of the abdomen: prostate, rectal and oligometastatic tumours. A total of 216 patient fractions were used, previously treated in our clinic with fixed-beam IMRT using the Elekta MR-linac. For the purpose of training, 176 fractions were used with random gantry angles assigned to each segment, while 20 fractions were used for the validation of the network. The ground truth data were calculated with a Monte Carlo dose engine at 1% statistical uncertainty per segment. For a total of 20 independent abdominal test fractions with the clinical angles, the network was able to accurately predict the dose distributions, achieving 99.4% ± 0.6% for the whole plan prediction at the 3%/3 mm gamma test. The average dose difference and standard deviation per segment was 0.3% ± 0.7%. Additional dose prediction on one cervical and one pancreatic case yielded high dose agreement of 99.9% and 99.8% respectively for the 3%/3 mm criterion. Overall, we show that our deep learning-based dose engine calculates highly accurate dose distributions for a variety of abdominal tumour sites treated on the MR-linac, in terms of performance and generality.

Automatic dosimetric verification of online adapted plans on the Unity MR-Linac using 3D EPID dosimetry

BACKGROUND AND PURPOSE

The Unity MR-Linac is equipped with an EPID, the images from which contain information about the dose delivered to the patient. The purpose of this study was to introduce a framework for the automatic dosimetric verification of online adapted plans using 3D EPID dosimetry and to present the obtained dosimetric results.

MATERIALS AND METHODS

The framework was active during the delivery of 1207 online adapted plans corresponding to 127 clinical IMRT treatments (74 prostate, 19 rectum, 19 liver and 15 lymph node oligometastases). EPID reconstructed dose distributions in the patient geometry were calculated automatically and then compared to the dose distributions calculated online by the treatment planning system (TPS). The comparison was performed by γ-analysis (3% global/2mm/10% threshold) and by the difference in median dose to the high-dose volume (ΔHDV_D50). 85% for γ-pass rate and 5% for ΔHDV_D50 were used as tolerance limit values.

RESULTS

93% of the online plans were verified automatically by the framework. Missing EPID data was the reason for automation failure. 91% of the verified plans were within tolerance.

CONCLUSION

Automatic dosimetric verification of online adapted plans on the Unity MR-Linac is feasible using in vivo 3D EPID dosimetry. Almost all online adapted plans were approved automatically by the framework. This newly developed framework is a major step forward towards the clinical implementation of a permanent safety net for the entire online adaptive workflow.

Longitudinal acquisition repeatability of MRI radiomics features: An ACR MRI phantom study on two MRI scanners using a 3D T1W TSE sequence

PURPOSE

The purpose of this study was to quantitatively assess the longitudinal acquisition repeatability of MRI radiomics features in a three-dimensional (3D) T1-weighted (T1W) TSE sequence via a well-controlled prospective phantom study.

METHODS

Thirty consecutive daily datasets of an ACR-MRI phantom were acquired on two 1.5T MRI simulators using a 3D T1W TSE sequence. Images were blindly segmented by two observers. Post-acquisition processing was minimized but an intensity discretization (fixed bin size of 25). One hundred and one radiomics features (shape n = 12; first order n = 16; texture n = 73) were extracted. Longitudinal repeatability of each feature was evaluated by Pearson correlation and coefficient of variance (CV_68% ). Interobserver feature value agreement was also quantified using intraclass correlation coefficient (ICC) and Bland-Altman analysis. A most repeatable radiomics feature set on both scanners was determined by feature coefficient of variance (CV_68% <5%), ICC (>0.75), and the ratio of the interobserver difference to the interobserver mean δ<5%.

RESULTS

No trend of radiomics feature value changed with time. Longitudinal feature repeatability CV_68% ranged 0.01-38.60% (mean/median: 12.5%/9.9%), and 0.01-40.47%, (8.49%/7.34%) on the scanners A and B. Shape features exhibited significantly better repeatability than first-order and texture features (all P < 0.01). Significant longitudinal repeatability difference was observed in texture features (P < 0.001) between the two scanners, but not in shape and first-order features (P > 0.30). First-order and texture features had smaller interobserver-dependent variation than acquisition-dependent variation. They also showed good interobserver agreement on both scanners (A:ICC = 0.80 ± 0.23; B:ICC = 0.80 ± 0.22), independent of acquisition repeatability. The repeatable radiomics features in common on both scanners, including 12 shape features, 0 first-order features, and 3 texture features, were determined as the most repeatable MRI radiomics feature set.

CONCLUSIONS

Radiomics features exhibited heterogeneous longitudinal repeatability, while the shape features were the most repeatable, in this phantom study with a 3D T1W TSE acquisition. The most repeatable radiomics feature set derived in this study should be helpful for the selection of reliable radiomics features in the future clinical use.

Comparison of Intensity Modulated Radiotherapy Treatment Plans Between 1.5T MR-Linac and Conventional Linac

In this study, we assess the dosimetric qualities and usability of planning for 1.5 T MR-Linac based intensity modulated radiotherapy (MRL-IMRT) for various clinical sites in comparison with IMRT plans using a conventional linac. In total of 30 patients with disease sites in the brain, esophagus, lung, rectum and vertebra were re-planned retrospectively for simulated MRL-IMRT using the Elekta Unity dedicated treatment planning system (TPS) Monaco (v5.40.01). Currently, the step-and-shoot (ss) is the only delivery technique for IMRT available on Unity. All patients were treated on an Elekta Versa HD^TM with IMRT using the dynamic multileaf collimator (dMLC) technique, and the plans were designed using Monaco v5.11. For comparison, the same dMLC-IMRT plan was recalculated with the same machine and TPS but only changing the technique to step-and-shoot. The dosimetric qualities of the MRL-IMRT plans, to be evaluated by the Dose Volume Histograms (DVH) metrics, Homogeneity Index and Conformality Index, were compared with the clinical plans. The planning usability was measured by the optimization time and the number of Monitor Units (MUs). Comparing MRL-IMRT with conventional linac based plans, all created plans were clinically equivalent to current clinical practice. However, MRL-IMRT plans had higher dose to skin and larger low dose region of normal tissues. Furthermore, MRL-IMRT plans had significantly reduced optimization time by comparing conventional linac based plans. The number of MUs of MRL-IMRT was increased by 23% compared with ss-IMRT, and no difference from dMLC-IMRT. In conclusion, clinically acceptable plans can be achieved with 1.5 T MR-Linac system for multiple tumor sites. Given the differences in machine characteristics, some minor differences in plan quality were found between MR-Linac plans and current clinical practice and this should be considered in clinical practice.

Synthetic computed tomography data allows for accurate absorbed dose calculations in a magnetic resonance imaging only workflow for head and neck radiotherapy

•

The geometry of the synthetic CT is comparable to the CT in the H&N region.

•

Synthetic CT in the H&N region provides similar absorbed dose calculation as the CT.

•

Absorbed dose calculations in the dental region could benefit from using synthetic CT.

Background and purpose

Few studies on magnetic resonance imaging (MRI) only head and neck radiation treatment planning exist, and none using a generally available software. The aim of this study was to evaluate the accuracy of absorbed dose for head and neck synthetic computed tomography data (sCT) generated by a commercial convolutional neural network-based algorithm.

Materials and methods

For 44 head and neck cancer patients, sCT were generated and the geometry was validated against computed tomography data (CT). The clinical CT based treatment plan was transferred to the sCT and recalculated without re-optimization, and differences in relative absorbed dose were determined for dose-volume-histogram (DVH) parameters and the 3D volume.

Results

For overall body, the results of the geometric validation were (Mean ± 1sd): Mean error −5 ± 10 HU, mean absolute error 67 ± 14 HU, Dice similarity coefficient 0.98 ± 0.05, and Hausdorff distance difference 4.2 ± 1.7 mm. Water equivalent depth difference for region Th1-C7, mid mandible and mid nose were −0.3 ± 3.4, 1.1 ± 2.0 and 0.7 ± 3.8 mm respectively. The maximum mean deviation in absorbed dose for all DVH parameters was 0.30% (0.12 Gy). The absorbed doses were considered equivalent (p-value < 0.001) and the mean 3D gamma passing rate was 99.4 (range: 95.7–99.9%).

Conclusions

The convolutional neural network-based algorithm generates sCT which allows for accurate absorbed dose calculations for MRI-only head and neck radiation treatment planning. The sCT allows for statistically equivalent absorbed dose calculations compared to CT based radiotherapy.