Dataset Information

Quantifying intrafractional gastric motion using auto-segmentation on MRI: Deformation and respiratory-induced displacement compared.

ABSTRACT:

Background and purpose

For 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 methods

Coronal 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 P_Occ = 0.50 and 50 other isosurfaces (from P_Occ = 0.01 to 0.99), with P_Occ 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 (SD_deform ) expressing local deformation. For each volunteer, we determined median and 98^th percentile of SD_deform over the reference surface and compared these with the respiratory-induced displacement SD_resp , that is, the SD of all CoM shifts (paired Wilcoxon signed-rank, α = 0.05).

Results

Larger deformations were mostly seen in the antrum and pyloric region. Median SD_deform (range, 2.0-2.9 mm) was smaller than SD_resp (2.7-8.8 mm) for each volunteer (p < 0.00001); 98^th percentile of SD_deform (3.2-7.3 mm) did not significantly differ from SD_resp (p = 0.13).

Conclusion

Locally, 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.

SUBMITTER: Driever T

PROVIDER: S-EPMC10113698 | biostudies-literature | 2023 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Quantifying intrafractional gastric motion using auto-segmentation on MRI: Deformation and respiratory-induced displacement compared.

Driever Theo T Hulshof Maarten C C M MCCM Bel Arjan A Sonke Jan-Jakob JJ van der Horst Astrid A

Journal of applied clinical medical physics 20221224 4

<h4>Background and purpose</h4>For 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.<h4>Materials and methods</h4>Coronal 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 respirat ...[more]

PMID: 36565168

Similar Datasets

Project description:Defining myocardial contours is often the most time-consuming portion of dynamic cardiac MRI image analysis. Displacement encoding with stimulated echoes (DENSE) is a quantitative MRI technique that encodes tissue displacement into the phase of the complex MRI images. Cine DENSE provides a time series of these images, thus facilitating the non-invasive study of myocardial kinematics. Epicardial and endocardial contours need to be defined at each frame on cine DENSE images for the quantification of regional displacement and strain as a function of time. This work presents a reliable and effective two-dimensional semi-automated segmentation technique that uses the encoded motion to project a manually-defined region of interest through time. Contours can then easily be extracted for each cardiac phase. This method boasts several advantages, including, (1) parameters are based on practical physiological limits, (2) contours are calculated for the first few cardiac phases, where it is difficult to visually distinguish blood from myocardium, and (3) the method is independent of the shape of the tissue delineated and can be applied to short- or long-axis views, and on arbitrary regions of interest. Motion-guided contours were compared to manual contours for six conventional and six slice-followed mid-ventricular short-axis cine DENSE datasets. Using an area measure of segmentation error, the accuracy of the segmentation algorithm was shown to be similar to inter-observer variability. In addition, a radial segmentation error metric was introduced for short-axis data. The average radial epicardial segmentation error was 0.36+/-0.08 and 0.40+/-0.10 pixels for slice-followed and conventional cine DENSE, respectively, and the average radial endocardial segmentation error was 0.46+/-0.12 and 0.46+/-0.16 pixels for slice following and conventional cine DENSE, respectively. Motion-guided segmentation employs the displacement-encoded phase shifts intrinsic to DENSE MRI to accurately propagate a single set of pre-defined contours throughout the remaining cardiac phases.

Project description:PurposeTo determine the 3-dimensional (3D) intrafractional motion of head and neck squamous cell carcinoma (HNSCC).Methods and materialsDynamic contrast-enhanced magnetic resonance images from 56 patients with HNSCC in the treatment position were analyzed. Dynamic contrast-enhanced magnetic resonance imaging consisted of 3D images acquired every 2.9 seconds for 4 minutes 50 seconds. Intrafractional tumor motion was studied in the 3 minutes 43 seconds of images obtained after initial contrast enhancement. To assess tumor motion, rigid registration (translations only) was performed using a region of interest (ROI) mask around the tumor. The results were compared with bulk body motion from registration to all voxels. Motion was split into systematic motion and random motion. Correlations between the tumor site and random motion were tested. The within-subject coefficient of variation was determined from 8 patients with repeated baseline measures. Random motion was also assessed at the end of the first week (38 patients) and second week (25 patients) of radiation therapy to investigate trends of motion.ResultsTumors showed irregular occasional rapid motion (eg, swallowing or coughing), periodic intermediate motion (respiration), and slower systematic drifts throughout treatment. For 95% of the patients, displacements due to systematic and random motion were <1.4 mm and <2.1 mm, respectively, 95% of the time. The motion without an ROI mask was significantly (P<.0001, Wilcoxon signed rank test) less than the motion with an ROI mask, indicating that tumors can move independently from the bony anatomy. Tumor motion was significantly (P=.005, Mann-Whitney U test) larger in the hypopharynx and larynx than in the oropharynx. The within-subject coefficient of variation for random motion was 0.33. The average random tumor motion did not increase notably during the first 2 weeks of treatment.ConclusionsThe 3D intrafractional tumor motion of HNSCC is small, with systematic motion <1.4 mm and random motion <2.1 mm 95% of the time.

