CBCT image quality QA: Establishing a quantitative program

Automated dentition segmentation: 3D UNet-based approach with MIScnn framework

INTRODUCTION

Advancements in technology have led to the adoption of digital workflows in dentistry, which require the segmentation of regions of interest from cone-beam computed tomography (CBCT) scans. These segmentations assist in diagnosis, treatment planning, and research. However, manual segmentation is an expensive and labor-intensive process. Therefore, automated methods, such as convolutional neural networks (CNNs), provide a more efficient way to generate segmentations from CBCT scans.

METHODS

A three-dimensional UNet-based CNN model, utilizing the Medical Image Segmentation CNN framework, was used for training and generating predictions from CBCT scans. A dataset of 351 CBCT scans, with ground-truth labels created through manual segmentation using AI-assisted segmentation software, was prepared. Data preprocessing, augmentation, and model training were performed, and the performance of the proposed CNN model was analyzed.

RESULTS

The CNN model achieved high accuracy in segmenting maxillary and mandibular teeth from CBCT scans, with average Dice Similarity Coefficient values of 91.83% and 91.35% for maxillary and mandibular teeth, respectively. Performance metrics, including Intersection over Union, precision, and recall, further confirmed the model's effectiveness.

CONCLUSIONS

The study demonstrates the efficacy of the three-dimensional UNet-based CNN model within the Medical Image Segmentation CNN framework for automated segmentation of maxillary and mandibular dentition from CBCT scans. Automated segmentation using CNNs has the potential to deliver accurate and efficient results, offering a significant advantage over traditional segmentation methods.

Characterization of kilovoltage x-ray image guidance system with a novel post-processing algorithm on a new slip ring-mounted radiotherapy system

PURPOSE

This study evaluates the performance of a kilovoltage x-ray image-guidance system equipped with a novel post-processing optimization algorithm on the newly introduced TAICHI linear accelerator (Linac).

METHODS

A comparative study involving image quality tests and radiation dose measurements was conducted across six scanning protocols of the kV-cone beam computed tomography (CBCT) system on the TAICHI Linac. The performance assessment utilized the conventional Feldkamp-Davis-Kress (FDK) algorithm and a novel Non-Local Means denoising and adaptive scattering correction (NLM-ASC) algorithm. Image quality metrics, including spatial resolution, contrast-to-noise ratio (CNR), and signal-to-noise ratio (SNR), were evaluated using a Catphan 604 phantom. Radiation doses for low-dose and standard protocols were measured using a computed tomography dose index (CTDI) phantom, with comparative measurements from the Halcyon Linac's iterative CBCT (iCBCT).

RESULTS

The NLM-ASC algorithm significantly improved image quality, achieving a 300%-1000% increase in CNR and SNR over the FDK-only images and it also showed a 100%-200% improvement over the iCBCT images from Halcyon's head protocol. The optimized low-dose protocols yielded higher image quality than the standard FDK protocols, indicating potential for reduced radiation exposure. Clinical implementation confirmed the TAICHI system's utility for precise and adaptive radiotherapy.

CONCLUSION

The kV-IGRT system on the TAICHI Linac, with its novel post-processing algorithm, demonstrated superior image quality suitable for routine clinical use, effectively reducing image noise without compromising other quality metrics.

ACR benchmark testing of a novel high-speed ring-gantry linac kV-CBCT system

A new generation cone-beam computed tomography (CBCT) system with new hardware design and advanced image reconstruction algorithms is available for radiation treatment simulation or adaptive radiotherapy (HyperSight CBCT imaging solution, Varian Medical Systems-a Siemens Healthineers company). This study assesses the CBCT image quality metrics using the criteria routinely used for diagnostic CT scanner accreditation as a first step towards the future use of HyperSight CBCT images for treatment planning and target/organ delineations. Image performance was evaluated using American College of Radiology (ACR) Program accreditation phantom tests for diagnostic computed tomography systems (CTs) and compared HyperSight images with a standard treatment planning diagnostic CT scanner (Siemens SOMATOM Edge) and with existing CBCT systems (Varian TrueBeam version 2.7 and Varian Halcyon version 2.0).  Image quality performance for all Varian HyperSight CBCT vendor-provided imaging protocols were assessed using ACR head and body ring CT phantoms, then compared to existing imaging modalities. Image quality analysis metrics included contrast-to-noise (CNR), spatial resolution, Hounsfield number (HU) accuracy, image scaling, and uniformity. All image quality assessments were made following the recommendations and passing criteria provided by the ACR. The Varian HyperSight CBCT imaging system demonstrated excellent image quality, with the majority of vendor-provided imaging protocols capable of passing all ACR CT accreditation standards. Nearly all (8/11) vendor-provided protocols passed ACR criteria using the ACR head phantom, with the Abdomen Large, Pelvis Large, and H&N vendor-provided protocols produced HU uniformity values slightly exceeding passing criteria but remained within the allowable minor deviation levels (5-7 HU maximum differences). Compared to other existing CT and CBCT imaging modalities, both HyperSight Head and Pelvis imaging protocols matched the performance of the SOMATOM CT scanner, and both the HyperSight and SOMATOM CT substantially surpassed the performance of the Halcyon 2.0 and TrueBeam version 2.7 systems. Varian HyperSight CBCT imaging system could pass almost all tests for all vendor-provided protocols using ACR accreditation criteria, with image quality similar to those produced by diagnostic CT scanners and significantly better than existing linac-based CBCT imaging systems.

Radiological evaluation of an iodised hydrogel for prostate radiotherapy applications

PURPOSE

Physical separation of healthy tissue and target volumes in prostate radiotherapy through the insertion of hydrogel can improve patient toxicity rates. An iodised hydrogel may provide anatomical separation of prostate and rectum while being easily visualised through radio-opacity. The aim of this study was to characterise SpaceOAR Vue™ in kilovoltage (kV) images and megavoltage (MV) radiotherapy treatment planning.

METHODS

Two cassettes were 3D-printed, one filled with water and the other with SpaceOAR Vue™. Transmission dose through each cassette was measured in slab phantom geometry and compared for 6MV and 10MV photon energies. The SpaceOAR Vue™ slab phantom setup was simulated using computed tomography (CT) and a treatment plan created. The plan was calculated with the hydrogel segmented and material assignment set to water, and the resultant dose compared to corresponding measurement doses. The first 5 patients treated with SpaceOAR Vue™ were assessed with the volume and Hounsfield units (HU) of the hydrogel evaluated in CT and cone beam computed tomography (CBCT) imaging.

RESULTS

Transmission through Water and SpaceOAR Vue™ agreed to within 0.5% for both photon energies. Furthermore, the segmentation of SpaceOAR Vue™ and material assignment to water, resulted in a plan dose that agreed to measurement to within 0.5%. Clinically, the SpaceOAR Vue™ volume and HU did not vary over patient treatment course, however was found to display differently on different kV imaging modalities.

CONCLUSIONS

SpaceOAR Vue™ was found to be radio-opaque on kV images, but dosimetrically behaved similarly to water in MV treatment beams, making it suitable for clinical use.

A step closer to automation: kilovoltage and Megavoltage Planar Imaging Quality Assurance, baseline, tolerance and action levels definition and exploration

PURPOSE

To establish automated quality assurance (QA) procedures for the kilovoltage (kV) and the Megavoltage (MV) imagers of two linear accelerators (LINACS) using a commercial software.

METHODS

SNC Machine™ phantoms and software were used and the baseline values, tolerance and action levels for various image quality parameters were defined. Scaling, spatial resolution, contrast, uniformity and noise were considered, explored and evaluated utilizing the appropriate phantoms and the accompanying software. kV and MV planar radiographic images, for 6MV and 10MV beams were obtained for each LINAC. For both kV and MV QA tasks, the baseline values for spatial resolution, contrast, uniformity and noise were defined.

RESULTS

Subsequent measurements performed were highly reproducible and within tolerance and action levels, while noise showed variations. The calculated tolerance and action levels for noise were looser compared to the other image quality metrics.

CONCLUSIONS

An automated QA workflow of the kV and MV planar radiographic mode of LINAC imagers' was established and appears to be time effective.

Study on the value of multi-dimensional conformal radiotherapy and functional imaging in tumor bioimaging

BACKGROUND

To explore the diagnostic and therapeutic effects of multi-dimensional conformal radiotherapy (MD-CRT) combined with functional imaging in tumor bioimaging.

METHODS

A total of 150 cases of patients with brain metastases in First Affiliated Hospital of Xi'an Jiaotong University between December 2020 and December 2021 were retrospectively selected as the research cohort. Participants underwent whole brain imaging guided by MD-CRT combined with volume assessment to assess the patient's recent treatment effect, statistically acceptable dose irradiation treatment, and the incidence of adverse reactions. All patients were followed up to evaluate the long-term efficacy.

RESULTS

Among the 150 patients, 24 cases were in complete remission, 72 cases were in partial remission, 36 cases were in a stable condition, 18 cases were in deterioration, and the treatment of 96 cases (64.00%) was deemed effective. All participants were followed up, the mean survival was (62.37±1.24) months, 96 cases (64.00%) survived, and 54 cases (36.00%) had died. The average dose was (62.09±3.94) Gy. In terms of adverse reactions: brain edema occurred in 57 patients, accounting for 38.00%.

CONCLUSIONS

The MD-CRT and functional imaging techniques for patients with metastatic tumor have high therapeutic accuracy, are associated with improved local control rate, prolonged survival, and cause little damage to normal tissues, with significant therapeutic effect, and can be widely used in clinical practice.

Assessing the reproducibility of CBCT-derived radiomics features using a novel three-dimensional printed phantom

PURPOSE

Radiomics modeling is an exciting avenue for enhancing clinical decision making and personalized treatment. Radiation oncology patients often undergo routine imaging for position verification, particularly using LINAC-mounted cone beam computed tomography (CBCT). The wealth of imaging data collected in modern radiation therapy presents an ideal use case for radiomics modeling. Despite this, texture feature (TF) calculation can be limited by concerns over feature stability and reproducibility; in theory, this issue is compounded by the relatively poor image quality of CBCT, as well as variation of acquisition and reconstruction parameters.

METHODS

In this study, we developed and validated a novel three-dimensional (3D) printed phantom for evaluating CBCT-based TF reliability. The phantom has a cylindrical shape (22 cm diameter and 25.5 cm height) with five inner inserts designed to hold custom-printed rods (1 cm diameter and 10-20 cm height) of various materials, infill shapes, and densities. TF reproducibility was evaluated across and within three LINACs from a single vendor using sets of three consecutive CBCT taken with the head, thorax, and pelvis clinical imaging protocols. PyRadiomics was used to extract a standard set of TFs from regions of interest centered on each rod. Two-way mixed effects absolute agreement intra-class correlation coefficient (ICC) was used to evaluate TF reproducibility, with features showing ICC values above 0.9 considered robust if their Bonferroni-corrected p-value was below 0.05.

RESULTS

A total of 63, 87, and 83 features exhibited test-retest reliability for the head, thorax, and pelvis imaging protocols respectively. When assessing stability between discreet imaging sessions on the same LINAC, these numbers were reduced to 5, 63, and 70 features, respectively. The thorax and pelvis protocols maintained a rich candidate feature space in inter-LINAC analysis with 61 and 65 features, respectively, exceeding the ICC criteria. Crucially, no features were deemed reproducible when compared between protocols.

CONCLUSIONS

We have developed a 3D phantom for consistent evaluation of TF stability and reproducibility. For LINACs from a single vendor, our study found a substantial number of features available for robust radiomics modeling from CBCT imaging. However, some features showed variations across LINACs. Studies involving CBCT-based radiomics must preselect features prior to their use in clinical-based models.