One-year clinical outcomes of MR-guided stereotactic body radiation therapy with rectal spacer for patients with localized prostate cancer.

BACKGROUND AND PURPOSE: This prospective study aimed to investigate adaptive magnetic resonance (MR)-guided stereotactic body radiation therapy (MRgSBRT) with rectal spacer for localized prostate cancer (PC) and report 1-year clinical outcomes. MATERIALS AND METHODS: Thirty-four consecutive patients with low- to high-risk localized PC that underwent 5-fraction adaptive MRgSBRT with rectal spacer were enrolled. The dosimetric comparison was performed on a risk- and age-matched cohort treated with MRgSBRT but without a spacer at a similar timepoint. Clinician-reported outcomes were based on Common Terminology Criteria for Adverse Events. Patient-reported outcomes were based on the Expanded Prostate Cancer Index Composite (EPIC) questionnaire at baseline, acute (1-3 months), subacute (4-12 months), and late (> 12 months) phases. RESULTS: The median follow-up was 390 days (range 28-823) and the median age was 70 years (range 58-82). One patient experienced rectal bleeding soon after spacer insertion that subsided before MRgSBRT. The median distance between the midline of the prostate midgland and the rectum after spacer insertion measured 7.8 mm (range 2.6-15.3), and the median length of the spacer was 45.9 mm (range 16.8-62.9) based on T2-weighted MR imaging. The use of spacer resulted in significant improvements in target coverage (V100% > 95% = 98.6% [range 93.4-99.8] for spacer vs. 97.8% [range 69.6-99.7] for non-spacer) and rectal sparing (V95% < 3 cc = 0.7 cc [range 0-4.6] for spacer vs. 4.9 cc [range 0-12.5] for non-spacer). Nine patients (26.5%) experienced grade 1 gastrointestinal toxicities, and no grade ≥ 2 toxicities were observed. During the 1-year follow-up period, EPIC scores for the bowel domain remained stable and were the highest among all other domains. CONCLUSIONS: MRgSBRT with rectal spacer for localized PC showed exceptional tolerability with minimal gastrointestinal toxicities and satisfactory patient-reported outcomes. Improvements in dosimetry, rectal sparing, and target coverage were achieved with a rectal spacer. Randomized trials are warranted for further validation.

A study of Bayesian deep network uncertainty and its application to synthetic CT generation for MR-only radiotherapy treatment planning.

BACKGROUND: The use of synthetic computed tomography (CT) for radiotherapy treatment planning has received considerable attention because of the absence of ionizing radiation and close spatial correspondence to source magnetic resonance (MR) images, which have excellent tissue contrast. However, in an MR-only environment, little effort has been made to examine the quality of synthetic CT images without using the original CT images. PURPOSE: To estimate synthetic CT quality without referring to original CT images, this study established the relationship between synthetic CT uncertainty and Bayesian uncertainty, and proposed a new Bayesian deep network for generating synthetic CT images and estimating synthetic CT uncertainty for MR-only radiotherapy treatment planning. METHODS AND MATERIALS: A novel deep Bayesian network was formulated using probabilistic network weights. Two mathematical expressions were proposed to quantify the Bayesian uncertainty of the network and synthetic CT uncertainty, which was closely related to the mean absolute error (MAE) in Hounsfield Unit (HU) of synthetic CT. These uncertainties were examined to demonstrate the accuracy of representing the synthetic CT uncertainty using a Bayesian counterpart. We developed a hybrid Bayesian architecture and a new data normalization scheme, enabling the Bayesian network to generate both accurate synthetic CT and reliable uncertainty information when probabilistic weights were applied. The proposed method was evaluated in 59 patients (13/12/32/2 for training/validation/testing/uncertainty visualization) diagnosed with prostate cancer, who underwent same-day pelvic CT- and MR-acquisitions. To assess the relationship between Bayesian and synthetic CT uncertainties, linear and non-linear correlation coefficients were calculated on per-voxel, per-tissue, and per-patient bases. For accessing the accuracy of the CT number and dosimetric accuracy, the proposed method was compared with a commercially available atlas-based method (MRCAT) and a U-Net conditional-generative adversarial network (UcGAN). RESULTS: The proposed model exhibited 44.33 MAE, outperforming UcGAN 52.51 and MRCAT 54.87. The gamma rate (2%/2 mm dose difference/distance to agreement) of the proposed model was 98.68%, comparable to that of UcGAN (98.60%) and MRCAT (98.56%). The per-patient and per-tissue linear correlation coefficients between the Bayesian and synthetic CT uncertainties ranged from 0.53 to 0.83, implying a moderate to strong linear correlation. Per-voxel correlation coefficients varied from -0.13 to 0.67 depending on the regions-of-interest evaluated, indicating tissue-dependent correlation. The R2 value for estimating MAE solely using Bayesian uncertainty was 0.98, suggesting that the uncertainty of the proposed model was an ideal candidate for predicting synthetic CT error, without referring to the original CT. CONCLUSION: This study established a relationship between the Bayesian model uncertainty and synthetic CT uncertainty. A novel Bayesian deep network was proposed to generate a synthetic CT and estimate its uncertainty. Various metrics were used to thoroughly examine the relationship between the uncertainties of the proposed Bayesian model and the generated synthetic CT. Compared with existing approaches, the proposed model showed comparable CT number and dosimetric accuracies. The experiments showed that the proposed Bayesian model was capable of producing accurate synthetic CT, and was an effective indicator of the uncertainty and error associated with synthetic CT in MR-only workflows.