Project description:BackgroundThe accurate segmentation of spine muscles plays a crucial role in analyzing musculoskeletal disorders and designing effective rehabilitation strategies. Various imaging techniques such as MRI have been utilized to acquire muscle images, but the segmentation process remains complex and challenging due to the inherent complexity and variability of muscle structures. In this systematic review, we investigate and evaluate methods for automatic segmentation of spinal muscles.MethodsData for this study were obtained from PubMed/MEDLINE databases, employing a search methodology that includes the terms 'Segmentation spine muscle' within the title, abstract, and keywords to ensure a comprehensive and systematic compilation of relevant studies. Systematic reviews were not included in the study.ResultsOut of 369 related studies, we focused on 12 specific studies. All studies focused on segmentation of spine muscle use MRI, in this systematic review subjects such as healthy volunteers, back pain patients, ASD patient were included. MRI imaging was performed on devices from several manufacturers, including Siemens, GE. The study included automatic segmentation using AI, segmentation using PDFF, and segmentation using ROI.ConclusionDespite advancements in spine muscle segmentation techniques, challenges still exist. The accuracy and precision of segmentation algorithms need to be improved to accurately delineate the different muscle structures in the spine. Robustness to variations in image quality, artifacts, and patient-specific characteristics is crucial for reliable segmentation results. Additionally, the availability of annotated datasets for training and validation purposes is essential for the development and evaluation of new segmentation algorithms. Future research should focus on addressing these challenges and developing more robust and accurate spine muscle segmentation techniques to enhance clinical assessment and treatment planning for musculoskeletal disorders.

Project description:PurposeAbdominal compression can minimize breathing motion in stereotactic radiotherapy, though it may impact the positioning of dose-limiting normal tissues. This study quantified the reproducibility of abdominal normal tissues and respiratory motion with the use of an abdominal compression device using MR imaging.MethodsTwenty healthy volunteers had repeat MR over 3 days under an abdominal compression plate device. Normal tissues were delineated on daily axial T2-weighted MR and compared on days 2 and 3 relative to day 1, after adjusting for baseline shifts relative to bony anatomy. Inter-fraction organ deformation was computed using deformable registration of axial T2 images. Deformation > 5 mm was assumed to be clinically relevant. Inter-fraction respiratory amplitude changes and intra-fraction baseline drifts during imaging were quantified on daily orthogonal cine-MR (70 s each), and changes > 3 mm were assumed to be relevant.ResultsOn axial MR, the mean inter-fraction normal tissue deformation was > 5 mm for all organs (range 5.1-13.4 mm). Inter-fraction compression device misplacements > 5 mm and changes in stomach volume > 50% occurred at a rate of 93% and 38%, respectively, in one or more directions and were associated with larger adjacent organ deformation, in particular for the duodenum. On cine-MR, inter-fraction amplitude changes > 3 mm on day 2 and 3 relative to day 1 occurred at a rate of < 12.5% (mean superior-inferior change was 1.6 mm). Intra-fraction baseline drifts > 3 mm during any cine-MR acquisition occurred at a rate of 23% (mean superior-inferior changes was 2.4 mm).ConclusionsRespiratory motion under abdominal compression is reproducible in most subjects within 3 mm. However, inter-fraction deformations greater than 5 mm in normal tissues were common and larger than inter- and intra-fraction respiratory changes. Deformations were driven mostly by variable stomach contents and device positioning. The magnitude of this motion may impact normal tissue dosimetry during stereotactic radiotherapy.

Dataset Information

Quantifying intrafractional gastric motion using auto-segmentation on MRI: Deformation and respiratory-induced displacement compared.

Background and purpose

Materials and methods

Results

Conclusion

Publications

Quantifying intrafractional gastric motion using auto-segmentation on MRI: Deformation and respiratory-induced displacement compared.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets