Dataset Information

MRI vs CT-based 2D-3D auto-registration accuracy for quantifying shoulder motion using biplane video-radiography.

ABSTRACT: Biplane 2D-3D registration approaches have been used for measuring 3D, in vivo glenohumeral (GH) joint kinematics. Computed tomography (CT) has become the gold standard for reconstructing 3D bone models, as it provides high geometric accuracy and similar tissue contrast to video-radiography. Alternatively, magnetic resonance imaging (MRI) would not expose subjects to radiation and provides the ability to add cartilage and other soft tissues to the models. However, the accuracy of MRI-based 2D-3D registration for quantifying glenohumeral kinematics is unknown. We developed an automatic 2D-3D registration program that works with both CT- and MRI-based image volumes for quantifying joint motions. The purpose of this study was to use the proposed 2D-3D auto-registration algorithm to describe the humerus and scapula tracking accuracy of CT- and MRI-based registration relative to radiostereometric analysis (RSA) during dynamic biplanar video-radiography. The GH kinematic accuracy (RMS error) was 0.6-1.0?mm and 0.6-2.2° for the CT-based registration and 1.4-2.2?mm and 1.2-2.6° for MRI-based registration. Higher kinematic accuracy of CT-based registration was expected as MRI provides lower spatial resolution and bone contrast as compared to CT and suffers from spatial distortions. However, the MRI-based registration is within an acceptable accuracy for many clinical research questions.

SUBMITTER: Akbari-Shandiz M

PROVIDER: S-EPMC6310644 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

MRI vs CT-based 2D-3D auto-registration accuracy for quantifying shoulder motion using biplane video-radiography.

Akbari-Shandiz Mohsen M Lawrence Rebekah L RL Ellingson Arin M AM Johnson Casey P CP Zhao Kristin D KD Ludewig Paula M PM

Journal of biomechanics 20180929

Biplane 2D-3D registration approaches have been used for measuring 3D, in vivo glenohumeral (GH) joint kinematics. Computed tomography (CT) has become the gold standard for reconstructing 3D bone models, as it provides high geometric accuracy and similar tissue contrast to video-radiography. Alternatively, magnetic resonance imaging (MRI) would not expose subjects to radiation and provides the ability to add cartilage and other soft tissues to the models. However, the accuracy of MRI-based 2D-3D ...[more]

PMID: 30385001

Similar Datasets

Project description:PURPOSE:To automate the estimation of swallowing motion from 2D MR cine images using deformable registration for future applications of personalized margin reduction in head and neck radiotherapy and outcome assessment of radiation-associated dysphagia. METHODS:Twenty-one patients with serial 2D FSPGR-MR cine scans of the head and neck conducted through the course of definitive radiotherapy for oropharyngeal cancer. Included patients had at least one cine scan before, during, or after radiotherapy, with a total of 52 cine scans. Contours of 7 swallowing related regions-of-interest (ROIs), including pharyngeal constrictor, epiglottis, base of tongue, geniohyoid, hyoid, soft palate, and larynx, were manually delineated from consecutive frames of the cine scan covering at least one swallowing cycle. We applied a modified thin-plate-spline robust-point-matching algorithm to register the point sets of each ROI automatically over frames. The deformation vector fields from the registration were then used to estimate the motion during swallowing for each ROI. Registration errors were estimated by comparing the deformed contours with the manual contours. RESULTS:On average 22 frames of each cine scan were contoured. The registration for one cine scan (7 ROIs over 22 frames) on average took roughly 22 minutes. A number of 8018 registrations were successfully batch processed without human interaction after the contours were drawn. The average registration error for all ROIs and all patients was 0.36 mm (range: 0.06 mm- 2.06 mm). Larynx had the average largest motion in superior direction of all structures under consideration (range: 0.0 mm- 58.7 mm). Geniohyoid had the smallest overall motion of all ROIs under consideration and the superior-inferior motion was larger than the anterior-posterior motion for all ROIs. CONCLUSION:We developed and validated a deformable registration framework to automate the estimation of swallowing motion from 2D MR cine scans.

Project description:Background and purposeFor accurate pre-operative gastric radiotherapy, intrafractional changes must be taken into account. The aim of this study is to quantify local gastric deformations and compare these deformations with respiratory-induced displacement.Materials and methodsCoronal 2D MRI scans (15-16 min; 120 repetitions of 25-27 interleaved slices) were obtained for 18 healthy volunteers. A deep-learning network was used to auto-segment the stomach. To separate out respiratory-induced displacements, auto-segmentations were rigidly shifted in superior-inferior (SI) direction to align the centre of mass (CoM) within every slice. From these shifted auto-segmentations, 3D iso-probability surfaces (isosurfaces) were established: a reference surface for POcc = 0.50 and 50 other isosurfaces (from POcc = 0.01 to 0.99), with POcc indicating the probability of occupation by the stomach. For each point on the reference surface, distances to all isosurfaces were determined and a cumulative Gaussian was fitted to this probability-distance dataset to obtain a standard deviation (SDdeform ) expressing local deformation. For each volunteer, we determined median and 98th percentile of SDdeform over the reference surface and compared these with the respiratory-induced displacement SDresp , that is, the SD of all CoM shifts (paired Wilcoxon signed-rank, α = 0.05).ResultsLarger deformations were mostly seen in the antrum and pyloric region. Median SDdeform (range, 2.0-2.9 mm) was smaller than SDresp (2.7-8.8 mm) for each volunteer (p < 0.00001); 98th percentile of SDdeform (3.2-7.3 mm) did not significantly differ from SDresp (p = 0.13).ConclusionLocally, gastric deformations can be large. Overall, however, these deformations are limited compared to respiratory-induced displacement. Therefore, unless respiratory motion is considerably reduced, the need to separately include these deformation uncertainties in the treatment margins may be limited.