Clinical implementation of kVCT-guided tomotherapy with ClearRT.

A helical fan-beam kilovoltage computed tomography (kVCT) was recently introduced into Tomotherapy units. This study aims to share the initial experience of kVCT in clinical workflow, compare its performance with that of the existing megavoltage computed tomography (MVCT), and explore its potential in adaptive planning. We retrospectively enrolled 23 patients who underwent both MVCT and kVCT scans. The clinical performance data regarding image acquisition time, nominal dose length product (DLP), registration time and registration corrections were extracted and compared. Image quality was scored by six experienced radiation therapists and quantified based on phantom measurements. CT number stability and the implementation of adaptive radiotherapy were dosimetrically evaluated by performing the dose recalculation on kVCT. Compared to MVCT, kVCT significantly reduced DLP (except the highest kVp protocol), image acquisition and registration time. KVCT obtained higher scores than MVCT on all criteria except artifacts. Phantom measurements also revealed a better image performance characterization of kVCT except for image uniformity. The CT number variation could lead to a dose difference of 0.5% for D95% of target and Dmean of organ-at-risk. For the treatment planning with kVCT, a systematic dose difference (> 1%) in PTV dose metrics was observed at regions with large longitudinal density discontinuities compared to the reference plans. The new kVCT imaging provides enhanced soft-tissue visualization. The improved efficiency with kVCT-guided treatment will allow more patients to be treated each day. In most cases, the dose calculation accuracy of kVCT images is acceptable except for regions with severe artifacts.

Out-of-field dose and its constituent components for a 1.5 T MR-Linac.

This study aims to quantify the relative contributions of phantom scatter, collimator scatter and head leakage to the out-of-field doses (OFDs) of both static fields and clinical intensity-modulated radiation therapy (IMRT) treatments in a 1.5 T MR-Linac. The OFDs of static fields were measured at increasing distances from the field edge in an MR-conditional water phantom. Inline scans at depths of dmax (14 mm), 50 and 100 mm were performed for static fields of 5 × 5, 10 × 10 and 15 × 15 cm2under three different conditions: full scatter, with phantom scatter prevented, and head leakage only. Crossline scans at isocenter and offset positions were performed in full scatter condition. EBT3 radiochromic films were placed at 100 mm depth of solid water phantom to measure the OFD of clinical IMRT plans. All water tank data were normalized to Dmax of a 10 × 10 cm2field and the film results were presented as a fraction of the target mean dose.The OFD in the inline direction varied from 3.5% (15 × 15 cm2, 100 mm depth, 50 mm distance) to 0.014% (5 × 5 cm2, dmax, 400 mm distance). For all static fields, the collimator scatter was higher than the phantom scatter and head leakage at a distance of 100-400 mm. Head leakage remained the smallest among the three components, except at long distances (>375 mm) with small field size. Compared to the inline scans, the crossline scans at the isocenter showed higher doses at distances longer than 80 mm. All crossline profiles at longitudinal offset positions showed a cone shape with laterally shifted maxima. The OFD of IMRT deliveries varied with different target size. For prostate stereotactic body radiation therapy (SBRT) treatment, the OFD decreased from 2% to 0.03% at a distance of 50-500 mm. The OFDs have been measured for a 1.5 T MR-Linac. The presented dosimetric data are valuable for radiation safety assessments on patients treated with the MR-Linac, such as evaluating carcinogenic risk and radiation exposure to cardiac implantable electronic devices.