MRI-BASED PROSTATE BRACHYTHERAPY SEED LOCALIZATION

Catheter reconstruction and dosimetric verification of MRI-only treatment planning (MRTP) for interstitial HDR brachytherapy using PETRA sequence

Objective. The feasibility of MRI-only treatment planning (MRTP) for interstitial high-dose rate (HDR) brachytherapy (BT) was investigated for patients diagnosed with gynecologic cancer.Approach. A clinical MRTP workflow utilizing a 'pointwise encoding time reduction with radial acquisition (PETRA)' sequence was proposed. This is a clinically available MRI sequence optimized to improve interstitial catheter-tissue contrast. Interstitial needles outside the obturator region were reconstructed using MR images only. For catheters penetrating through the obturator, a library-based reconstruction was proposed. In this work, dwell coordinates from the clinical CT-based reconstruction were used as the surrogate for the library-based approach. For MR-only plan, dwell times were activated and assigned as in the clinical plans. The catheter reconstruction was assessed by comparing dwell position coordinates. The dosimetric comparisons between a clinical plan and MR-only plan were assessed for physical and EQD2 dose and volume parameters forD₉₀,D₅₀andD₉₈for clinical target volume (CTV) andD_2cc,D_0.1ccandD_5ccfor OARs.Main results. Catheter reconstruction was possible using the optimized PETRA sequence on MR images. An overall reconstruction difference of 1.7 ± 0.5 mm, attributed to registration-based errors, was found compared to the CT-based reconstruction. The MRTP workflow has the potential to generate a treatment plan with an equivalent dosimetric quality compared to the conventional CT/MRI-based approach. For CTVD₉₀, physical and EQD2 dose and volume parameter differences were 1.5 ± 1.9% and 0.7 ± 1.0 Gy, respectively. ForD_2ccOARs, DVH (EQD2) differences were -0.4 ± 1.1% (-0.2 ± 0.5 Gy), 0.5 ± 2.8% (0.2 ± 1.3 Gy) and -0.5 ± 1.4% (-0.2 ± 0.5 Gy) for rectum, bladder, and sigmoid, respectively.Significance. With the proposed MRTP approach, CT imaging may no longer be needed in HDR BT for interstitial gynecologic treatment. A proof-of-concept study was conducted to demonstrated that MRTP using PETRA is feasible, with comparable dosimetric results to the conventional CT/MRI-based approach.

Machine learning and registration for automatic seed localization in 3D US images for prostate brachytherapy

PURPOSE

New radiation therapy protocols, in particular adaptive, focal or boost brachytherapy treatments, require determining precisely the position and orientation of the implanted radioactive seeds from real-time ultrasound (US) images. This is necessary to compare them to the planned one and to adjust automatically the dosimetric plan accordingly for next seeds implantations. The image modality, the small size of the seeds, and the artifacts they produce make it a very challenging problem. The objective of the presented work is to setup and to evaluate a robust and automatic method for seed localization in three-dimensional (3D) US images.

METHODS

The presented method is based on a prelocalization of the needles through which the seeds are injected in the prostate. This prelocalization allows focusing the search on a region of interest (ROI) around the needle tip. Seeds localization starts by binarizing the ROI and removing false positives using, respectively, a Bayesian classifier and a support vector machine (SVM). This is followed by a registration stage using first an iterative closest point (ICP) for localizing the connected set of seeds (named strand) inserted through a needle, and secondly refining each seed position using sum of squared differences (SSD) as a similarity criterion. ICP registers a geometric model of the strand to the candidate voxels while SSD compares an appearance model of a single seed to a subset of the image. The method was evaluated both for 3D images of an Agar-agar phantom and a dataset of clinical 3D images. It was tested on stranded and on loose seeds.

RESULTS

Results on phantom and clinical images were compared with a manual localization giving mean errors of 1.09 ± 0.61 mm on phantom image and 1.44 ± 0.45 mm on clinical images. On clinical images, the mean errors of individual seeds orientation was 4.33 ± 8 . 51 ∘ .

CONCLUSIONS

The proposed algorithm for radioactive seed localization is robust, tested on different US images, accurate, giving small mean error values, and returns the five cylindrical seeds degrees of freedom.

Automatic tandem and ring reconstruction using MRI for cervical cancer brachytherapy

PURPOSE

The MRI-guided cervical cancer brachytherapy provides unparalleled soft-tissue contrast for target and normal tissue contouring, but eliminates the ability to use conventional metallic fiducials for radiation source path reconstruction as required for treatment planning. Instead, the source path is reconstructed by manually aligning a library model to the signal void produced by the applicator, which takes time intraoperatively and precludes fully automated treatment planning. The purpose of this study is to present and validate an algorithm to automatically reconstruct tandem and ring applicators using MRI for cervical cancer brachytherapy treatment planning.

METHODS

Applicators were reconstructed using T2-weighted MR images acquired at 1.5 T from 33 brachytherapy fractions including 10 patients using a model-to-image registration algorithm. The algorithm involves (a) image filtering and maximum intensity projection to highlight the applicator, (b) ring center identification using the circular Hough transform, and (c) three-dimensional surface model registration, optimized by maximizing the image intensity gradient normal to the model surface. Two independent observers manually reconstructed all applicators, enabling the calculation of interobserver variability and establishing a ground truth. Algorithm variability was calculated by comparing algorithm results to each individual observer, and algorithm accuracy was calculated by comparing algorithm results to the ground truth. The algorithm variability and accuracy were compared to the interobserver variability using paired t-tests.

RESULTS

Mean ± SD interobserver variability was 0.83 ± 0.31 mm and 0.78 ± 0.29 mm for the ring and tandem, respectively. The algorithm had mean ± SD variability and accuracy of 0.72 ± 0.32 mm (P = 0.02) and 0.60 ± 0.24 mm (P = 0.0005) for the ring, and 0.70 ± 0.29 mm (P = 0.11) and 0.58 ± 0.24 mm (P = 0.004) for the tandem, respectively.

CONCLUSIONS

The algorithm variability and accuracy were within the interobserver variability measured in this study. The algorithm accuracy and mean execution time of 10.0 s are sufficient for clinical tandem and ring reconstruction, and are a step toward fully automated tandem and ring brachytherapy treatment planning.

Deformable registration of x ray and MRI for postimplant dosimetry in low dose rate prostate brachytherapy

PURPOSE

Dosimetric assessment following permanent prostate brachytherapy (PPB) commonly involves seed localization using CT and prostate delineation using coregistered MRI. However, pelvic CT leads to additional imaging dose and requires significant resources to acquire and process both CT and MRI. In this study, we propose an automatic postimplant dosimetry approach that retains MRI for soft-tissue contouring, but eliminates the need for CT and reduces imaging dose while overcoming the inconsistent appearance of seeds on MRI with three projection x rays acquired using a mobile C-arm.

METHODS

Implanted seeds are reconstructed using x rays by solving a combinatorial optimization problem and deformably registered to MRI. Candidate seeds are located in MR images using local hypointensity identification. X ray-based seeds are registered to these candidate seeds in three steps: (a) rigid registration using a stochastic evolutionary optimizer, (b) affine registration using an iterative closest point optimizer, and (c) deformable registration using a local feature point search and nonrigid coherent point drift. The algorithm was evaluated using 20 PPB patients with x rays acquired immediately postimplant and T2-weighted MR images acquired the next day at 1.5 T with mean 0.8 × 0.8 × 3.0 mm 3 voxel dimensions. Target registration error (TRE) was computed based on the distance from algorithm results to manually identified seed locations using coregistered CT acquired the same day as the MRI. Dosimetric accuracy was determined by comparing prostate D90 determined using the algorithm and the ground truth CT-based seed locations.

RESULTS

The mean ± standard deviation TREs across 20 patients including 1774 seeds were 2.23 ± 0.52 mm (rigid), 1.99 ± 0.49 mm (rigid + affine), and 1.76 ± 0.43 mm (rigid + affine + deformable). The corresponding mean ± standard deviation D90 errors were 5.8 ± 4.8%, 3.4 ± 3.4%, and 2.3 ± 1.9%, respectively. The mean computation time of the registration algorithm was 6.1 s.

CONCLUSION

The registration algorithm accuracy and computation time are sufficient for clinical PPB postimplant dosimetry.

Automatic seed picking for brachytherapy postimplant validation with 3D CT images

PURPOSE

Postimplant validation is an indispensable part in the brachytherapy technique. It provides the necessary feedback to ensure the quality of operation. The ability to pick implanted seed relates directly to the accuracy of validation. To address it, an automatic approach is proposed for picking implanted brachytherapy seeds in 3D CT images.

METHODS

In order to pick seed configuration (location and orientation) efficiently, the approach starts with the segmentation of seed from CT images using a thresholding filter which based on gray-level histogram. Through the process of filtering and denoising, the touching seed and single seed are classified. The true novelty of this approach is found in the application of the canny edge detection and improved concave points matching algorithm to separate touching seeds. Through the computation of image moments, the seed configuration can be determined efficiently. Finally, two different experiments are designed to verify the performance of the proposed approach: (1) physical phantom with 60 model seeds, and (2) patient data with 16 cases.

RESULTS

Through assessment of validated results by a medical physicist, the proposed method exhibited promising results. Experiment on phantom demonstrates that the error of seed location and orientation is within ([Formula: see text]) mm and ([Formula: see text])[Formula: see text], respectively. In addition, the most seed location and orientation error is controlled within 0.8 mm and 3.5[Formula: see text] in all cases, respectively. The average process time of seed picking is 8.7 s per 100 seeds.

CONCLUSIONS

In this paper, an automatic, efficient and robust approach, performed on CT images, is proposed to determine the implanted seed location as well as orientation in a 3D workspace. Through the experiments with phantom and patient data, this approach also successfully exhibits good performance.