Project description:In prostate radiotherapy, setup errors with respect to the patient's bony anatomy can be reduced by aligning 2D megavoltage (MV) portal images acquired during treatment to a reference 3D kilovoltage (kV) CT acquired for treatment planning purposes. The purpose of this study was to evaluate a fully automated 2D-3D registration algorithm to quantify setup errors in 3D through the alignment of line-enhanced portal images and digitally reconstructed radiographs computed from the CT. The line-enhanced images were obtained by correlating the images with a filter bank of short line segments, or "sticks" at different orientations. The proposed methods were validated on (1) accurately collected gold-standard data consisting of a 3D kV cone-beam CT scan of an anthropomorphic phantom of the pelvis and 2D MV portal images in the anterior-posterior (AP) view acquired at 15 different poses and (2) a conventional 3D kV CT scan and weekly 2D MV AP portal images of a patient over 8 weeks. The mean (and standard deviation) of the absolute registration error for rotations around the right-lateral (RL), inferior-superior (IS), and posterior-anterior (PA) axes were 0.212 degree (0.214 degree), 0.055 degree (0.033 degree) and 0.041 degree (0.039 degree), respectively. The corresponding registration errors for translations along the RL, IS, and PA axes were 0.161 (0.131) mm, 0.096 (0.033) mm, and 0.612 (0.485) mm. The mean (and standard deviation) of the total registration error was 0.778 (0.543) mm. Registration on the patient images was successful in all eight cases as determined visually. The results indicate that it is feasible to automatically enhance features in MV portal images of the pelvis for use within a completely automated 2D-3D registration framework for the accurate determination of patient setup errors. They also indicate that it is feasible to estimate all six transformation parameters from a 3D CT of the pelvis and a single portal image in the AP view.

Project description:BackgroundInternal rotation in adduction is often limited after reverse total shoulder arthroplasty (rTSA), but the origins of this functional deficit are unclear. Few studies have directly compared individuals who can and cannot perform internal rotation in adduction. Little data on underlying 3D humerothoracic, scapulothoracic, and glenohumeral joint relationships in these patients are available.MethodsIndividuals >1-year postoperative to rTSA were imaged with biplane fluoroscopy in resting neutral and internal rotation in adduction poses. Subjects could either perform internal rotation in adduction with their hand at T12 or higher (high, N = 7), or below the hip pocket (low, N = 8). Demographics, the American Shoulder and Elbow Surgeons score, Simple Shoulder Test, and scapular notching grade were recorded. Joint orientation angles were derived from model-based markerless tracking of the scapula and humerus relative to the torso. The 3D implant models were aligned to preoperative computed tomography models to evaluate bone-implant impingement.ResultsThe Simple Shoulder Test was highest in the high group (11 ± 1 vs. 9 ± 2, P = .019). Two subjects per group had scapular notching (grades 1 and 2), and 3 high group and 4 low group subjects had impingement below the glenoid. In the neutral pose, the scapula had 7° more upward rotation in the high group (P = .100), and the low group demonstrated 9° more posterior tilt (P = .017) and 14° more glenohumeral elevation (P = .047). In the internal rotation pose, axial rotation was >45° higher in the high group (P ≤ .008) and the low group again had 11° more glenohumeral elevation (P = .058). Large rotational differences within subject groups arose from a combination of differences in the resting neutral and maximum internal rotation in adduction poses, not only the terminal arm position.ConclusionsIndividuals who were able to perform high internal rotation in adduction after rTSA demonstrated differences in joint orientation and anatomic biases versus patients with low internal rotation. The high rotation group had 7° more resting scapular upward rotation and used a 15°-30° change in scapular tilt to perform internal rotation in adduction versus patients in the low group. The combination of altered resting scapular posture and restricted scapulothoracic range of motion could prohibit glenohumeral rotation required to reach internal rotation in adduction. In addition, inter-patient variation in humeral torsion may contribute substantially to postoperative internal rotation differences. These data point toward modifiable implant design and placement factors, as well as foci for physical therapy to strengthen and mobilize the scapula and glenohumeral joint in response to rTSA surgery.

Dataset Information

MRI vs CT-based 2D-3D auto-registration accuracy for quantifying shoulder motion using biplane video-radiography.

Publications

MRI vs CT-based 2D-3D auto-registration accuracy for quantifying shoulder motion using biplane video-radiography.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets