Weight-bearing cone-beam CT with extensive coverage for volumetric imaging in adolescent idiopathic scoliosis: system implementation and initial validation.
Zejun LiangChunchao XiaQian WangZengtong ChenYu ZhangChao YeYiteng ZhangJie YangHairong WangHan ZhengJing DuZhen-Lin LiJing TangPublished in: Physical and engineering sciences in medicine (2023)
The study aimed to introduce a novel imaging method that generates large-coverage, weight-bearing, and 3D images of the whole spine. The proposed system comprises an X-ray tube, a flat panel detector, and a standing platform. The standing platform rotates the imaged subject, allowing for the acquisition of serial fluoroscopic images from different angles which can be used to create 3D images. To increase the longitudinal coverage, we apply a segmental scanning pattern in which the imaged region is scanned in segments and stitched. To address the issue of data inaccuracy between the segments, redundant areas are set at margins of the segmental images, and registration and stitching algorithms are applied. We conducted validation experiments to evaluate radiation dose and image quality. The dose was evaluated using the volume CT dose index (CTDI vol ). For image quality evaluation, we measured the low-contrast and spatial resolution. Additionally, we conducted a clinical study consisting of 30 volunteers with adolescent idiopathic scoliosis who were imaged by our method, and the images were subjectively assessed based on image noise, artifacts, anatomical coverage, diagnostic confidence, and overall quality. The CTDI vol was 1.23 mGy, and the low-contrast resolution was 0.6% at 4 mm and the spatial resolution was 8 lp/cm. The clinical images were generally of good quality, with high scores for all factors evaluated. Our method successfully generates large-coverage, weight-bearing, and 3D images of the whole spine with high image quality and low radiation dose. It shows potential for wider clinical applications for various musculoskeletal conditions.
Keyphrases
- image quality
- deep learning
- dual energy
- convolutional neural network
- computed tomography
- optical coherence tomography
- high resolution
- affordable care act
- body mass index
- physical activity
- magnetic resonance
- artificial intelligence
- machine learning
- weight loss
- healthcare
- primary care
- weight gain
- cone beam
- high throughput
- magnetic resonance imaging
- health insurance
- big data
- risk assessment
- photodynamic therapy
- mass spectrometry
- cross sectional
- double blind