Multiparametric MRI-guided dose boost to dominant intraprostatic lesions in CT-based High-dose-rate prostate brachytherapy

Viability of focal dose escalation to prostate cancer intraprostatic lesions using HDR prostate brachytherapy

PURPOSE

This study aimed to determine the viability of focal dose escalation to prostate cancer intraprostatic lesions (IPLs) from multiparametric magnetic resonance (mpMRI) and prostate-specific membrane antigen positron emission tomography (PSMA-PET) images using high-dose-rate (HDR) prostate brachytherapy (pBT).

METHODS AND MATERIALS

Retrospective data from 20 patients treated with HDR pBT was utilized. The interobserver contouring variability of 5 observers was quantified using the dice similarity coefficient (DSC) and mean distance to agreement (MDA). Uncertainty in propagating IPL contours to trans-rectal ultrasound (TRUS) was quantified using a tissue equivalent prostate phantom. Feasibility of incorporating IPLs into HDR pBT planning was tested on retrospective patient data.

RESULTS

The average observer DSC was 0.65 (PSMA-PET) and 0.52 (mpMRI). The uncertainty in propagating IPL contours was 0.6 mm (PSMA-PET), and 0.4 mm (mpMRI). Uncertainties could be accounted for by expanding IPL contours by 2 mm to create IPL PTVs. The mean D98% achieved using HDR pBT was 166% and 135% for the IPL and IPL PTV contours, respectively.

CONCLUSIONS

Focal dose escalation to IPLs identified on either PSMA-PET or mpMRI is viable using TRUS-based HDR pBT. Utilizing HDR pBT allows dose escalation of up to 166% of the prescribed dose to the prostate.

Dose differentiated high-dose-rate prostate brachytherapy: a feasibility assessment of MRI-guided dose escalation to dominant intra-prostatic lesions

PURPOSE

Prostate brachytherapy is routinely performed with trans-rectal ultrasound (TRUS)- or computed tomography (CT)-based planning that cannot delineate dominant intra-prostatic lesions (DILs). In contrast, magnetic resonance imaging (MRI)-based planning allows for more accurate DIL delineation and dose escalation. This study assessed the maximum achievable dose escalation to DILs.

MATERIAL AND METHODS

We retrospectively identified 24 patients treated with high-dose-rate (HDR) prostate brachytherapy boost (15 Gy in 1 fraction). All patients had a pre-treatment prostate MRI with 1-3 DILs. MRIs were used to delineate DILs and were co-registered to TRUS intra-procedure. Treatment plans were experimentally re-optimized to escalate DIL dose. Dosimetric indices from the original and re-optimized plans were compared using two-tailed paired t-test. Re-optimized plans were deemed acceptable if they achieved all of the following criteria: prostate D90 > 100%, prostate V100 > 90%, urethra D10 < 118%, rectum V80 < 0.5 cc, bladder D1cc < 75%, or if they did not exceed organs at risk (OARs) doses of the original plan.

RESULTS

The mean DIL D90 was significantly increased from 134% of the prescription dose on the original plans to 154% on the re-optimized plans. The mean urethra D10 and mean bladder D1cc were significantly reduced from 123% to 117% and from 72% to 65%, respectively. Prostate D90 was reduced from 106% to 102%, and prostate V100 was reduced from 93% to 91%.

CONCLUSIONS

We re-optimized HDR brachytherapy plans to escalate DILs dose to a mean D90 of > 150% while maintaining favorable prostate coverage and OARs doses. We propose DIL D90 dose of > 150% (22.5 Gy) as an achievable goal.

Breathing-induced Errors in Quantification and Description of Dominant Intra-Prostatic Lesions (Dils) in PET Images: A Simulation Study by Means of The 4D NCAT Phantom

BACKGROUND

Respiratory movement and the motion range of the diaphragm can affect the quality and quantity of prostate images.

OBJECTIVE

This study aimed to investigate the magnitude of respiratory-induced errors to determine Dominant Intra- prostatic Lesions (DILs) in positron emission tomography (PET) images.

MATERIAL AND METHODS

In this simulation study, we employed the 4D NURBS-based cardiac-torso (4D-NCAT) phantom with a realistic breathing model to simulate the respiratory cycles of a patient to assess the displacement, volume, maximum standardized uptake value (SUV_max), mean standardized uptake value (SUV_mean), signal to noise ratio (SNR), and the contrast of DILs in frames within the respiratory cycle.

RESULTS

Respiration in a diaphragm motion resulted in the maximum superior-inferior displacement of 3.9 and 6.1 mm, and the diaphragm motion amplitudes of 20 and 35 mm. In a no-motion image, the volume measurement of DILs had the smallest percentage of errors. Compared with the no-motion method, the percentages of errors in the average method in 20 and 35 mm- diaphragm motion were 25% and 105%, respectively. The motion effect was significantly reduced in terms of the values of SUV_max and SUV_mean in comparison with the values of SUV_max and SUV_mean in no- motion images. The contrast values in respiratory cycle frames were at a range of 3.3-19.2 mm and 6.5-46 for diaphragm movements' amplitudes of 20 and 35 mm.

CONCLUSION

The respiratory movement errors in quantification and delineation of DILs were highly dependent on the range of motion, while the average method was not suitable to precisely delineate DILs in PET/CT in the dose-painting technique.

Evaluation of Dose-Painting in the Dominant Intraprostatic Lesions by Radiobiological Parameters using 68Ga- PSMA PET/CT

BACKGROUND

Patients diagnosed with dominant intraprostatic lesions (DIL) may need radiation doses over than 80 Gy. Dose-painting by contours (DPC) is a useful technique which helps the patients. Dose-painting approach need to be evaluated.

OBJECTIVE

To evaluate the DCP technique in the case of boosting the DILs by radiobiological parameters, tumor control probability (TCP), and normal tissue complication probability (NTCP) via PET/CT images traced by ⁶⁸Ga-PSMA.

MATERIAL AND METHODS

In this analytical study, ⁶⁸Ga-PSMA PET/CT images were obtained from patients with DILs that were delineated using the Fuzzy c-mean (FCM) algorithm and thresholding methods. The protocol of therapy included two phases; at the first phase (ph1), a total dose of 72 Gy in 36 fractions were delivered to the planning target volume (PTV1); the seconds phase consisted of the application of variable doses to the PTV2. Moreover, two concepts were also considered to calculate the TCP using the Zaider-Minerbo model.

RESULTS

The lowest volume in DILs belonged to the DIL1 extracted by the FCM method. According to dose-volume parameters of the rectum and bladder, by the increase in the PTV dose higher than 92 Gy, the amounts of rectum and bladder doses are increased. There was no difference between the TCPs of DILs at doses higher than 86 Gy and 100 Gy for ordinary and high clone density, respectively.

CONCLUSION

Consequently, our dose-painting approach for DILs, extracted by the FCM method via PET/CT images, can reduce the total dose for prostate radiation with 100% tumor control and less normal tissue complications.

MRI-based prostate and dominant lesion segmentation using cascaded scoring convolutional neural network

PURPOSE

Dose escalation to dominant intraprostatic lesions (DILs) is a novel treatment strategy to improve the treatment outcome of prostate radiation therapy. Treatment planning requires accurate and fast delineation of the prostate and DILs. In this study, a 3D cascaded scoring convolutional neural network is proposed to automatically segment the prostate and DILs from MRI.

METHODS AND MATERIALS

The proposed cascaded scoring convolutional neural network performs end-to-end segmentation by locating a region-of-interest (ROI), identifying the object within the ROI, and defining the target. A scoring strategy, which is learned to judge the segmentation quality of DIL, is integrated into cascaded convolutional neural network to solve the challenge of segmenting the irregular shapes of the DIL. To evaluate the proposed method, 77 patients who underwent MRI and PET/CT were retrospectively investigated. The prostate and DIL ground truth contours were delineated by experienced radiologists. The proposed method was evaluated with five-fold cross validation and holdout testing.

RESULTS

The average centroid distance, volume difference, and Dice similarity coefficient (DSC) value for prostate/DIL are 4.3±7.5mm/3.73±3.78mm, 4.5±7.9cc/0.41±0.59cc and 89.6±8.9%/84.3±11.9%, respectively. Comparable results were obtained in the holdout test. Similar or superior segmentation outcomes were seen when compared the results of the proposed method to those of competing segmentation approaches CONCLUSIONS: : The proposed automatic segmentation method can accurately and simultaneously segment both the prostate and DILs. The intended future use for this algorithm is focal boost prostate radiation therapy. This article is protected by copyright. All rights reserved.

Targeting prostate lesions on multiparametric MRI with HDR brachytherapy: Optimal planning margins determined using whole-mount digital histology

PURPOSE

Multiparametric magnetic resonance imaging (mpMRI) has demonstrated the ability to localize intraprostatic lesions. It is our goal to determine how to optimally target the underlying histopathological cancer within the setting of high-dose-rate brachytherapy (HDR-BT).