Effect of pulse sequence parameter selection on signal strength in positive-contrast MRI markers for MRI-based prostate postimplant assessment

PURPOSE

For postimplant dosimetric assessment, computed tomography (CT) is commonly used to identify prostate brachytherapy seeds, at the expense of accurate anatomical contouring. Magnetic resonance imaging (MRI) is superior to CT for anatomical delineation, but identification of the negative-contrast seeds is challenging. Positive-contrast MRI markers were proposed to replace spacers to assist seed localization on MRI images. Visualization of these markers under varying scan parameters was investigated.

METHODS

To simulate a clinical scenario, a prostate phantom was implanted with 66 markers and 86 seeds, and imaged on a 3.0T MRI scanner using a 3D fast radiofrequency-spoiled gradient recalled echo acquisition with various combinations of scan parameters. Scan parameters, including flip angle, number of excitations, bandwidth, field-of-view, slice thickness, and encoding steps were systematically varied to study their effects on signal, noise, scan time, image resolution, and artifacts.

RESULTS

The effects of pulse sequence parameter selection on the marker signal strength and image noise were characterized. The authors also examined the tradeoff between signal-to-noise ratio, scan time, and image artifacts, such as the wraparound artifact, susceptibility artifact, chemical shift artifact, and partial volume averaging artifact. Given reasonable scan time and managable artifacts, the authors recommended scan parameter combinations that can provide robust visualization of the MRI markers.

CONCLUSIONS

The recommended MRI pulse sequence protocol allows for consistent visualization of the markers to assist seed localization, potentially enabling MRI-only prostate postimplant dosimetry.

Pulse sequence considerations for simulation and postimplant dosimetry of prostate brachytherapy

PURPOSE

The purpose of this work is to present a brief review of MRI physics principles pertinent to prostate brachytherapy, and a summary of our experience in optimizing protocols for prostate brachytherapy applications.

METHODS AND MATERIALS

We summarized essential MR imaging characteristics and their interplays that need to be considered for prostate brachytherapy applications. These include spatial resolution, signal-to-noise ratio, image contrast, artifacts, geometric distortion, specific absorption rate, and total scan time. We further described the optimization of the protocols for three pulse sequences: three-dimensional (3D) fast-spoiled gradient echo sequence for T1-weighted imaging, 3D fast-spin echo sequence for T2-weighted imaging, and 3D fast imaging in steady-state precession sequence for combined T1 and T2-weighed imaging. The utilization of an endorectal coil was also described.

RESULTS

Using the optimized protocols, we acquired high-quality images of the entire prostate within 3-5 minutes for each sequence. These images display the desired image contrasts and a spatial resolution that is equal to or better than 0.59 mm × 0.73 mm × 1.2 mm. While 3D fast-spoiled gradient echo sequence and 3D fast-spin echo sequence depict radioactive seed markers and anatomic structures separately, 3D fast imaging in steady-state precession sequence demonstrates great promise for imaging both seed markers and prostate anatomy simultaneously in a single acquisition.

CONCLUSIONS

We have optimized current MRI protocols and demonstrated that the anatomic structures and positive contrast radioactive seed markers for prostate post-implant dosimetry can be adequately imaged either separately or simultaneously using different pulse sequences within a total scan time of 3-5 minutes each.

Trends in targeted prostate brachytherapy: from multiparametric MRI to nanomolecular radiosensitizers

The treatment of localized prostate cancer is expected to become a significant problem in the next decade as an increasingly aging population becomes prone to developing the disease. Recent research into the biological nature of prostate cancer has shown that large localized doses of radiation to the cancer offer excellent long-term disease control. Brachytherapy, a form of localized radiation therapy, has been shown to be one of the most effective methods for delivering high radiation doses to the cancer; however, recent evidence suggests that increasing the localized radiation dose without bound may cause unacceptable increases in long-term side effects. This review focuses on methods that have been proposed, or are already in clinical use, to safely escalate the dose of radiation within the prostate. The advent of multiparametric magnetic resonance imaging (mpMRI) to better identify and localize intraprostatic tumors, and nanomolecular radiosensitizers such as gold nanoparticles (GNPs), may be used synergistically to increase doses to cancerous tissue without the requisite hazard of increased side effects.

Automatic seed localization of iodine brachytherapy implants from CT images

Radioactive seed implantation has emerged as an effective treatment modality where small radioactive seeds are implanted into the target organ to eradicate the cancer by emitting radiation. Precise seeds localization can indicate whether those seeds deliver sufficient doses of radiation. However, it is challenging and laborious to identify all seeds manually in a short time. Therefore, our purpose in this study was to develop an automatic technique for identifying implanted seeds on any parts of body. The algorithm relies on a 3D adaptive median filter to remove bone structure; white top-hat transform to extract seeds-like objects and further seed classification analysis based on size, shape and their connection etc. Preliminary results on ten patients and seven simulated data show that this approach to be effective and accurate. It resulted in a 96.9 % detection rate with a corresponding 4.7 % false-positive rate for clinical data; a 98.5 % detection rate with a corresponding 4.1 % false-positive rate for the simulated data; and sub-millimeter accuracy for both data sets. This method can achieve robust and accurate seed segmentation through the proposed workflow.