METHODS AND MATERIALS

Ten prostatectomy patients had pathologist-annotated mid-gland histology registered to pre-procedural mpMRI, which were interpreted by four different observers. Simulated HDR-BT plans with realistic catheter placements were generated by registering the mpMRI lesions and corresponding histology annotations to previously performed clinical HDR-BT implants. Inverse treatment planning was used to generate treatment plans that treated the entire gland to a single dose of 15 Gy, as well as focally targeted plans that aimed to escalate dose to the mpMRI lesions to 20.25 Gy. Three margins to the lesion were explored: 0 mm, 1 mm, and 2 mm. The analysis compared the dose that would have been delivered to the corresponding histologically-defined cancer with the different treatment planning techniques.

RESULTS

mpMRI-targeted plans delivered a significantly higher dose to the histologically-defined cancer (p < 0.001), in comparison to the standard treatment plans. Additionally, adding a 1 mm margin resulted in significantly higher D98, and D90 to the histologically-defined cancer in comparison to the 0 mm margin targeted plans (p = 0.019 & p = 0.0026). There was no significant difference between plans using 1 mm and 2 mm margins.

CONCLUSIONS

Adding a 1 mm margin to intraprostatic mpMRI lesions significantly increased the dose to histologically-defined cancer, in comparison applying no margin. No significant effect was observed by further expanding the margins.

Intensity Modulated High Dose Rate (HDR) Brachytherapy Using Patient Specific 3D Metal Printed Applicators: Proof of Concept

Purpose

In high-dose-rate (HDR) brachytherapy, an anisotropic dose distribution may be desirable for achieving a higher therapeutic index, particularly when the anatomy imposes challenges. Several methods to deliver intensity-modulated brachytherapy (IMBT) have been proposed in the literature, however practical implementation is lacking due to issues of increased delivery times and complicated delivery mechanisms. This study presents the novel approach of designing a patient-specific inner shape of an applicator with 3D metal printing for IMBT using an inverse plan optimization model.

Methods

The 3D printed patient-specific HDR applicator has an external shape that resembles the conventional brachytherapy applicator. However, at each dwell position of the HDR source, the shielding walls in the interior are divided into six equiangular sections with varying thicknesses. We developed a mathematical model to simultaneously optimize the shielding thicknesses and dwell times according to the patient’s anatomical information to achieve the best possible target coverage. The model, which is a bi-convex optimization problem, is solved using alternating minimization. Finally, the applicator design parameters were input into 3D modeling software and saved in a 3D printable file. The applicator has been tested with both a digital phantom and a simulated clinical cervical cancer patient.

Results

The proposed approach showed substantial improvements in the target coverage over the conventional method. For the phantom case, 99.18% of the target was covered by the prescribed dose using the proposed method, compared to only 58.32% coverage achieved by the conventional method. For the clinical case, the proposed method increased the coverage of the target from 56.21% to 99.92%. In each case, both methods satisfied the treatment constraints for neighboring OARs.

Conclusion

The study simulates the concept of the IMBT with inverse planning using the 3D printed applicator design. The non-isotropic dose map can be produced with optimized shielding patterns and tailored to individual patient’s anatomy, to plan a more conformal plan.

Prostate and dominant intraprostatic lesion segmentation on PET/CT using cascaded regional-net

Focal boost to dominant intraprostatic lesions (DILs) has recently been proposed for prostate radiation therapy. Accurate and fast delineation of the prostate and DILs is thus required during treatment planning. In this paper, we develop a learning-based method using positron emission tomography (PET)/computed tomography (CT) images to automatically segment the prostate and its DILs. To enable end-to-end segmentation, a deep learning-based method, called cascaded regional-Net, is utilized. The first network, referred to as dual attention network, is used to segment the prostate via extracting comprehensive features from both PET and CT images. A second network, referred to as mask scoring regional convolutional neural network (MSR-CNN), is used to segment the DILs from the PET and CT within the prostate region. Scoring strategy is used to diminish the misclassification of the DILs. For DIL segmentation, the proposed cascaded regional-Net uses two steps to remove normal tissue regions, with the first step cropping images based on prostate segmentation and the second step using MSR-CNN to further locate the DILs. The binary masks of DILs and prostates of testing patients are generated on the PET/CT images by the trained model. For evaluation, we retrospectively investigated 49 prostate cancer patients with PET/CT images acquired. The prostate and DILs of each patient were contoured by radiation oncologists and set as the ground truths and targets. We used five-fold cross-validation and a hold-out test to train and evaluate our method. The mean surface distance and DSC values were 0.666 ± 0.696 mm and 0.932 ± 0.059 for the prostate and 0.814 ± 1.002 mm and 0.801 ± 0.178 for the DILs among all 49 patients. The proposed method has shown promise for facilitating prostate and DIL delineation for DIL focal boost prostate radiation therapy.

Dosimetric Uncertainties in Dominant Intraprostatic Lesion Simultaneous Boost Using Intensity Modulated Proton Therapy

Purpose

While intensity modulated proton therapy can deliver simultaneous integrated boost (SIB) to the dominant intraprostatic lesion (DIL) with high precision, it is sensitive to anatomic changes. We investigated the dosimetric effects from these changes based on pretreatment cone-beam computed tomographic (CBCT) images and identified the most important factors using a multilayer perceptron neural network (MLPNN).

Methods and Materials

DILs were contoured based on coregistered multiparametric magnetic resonance images for 25 previously treated prostate cancer patients. SIB plans were created with (1) prostate clinical target volume − V70 Gy = 98%; (2) DIL − V98 Gy > 95%; and (3) all organs at risk (OARs)"?> within clinical constraints. SIB plans were applied to daily CBCT-based deformed planning computed tomography (CT)"?>. DIL − V98 Gy, bladder/rectum maximum dose (Dmax) and volume changes, femur shifts, and the distance from DIL to organs at riskOARs"?> in both planning computed tomogramsCT"?> and CBCT were calculated. Wilcoxon signed-ranks tests were used to compare the changes. MLPNNs were used to model the change in ΔDIL − V98 Gy > 10% and bladder/rectum Dmax > 80 Gy, and the relative importance factors for the model were provided. The performances of the models were evaluated with receiver operating characteristic curves.

Results

Comparing initial plan to the average from evaluation plans, respectively, DIL − V98 Gy was 89.3% ± 19.9% versus 86.2% ± 21.3% (P = .151); bladder Dmax 71.9 ± 0.6 Gy versus 74.5 ± 2.9 Gy (P < .001); and rectum Dmax 70.1 ± 2.4 Gy versus 74.9 ± 9.1Gy (P = .007). Bladder and rectal volumes were 99.6% ± 39.5% and 112.8% ± 27.2%, respectively, of their initial volume. The femur shift was 3.16 ± 2.52 mm. In the modeling of ΔDIL V98 Gy > 10%, DIL to rectum distance changes, DIL to bladder distance changes, and rectum volume changes ratio are the 3 most important factors. The areas under the receiver operating characteristic curves were 0.89, 1.00, and 0.99 for the modeling of ΔDIL − V98 Gy > 10%, and bladder and rectum Dmax > 80 Gy, respectively.

Conclusions

Dosimetric changes in DIL SIB with intensity modulated proton therapy can be modeled and classified based on anatomic changes on pretreatment images by an MLPNN.

Prostate specific membrane antigen positron emission tomography for lesion-directed high-dose-rate brachytherapy dose escalation

•

This paper evaluated lesion-directed prostatic high dose rate brachytherapy.

•

Lesions defined by prostate specific membrane antigen positron emission tomography.

•

Dose escalation was confirmed using whole-mount digital histology.

•

Targeting lesions led to significantly higher dose to high-grade histologic cancer.

Background and purpose

Prostate specific membrane antigen positron emission tomography imaging (PSMA-PET) has demonstrated potential for intra-prostatic lesion localization. We leveraged our existing database of co-registered PSMA-PET imaging with cross sectional digitized pathology to model dose coverage of histologically-defined prostate cancer when tailoring brachytherapy dose escalation based on PSMA-PET imaging.

Materials and methods

Using a previously-developed automated approach, we created segmentation volumes delineating underlying dominant intraprostatic lesions for ten men with co-registered pathology-imaging datasets. To simulate realistic high-dose-rate brachytherapy (HDR-BT) treatments, we registered the PSMA-PET-defined segmentation volumes and underlying cancer to 3D trans-rectal ultrasound images of HDR-BT cases where 15 Gray (Gy) was delivered. We applied dose/volume optimization to focally target the dominant intraprostatic lesion identified on PSMA-PET. We then compared histopathology dose for all high-grade cancer within whole-gland treatment plans versus PSMA-PET-targeted plans. Histopathology dose was analyzed for all clinically significant cancer with a Gleason score of 7or greater.

Results

The standard whole-gland plans achieved a median [interquartile range] D98 of 15.2 [13.8–16.4] Gy to the histologically-defined cancer, while the targeted plans achieved a significantly higher D98 of 16.5 [15.0–19.0] Gy (p = 0.007).

Conclusion

This study is the first to use digital histology to confirm the effectiveness of PSMA-PET HDR-BT dose escalation using automatically generated contours. Based on the findings of this study, PSMA-PET lesion dose escalation can lead to increased dose to the ground truth histologically defined cancer.

Catheter position prediction using deep-learning-based multi-atlas registration for high-dose rate prostate brachytherapy

PURPOSE

High-dose-rate (HDR) prostate brachytherapy involves treatment catheter placement, which is currently empirical and physician dependent. The lack of proper catheter placement guidance during the procedure has left the physicians to rely on a heuristic thinking-while-doing technique, which may cause large catheter placement variation and increased plan quality uncertainty. Therefore, the achievable dose distribution could not be quantified prior to the catheter placement. To overcome this challenge, we proposed a learning-based method to provide HDR catheter placement guidance for prostate cancer patients undergoing HDR brachytherapy.

METHODS

The proposed framework consists of deformable registration via registration network (Reg-Net), multi-atlas ranking, and catheter regression. To model the global spatial relationship among multiple organs, binary masks of the prostate and organs-at-risk are transformed into distance maps, which describe the distance of each local voxel to the organ surfaces. For a new patient, the generated distance map is used as fixed image. Reg-Net is utilized to deformably register the distance maps from multi-atlas set to match this patient's distance map and then bring catheter maps from multi-atlas to this patient via spatial transformation. Several criteria, namely prostate volume similarity, multi-organ semantic image similarity, and catheter position criteria (far from the urethra and within the partial prostate), are used for multi-atlas ranking. The top-ranked atlas' deformed catheter positions are selected as the predicted catheter positions for this patient. Finally, catheter regression is used to refine the final catheter positions. A retrospective study on 90 patients with a fivefold cross-validation scheme was used to evaluate the proposed method's feasibility. In order to investigate the impact of plan quality from the predicted catheter pattern, we optimized the source dwell position and time for both the clinical catheter pattern and predicted catheter pattern with the same optimization settings. Comparisons of clinically relevant dose volume histogram (DVH) metrics were completed.

RESULTS

For all patients, on average, both the clinical plan dose and predicted plan dose meet the common dose constraints when prostate dose coverage is kept at V100 = 95%. The plans from the predicted catheter pattern have slightly higher hotspot in terms of V150 by 5.0% and V200 by 2.9% on average. For bladder V75, rectum V75, and urethra V125, the average difference is close to zero, and the range of most patients is within ±1 cc.

CONCLUSION

We developed a new catheter placement prediction method for HDR prostate brachytherapy based on a deep-learning-based multi-atlas registration algorithm. It has great clinical potential since it can provide catheter location estimation prior to catheter placement, which could reduce the dependence on physicians' experience in catheter implantation and improve the quality of prostate HDR treatment plans. This approach merits further clinical evaluation and validation as a method of quality control for HDR prostate brachytherapy.

A multiobserver study investigating the effectiveness of prostatic multiparametric magnetic resonance imaging to dose escalate corresponding histologic lesions using high-dose-rate brachytherapy

PURPOSE

Using multiparametric MRI data and the pathologic data from radical prostatectomy specimens, we simulated the treatment planning of dose-escalated high-dose-rate brachytherapy (HDR-BT) to the Multiparametric MRI dominant intraprostatic lesion (mpMRI-DIL) to compare the dose potentially delivered to the pathologically confirmed locations of the high-grade component of the cancer.

METHODS AND MATERIALS

Pathologist-annotated prostatectomy midgland histology sections from 12 patients were registered to preprostatectomy mpMRI scans that were interpreted by four radiologists. To simulate realistic HDR-BT, we registered each observer's mpMRI-DILs and corresponding histology to two transrectal ultrasound images of other HDR-BT patients with a 15-Gy whole-gland prescription. We used clinical inverse planning to escalate the mpMRI-DILs to 20.25 Gy. We compared the dose that the histopathology would have received if treated with standard treatment plans to the dose mpMRI-targeting would have achieved. The histopathology was grouped as high-grade cancer (any Gleason Grade 4 or 5) and low-grade cancer (only Gleason Grade 3).

RESULTS

212 mpMRI-targeted HDR-BT plans were analyzed. For high-grade histology, the mpMRI-targeted plans achieved significantly higher median [IQR] D98 and D90 values of 18.2 [16.7-19.5] Gy and 19.4 [17.8-20.9] Gy, respectively, in comparison with the standard plans (p = 0.01 and p = 0.003). For low-grade histology, the targeted treatment plans would have resulted in a significantly higher median D90 of 17.0 [16.1-18.4] Gy in comparison with standard plans (p = 0.015); the median D98 was not significantly higher (p = 0.2).

CONCLUSIONS

In this retrospective pilot study of 12 patients, mpMRI-based dose escalation led to increased dose to high-grade, but not low-grade, cancer. In our data set, different observers and mpMRI sequences had no substantial effect on dose to histologic cancer.

HDR brachytherapy boost using MR-only workflow for intermediate- and high-risk prostate cancer: 8-year results of a pilot study

PURPOSE

To report 8-year clinical outcome with high-dose-rate brachytherapy (HDRBT) boost using MRI-only workflow for intermediate (IR) and high-risk (HR) prostate cancer (PC) patients.

METHODS AND MATERIALS

Fifty-two patients were treated with 46-60 Gy of 3D conformal radiotherapy preceded and/or followed by a single dose of 8-10 Gy MRI-guided HDRBT. Interventions were performed in a 0.35 T MRI scanner. Trajectory planning, navigation, contouring, catheter reconstruction, and dose calculation were exclusively based on MRI images. Biochemical relapse-free- (BRFS), local relapse-free- (LRFS), distant metastasis-free- (DMFS), cancer-specific-(CCS) and overall survival (OS) were analyzed. Late morbidity was scored using the Common Terminology Criteria for Adverse Events (CTCAE 4.0) combined with RTOG (Radiation Therapy Oncology Group) scale for urinary toxicity and rectal urgency (RU) determined by Yeoh.

RESULTS

Median follow-up time was 107 (range: 19-143) months. The 8-year actuarial rates of BRFS, LRFS, DMFS, CSS and OS were 85.7%, 97%, 97.6%, and 77.6%, respectively. There were no Gr.3 GI side effects. The 8-year actuarial rate of Gr.2 proctitis was 4%. The 8-year cumulative incidence of Gr.3 GU side effects was 8%, including two urinary stenoses (5%) and one cystitis (3%). EPIC urinary and bowel scores did not change significantly over time.

CONCLUSIONS

MRI-only HDR-BT boost with moderate dose escalation provides excellent 8-year disease control with a favorable toxicity profile for IRPC and HRPC patients. Our results support the clinical importance of MRI across the BT workflow.

Multimodal MRI synthesis using unified generative adversarial networks

PURPOSE

Complementary information obtained from multiple contrasts of tissue facilitates physicians assessing, diagnosing and planning treatment of a variety of diseases. However, acquiring multiple contrasts magnetic resonance images (MRI) for every patient using multiple pulse sequences is time-consuming and expensive, where, medical image synthesis has been demonstrated as an effective alternative. The purpose of this study is to develop a unified framework for multimodal MR image synthesis.

METHODS

A unified generative adversarial network consisting of only a single generator and a single discriminator was developed to learn the mappings among images of four different modalities. The generator took an image and its modality label as inputs and learned to synthesize the image in the target modality, while the discriminator was trained to distinguish between real and synthesized images and classify them to their corresponding modalities. The network was trained and tested using multimodal brain MRI consisting of four different contrasts which are T1-weighted (T1), T1-weighted and contrast-enhanced (T1c), T2-weighted (T2), and fluid-attenuated inversion recovery (Flair). Quantitative assessments of our proposed method were made through computing normalized mean absolute error (NMAE), peak signal-to-noise ratio (PSNR), structural similarity index measurement (SSIM), visual information fidelity (VIF), and naturalness image quality evaluator (NIQE).

RESULTS

The proposed model was trained and tested on a cohort of 274 glioma patients with well-aligned multi-types of MRI scans. After the model was trained, tests were conducted by using each of T1, T1c, T2, Flair as a single input modality to generate its respective rest modalities. Our proposed method shows high accuracy and robustness for image synthesis with arbitrary MRI modality that is available in the database as input. For example, with T1 as input modality, the NMAEs for the generated T1c, T2, Flair respectively are 0.034 ± 0.005, 0.041 ± 0.006, and 0.041 ± 0.006, the PSNRs respectively are 32.353 ± 2.525 dB, 30.016 ± 2.577 dB, and 29.091 ± 2.795 dB, the SSIMs are 0.974 ± 0.059, 0.969 ± 0.059, and 0.959 ± 0.059, the VIF are 0.750 ± 0.087, 0.706 ± 0.097, and 0.654 ± 0.062, and NIQE are 1.396 ± 0.401, 1.511 ± 0.460, and 1.259 ± 0.358, respectively.

CONCLUSIONS

We proposed a novel multimodal MR image synthesis method based on a unified generative adversarial network. The network takes an image and its modality label as inputs and synthesizes multimodal images in a single forward pass. The results demonstrate that the proposed method is able to accurately synthesize multimodal MR images from a single MR image.

Modern development of high-dose-rate brachytherapy

Brachytherapy is an invasive therapy with placement of radiation source into or near the tumor. The difference between planning target volume and clinical target volume is minimal, and the dose out of the tumor reduces rapidly due to the inverse-square law. High-dose-rate brachytherapy enables three-dimensional image guidance, and currently, tumor dose as well as doses of the surrounding normal structures can be evaluated accurately. High-dose-rate brachytherapy is the utmost precision radiation therapy even surpassing carbon ion therapy. Biological disadvantages of high-dose rate have been overcome by the fractional irradiation. High-dose-rate brachytherapy is indispensable in the definitive radiation therapy of cervical cancer. Also in prostate cancer and breast cancer, high-dose-rate brachytherapy plays a significant role. Brachytherapy requires techniques and skills of radiation oncologists at the time of invasive placement of the radiation source into the tumor area. Education of young radiation oncologists is most urgent and important.

Impact of suboptimal dosimetric coverage of pretherapeutic 18F-FDG PET/CT hotspots on outcome in patients with locally advanced cervical cancer treated with chemoradiotherapy followed by brachytherapy

INTRODUCTION

Areas of high uptake on pre-treatment 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET/CT), denoted as "hotspots", have been identified as preferential sites of local relapse in locally advanced cervical cancer (LACC). The purpose of this study was to analyze the dosimetric coverage of these hotspots with high dose-rate brachytherapy (BT).

METHODS

For each patient, a rigid registration of the CT from the pre-treatment PET/CT with the radiotherapy planning CT was performed using 3D SlicerTM, followed by a manual volume correction by translation and deformation if necessary. The fuzzy locally adaptive Bayesian (FLAB) algorithm was applied to PET images to simultaneously define an overall tumour volume and the high-uptake sub-volume V1. The inclusion of V1 in the high-risk clinical target volume (CTV HR) and its dosimetric coverage were evaluated using 3D SlicerTM. The average of the 3-4 BT sessions was reported.

RESULTS

Forty-two patients with recurrence after chemoradiotherapy (CRT) for LACC were matched to 42 patients without recurrence. Mean ± standard deviation follow-up was 26 ± 11 months. In the recurrence group, V1 was not included in the CTV HR and not covered by the 85 Gy isodose in 17/42 patients (41%) (1/20 with pelvic recurrence and 16/22 with distant recurrence) and not by the 80 Gy isodose in 7/42 patients (17%) (all with distant recurrence). In the non-recurrence group, V1 was not included in CTV HR and not covered by the 85 Gy isodose in 3 patients only (7%). The hotspots coverage by the 85 Gy isodose was significantly better in patients who did not recur, but only when compared to patients with distant relapse (p < 0.0001).

CONCLUSION

Suboptimal dosimetric coverage of high FDG uptakes on pretherapeutic PET could be associated with an increased risk of recurrence.

Multi-needle Localization with Attention U-Net in US-guided HDR Prostate Brachytherapy

PURPOSE

Ultrasound (US)-guided high dose rate (HDR) prostate brachytherapy requests the clinicians to place HDR needles (catheters) into the prostate gland under transrectal US (TRUS) guidance in the operating room. The quality of the subsequent radiation treatment plan is largely dictated by the needle placements, which varies upon the experience level of the clinicians and the procedure protocols. Real-time plan dose distribution, if available, could be a vital tool to provide more subjective assessment of the needle placements, hence potentially improving the radiation plan quality and the treatment outcome. However, due to low signal-to-noise ratio (SNR) in US imaging, real-time multi-needle segmentation in 3D TRUS, which is the major obstacle for real-time dose mapping, has not been realized to date. In this study, we propose a deep learning-based method that enables accurate and real-time digitization of the multiple needles in the 3D TRUS images of HDR prostate brachytherapy.

METHODS

A deep learning model based on the U-Net architecture was developed to segment multiple needles in the 3D TRUS images. Attention gates were considered in our model to improve the prediction on the small needle points. Furthermore, the spatial continuity of needles was encoded into our model with total variation (TV) regularization. The combined network was trained on 3D TRUS patches with the deep supervision strategy, where the binary needle annotation images were provided as ground truth. The trained network was then used to localize and segment the HDR needles for a new patient's TRUS images. We evaluated our proposed method based on the needle shaft and tip errors against manually defined ground truth and compared our method with other state-of-art methods (U-Net and deeply supervised attention U-Net).

RESULTS

Our method detected 96% needles of 339 needles from 23 HDR prostate brachytherapy patients with 0.290 ± 0.236 mm at shaft error and 0.442 ± 0.831 mm at tip error. For shaft localization, our method resulted in 96% localizations with less than 0.8 mm error (needle diameter is 1.67 mm), while for tip localization, our method resulted in 75% needles with 0 mm error and 21% needles with 2 mm error (TRUS image slice thickness is 2 mm). No significant difference is observed (P = 0.83) on tip localization between our results with the ground truth. Compared with U-Net and deeply supervised attention U-Net, the proposed method delivers a significant improvement on both shaft error and tip error (P < 0.05).

CONCLUSIONS

We proposed a new segmentation method to precisely localize the tips and shafts of multiple needles in 3D TRUS images of HDR prostate brachytherapy. The 3D rendering of the needles could help clinicians to evaluate the needle placements. It paves the way for the development of real-time plan dose assessment tools that can further elevate the quality and outcome of HDR prostate brachytherapy.

A planning study of focal dose escalations to multiparametric MRI-defined dominant intraprostatic lesions in prostate proton radiation therapy

OBJECTIVES

The purpose of this study is to investigate the dosimetric effect and clinical impact of delivering a focal radiotherapy boost dose to multiparametric MRI (mp-MRI)-defined dominant intraprostatic lesions (DILs) in prostate cancer using proton therapy.

METHODS

We retrospectively investigated 36 patients with pre-treatment mp-MRI and CT images who were treated using pencil beam scanning (PBS) proton radiation therapy to the whole prostate. DILs were contoured on co-registered mp-MRIs. Simultaneous integrated boost (SIB) plans using intensity-modulated proton therapy (IMPT) were created based on conventional whole-prostate-irradiation for each patient and optimized with additional DIL coverage goals and urethral constraints. DIL dose coverage and organ-at-risk (OAR) sparing were compared between conventional and SIB plans. Tumor control probability (TCP) and normal tissue complication probability (NTCP) were estimated to evaluate the clinical impact of the SIB plans.

RESULTS

Optimized SIB plans significantly escalated the dose to DILs while meeting OAR constraints. SIB plans were able to achieve 125, 150 and 175% of prescription dose coverage in 74, 54 and 17% of 36 patients, respectively. This was modeled to result in an increase in DIL TCP by 7.3-13.3% depending on α / β and DIL risk level.

CONCLUSION

The proposed mp-MRI-guided DIL boost using proton radiation therapy is feasible without violating OAR constraints and demonstrates a potential clinical benefit by improving DIL TCP. This retrospective study suggested the use of IMPT-based DIL SIB may represent a strategy to improve tumor control.

ADVANCES IN KNOWLEDGE

This study investigated the planning of mp-MRI-guided DIL boost in prostate proton radiation therapy and estimated its clinical impact with respect to TCP and NTCP.

CT prostate segmentation based on synthetic MRI-aided deep attention fully convolution network

PURPOSE

Accurate segmentation of the prostate on computed tomography (CT) for treatment planning is challenging due to CT's poor soft tissue contrast. Magnetic resonance imaging (MRI) has been used to aid prostate delineation, but its final accuracy is limited by MRI-CT registration errors. We developed a deep attention-based segmentation strategy on CT-based synthetic MRI (sMRI) to deal with the CT prostate delineation challenge without MRI acquisition.

METHODS AND MATERIALS

We developed a prostate segmentation strategy which employs an sMRI-aided deep attention network to accurately segment the prostate on CT. Our method consists of three major steps. First, a cycle generative adversarial network was used to estimate an sMRI from CT images. Second, a deep attention fully convolution network was trained based on sMRI and the prostate contours deformed from MRIs. Attention models were introduced to pay more attention to prostate boundary. The prostate contour for a query patient was obtained by feeding the patient's CT images into the trained sMRI generation model and segmentation model.

RESULTS

The segmentation technique was validated with a clinical study of 49 patients by leave-one-out experiments and validated with an additional 50 patients by hold-out test. The Dice similarity coefficient, Hausdorff distance, and mean surface distance indices between our segmented and deformed MRI-defined prostate manual contours were 0.92 ± 0.09, 4.38 ± 4.66, and 0.62 ± 0.89 mm, respectively, with leave-one-out experiments, and were 0.91 ± 0.07, 4.57 ± 3.03, and 0.62 ± 0.65 mm, respectively, with hold-out test.

CONCLUSIONS

We have proposed a novel CT-only prostate segmentation strategy using CT-based sMRI, and validated its accuracy against the prostate contours that were manually drawn on MRI images and deformed to CT images. This technique could provide accurate prostate volume for treatment planning without requiring MRI acquisition, greatly facilitating the routine clinical workflow.