Manual 2D Measurements Research Articles

Implementing automated 3D measurements to quantify reference values and side-to-side differences in the ankle syndesmosis

Detection of syndesmotic ankle instability remains challenging in clinical practice due to the limitations of two-dimensional (2D) measurements. The transition to automated three-dimensional (3D) measurement techniques is on the verge of a breakthrough but normative and side-to-side comparative data are missing. Therefore, our study aim was two-fold: (1) to establish 3D anatomical reference values of the ankle syndesmosis based on automated measurements and (2) to determine to what extent the ankle syndesmosis is symmetric across all 3D measurements. Patients without syndesmotic pathology with a non-weight-bearing CT scan (NWBCT; N = 38; Age = 51.6 ± 17.43 years) and weight-bearing CT scan (WBCT; N = 43; Age = 48.9 ± 14.3 years) were retrospectively included. After training and validation of a neural network to automate the segmentation of 3D ankle models, an iterative closest point registration was performed to superimpose the left on the right ankle. Subsequently, 3D measurements were manually and automatically computed using a custom-made algorithm and side-to-side comparison of these landmarks allowed one to investigate symmetry. Intra-observer analysis showed excellent agreements for all manual measurements (ICC range 0.85–0.99) and good (i.e. < 2.7° for the angles and < 0.5 mm for the distances) accuracy was found between the automated and manual measurements. A mean Dice coefficient of 0.99 was found for the automated segmentation framework. The established mean, standard deviation and range were provided for each 3D measurement. From these data, reference values were derived to differ physiological from pathological syndesmotic alignment. Furthermore, side-to-side symmetry was revealed when comparing left to right measurements (P > 0.05). In clinical practice, our novel algorithm could surmount the current limitations of manual 2D measurements and distinguish patients with a syndesmotic ankle lesion from normal variance.

P-702 Prediction of oocyte maturity via automated volumetric follicle measurements on the day of triggering final oocyte maturation. An observational cohort study

Abstract Study question Can automated measurements of follicular volume by three-dimensional (3D) ultrasound predict the number of mature oocytes retrieved better than two-dimensional (2D) measurements of follicles? Summary answer Automated measurements of follicular volume by 3D ultrasound have similar predictive ability of the number of mature oocytes retrieved as manual 2D measurements of follicles. What is known already Accurate assessment of the size and number of follicles during ovarian stimulation is important to determine the day of triggering final oocyte maturation and subsequent oocyte retrieval, in order to achieve the optimal number of mature oocytes. Follicles with a diameter ≥11mm on the day of triggering are often considered to contribute the most towards the final number of mature oocytes. It has also been shown that 3D follicle volumes offer a more physiological measurement and may be a more objective than 2D follicle diameters. However, to date, the correlation between diameters and volumes has not been properly evaluated. Study design, size, duration Prospective observational cohort study of 75 women undergoing ICSI between 01/2021 and 09/2021 in a private ART centre. In each patient, two dimensional-2D and three dimensional-3D transvaginal ultrasound (SonoAVC; GE Medical Systems), was used to assess differences in the number and size of follicles on the day of triggering final oocyte maturation. SonoAVC automatically calculates the volume of the follicle while manual-2D value is calculated as the mean of the maximal follicular dimensions x-y. Participants/materials, setting, methods Patients underwent ovarian stimulation with recombinant-FSH and GnRH antagonists. Statistical analysis involved robust linear regression with dependent variable the number MIIs retrieved and independent variables the number of follicles ≥11mm (via 2D) and the number of follicles with volume ≥0.7ml (via SonoAVC). 0.7ml was used as it is a close approximation to the volume of a sphere with diameter 11mm. This was confirmed by identifying the actual volume of aspirated follicles 11mm (unpublished data). Main results and the role of chance A high correlation of R = 0.922 was observed between manual-2D and automated-3D assessment in the number of follicles with volume ≥0.7ml and those with mean diameter ≥11mm. In addition, no differences were found in the number of follicles with volume ≥0.7ml vs the number of follicles with diameter of ≥ 11mm (median 9.0, IQR: 5.0 – 14.5 vs. median 10.0, IQR: 6.75 – 18, respectively) on the day of triggering final oocyte maturation. The median number of MIIs collected was 9.0 (IQR: 5.0 – 13.25). The predictive capability of follicles with volume ≥0.7ml in regards to the number of MII collected was found to be R2=0.736, which is higher than the predictive capability of follicles ≥11mm (R2=0.629). These findings suggest that the number of follicles with a volume ≥0.7ml offers at least a similar predictive capability as the traditionally used number of follicles ≥11mm. Limitations, reasons for caution While the volume of 0.7ml was found to be closely correlated with the size of 11mm, the predictive capability of other follicular volumes needs to also be compared, since follicles are rarely spheres, especially in hyperstimulated ovaries and therefore even better prediction of oocyte maturation may arise from another volume. Wider implications of the findings Manual-2D ultrasound and automated-3D volumetric assessment of follicles provide similar predictive value of the number of mature oocytes retrieved. Therefore volumetric measurements can possibly be used during assessment of ovarian stimulation, instead of mean diameter. However, their clinical effectiveness needs to be tested in a robust clinical trial. Trial registration number N/A

The MRI posterior drawer test to assess posterior cruciate ligament functionality and knee joint laxity

Clinical Magnetic Resonance Imaging (MRI) of joints is limited to mere morphologic evaluation and fails to directly visualize joint or ligament function. In this controlled laboratory study, we show that knee joint functionality may be quantified in situ and as a function of graded posterior cruciate ligament (PCL)-deficiency by combining MRI and standardized loading. 11 human knee joints underwent MRI under standardized posterior loading in the unloaded and loaded (147 N) configurations and in the intact, partially, and completely PCL-injured conditions. For each specimen, configuration, and condition, 3D joint models were implemented to analyse joint kinematics based on 3D Euclidean vectors and their projections on the Cartesian planes. Manual 2D measurements served as reference. With increasing PCL deficiency, vector projections increased significantly in the anteroposterior dimension under loading and manual measurements demonstrated similar patterns of change. Consequently, if combined with advanced image post-processing, stress MRI is a powerful diagnostic adjunct to evaluate ligament functionality and joint laxity in multiple dimensions and may have a role in differentiating PCL injury patterns, therapeutic decision-making, and treatment monitoring.

Automatic segmentation and location learning of neonatal cerebral ventricles in 3D ultrasound data combining CNN and CPPN

Preterm neonates are highly likely to suffer from ventriculomegaly, a dilation of the Cerebral Ventricular System (CVS). This condition can develop into life-threatening hydrocephalus and is correlated with future neuro-developmental impairments. Consequently, it must be detected and monitored by physicians. In clinical routing, manual 2D measurements are performed on 2D ultrasound (US) images to estimate the CVS volume but this practice is imprecise due to the unavailability of 3D information. A way to tackle this problem would be to develop automatic CVS segmentation algorithms for 3D US data. In this paper, we investigate the potential of 2D and 3D Convolutional Neural Networks (CNN) to solve this complex task and propose to use Compositional Pattern Producing Network (CPPN) to enable Fully Convolutional Networks (FCN) to learn CVS location. Our database was composed of 25 3D US volumes collected on 21 preterm nenonates at the age of 35.8±1.6 gestational weeks. We found that the CPPN enables to encode CVS location, which increases the accuracy of the CNNs when they have few layers. Accuracy of the 2D and 3D FCNs reached intraobserver variability (IOV) in the case of dilated ventricles with Dice of 0.893±0.008 and 0.886±0.004 respectively (IOV = 0.898±0.008) and with volume errors of 0.45±0.42 cm3 and 0.36±0.24 cm3 respectively (IOV = 0.41±0.05 cm3). 3D FCNs were more accurate than 2D FCNs in the case of normal ventricles with Dice of 0.797±0.041 against 0.776±0.038 (IOV = 0.816±0.009) and volume errors of 0.35±0.29 cm3 against 0.35±0.24 cm3 (IOV = 0.2±0.11 cm3). The best segmentation time of volumes of size 320×320×320 was obtained by a 2D FCN in 3.5±0.2 s.

Automated brainstem volumetry can aid in the diagnostics of parkinsonian disorders

IntroductionSeparating progressive supranuclear palsy (PSP) from Parkinson's disease (PD) and multiple system atrophy (MSA) is often challenging in early disease but is important for appropriate management. Magnetic resonance imaging (MRI) can aid the diagnostics and manual 2D measurements are often used. However, new fully automatic brainstem volumetry could potentially be more accurate and increase availability of brainstem metrics. MethodsClinical 3D T1-weighted MRI were obtained from 196 consecutive patients; 29 PSP, 27 MSA, 140 PD. Midbrain-pons ratio and magnetic resonance parkinsonism index (MRPI) 1.0 and 2.0 were manually calculated, and intra-rater and inter-rater reliability was assessed. FreeSurfer was used to automatically segment brainstem substructures, normalized to the intracranial volume. The robustness of the automated analysis was evaluated in 3 healthy controls. The diagnostic accuracy of the brainstem biomarkers was assessed using receiver operating characteristic curves. ResultsAutomatic brainstem volumetry had good repeatability/reproducibility with intra-scanner coefficient of variation 0.3–5.5% and inter-scanner coefficient of variation 0.9–8.4% in the different brainstem regions. Midbrain volume performs better than planimetric measurements in separating PSP from PD (Area under the curve (AUC) 0.90 compared with 0.81 for midbrain-pons ratio (p = 0.019), 0.77 for MRPI 1.0 (p = 0.007) and 0.81 for MRPI 2.0 (p = 0.021)). Midbrain volume performed on par with planimetry for separation between PSP and MSA. ConclusionAutomatic brainstem segmentation is robust and shows promising diagnostic performance in separating PSP from PD and MSA. If further developed, it could play a role in diagnosing PSP and could potentially be used as an outcome in clinical trials.

Computer-Assisted Three-Dimensional Morphology Evaluation of Intracranial Aneurysms

Precise morphologic evaluation is important for intracranial aneurysm (IA) management. At present, clinicians manually measure the IA size and neck diameter on 2-dimensional (2D) digital subtraction angiographic (DSA) images and categorize the IA shape as regular or irregular on 3-dimensional (3D)-DSA images, which could result in inconsistency and bias. We investigated whether a computer-assisted 3D analytical approach could improve IA morphology assessment. Five neurointerventionists evaluated the size, neck diameter, and shape of 39 IAs using current and computer-assisted 3D approaches. In the computer-assisted 3D approach, the size, neck diameter, and undulation index (UI, a shape irregularity metric) were extracted using semiautomated reconstruction of aneurysm geometry using 3D-DSA, followed by IA neck identification and computerized geometry assessment. The size and neck diameter measured using the manual 2D approach were smaller than computer-assisted 3D measurements by 2.01 mm (P < 0.001) and 1.85 mm (P < 0.001), respectively. Applying the definitions of small IAs (<7 mm) and narrow-necked IAs (<4 mm) from the reported data, interrater variation in manual 2D measurements resulted in inconsistent classification of the size of 14 IAs and the necks of 19 IAs. Visual inspection resulted in an inconsistent shape classification for 23 IAs among the raters. Greater consistency was achieved using the computer-assisted 3D approach for size (intraclass correlation coefficient [ICC], 1.00), neck measurements (ICC, 0.96), and shape quantification (UI; ICC, 0.94). Computer-assisted 3D morphology analysis can improve accuracy and consistency in measurements compared with manual 2D measurements. It can also more reliably quantify shape irregularity using the UI. Future application of computer-assisted analysis tools could help clinicians standardize morphology evaluations, leading to more consistent IA evaluations.

Computer-Generated, Three-Dimensional Spine Model From Biplanar Radiographs: A Validity Study in Idiopathic Scoliosis Curves Greater Than 50 Degrees

Study DesignReproducibility study of SterEOS 3-dimensional (3D) software in large, idiopathic scoliosis (IS) spinal curves. ObjectiveTo determine the accuracy and reproducibility of various 3D, software-generated radiographic measurements acquired from a 2-dimensional (2D) imaging system. Summary of Background DataSterEOS software allows a user to reconstruct a 3D spinal model from an upright, biplanar, low-dose, X-ray system. The validity and internal consistency of this system have not been tested in large IS curves. MethodsEOS images from 30 IS patients with curves greater than 50° were collected for analysis. Three observers blinded to the study protocol conducted repeated, randomized, manual 2D measurements, and 3D software generated measurements from biplanar images acquired from an EOS Imaging system. Three-dimensional measurements were repeated using both the Full 3D and Fast 3D guided processes. A total of 180 (120 3D and 60 2D) sets of measurements were obtained of coronal (Cobb angle) and sagittal (T1–T12 and T4–T12 kyphosis; L1–S1 and L1–L5; and pelvic tilt, pelvic incidence, and sacral slope) parameters. Intra-class correlation coefficients were compared, as were the calculated differences in values generated by SterEOS 3D software and manual 2D measurements. The 95% confidence intervals of the mean differences in measures were calculated as an estimate of reproducibility. ResultsAverage intra-class correlation coefficients were excellent: 0.97, 0.97, and 0.93 for Full 3D, Fast 3D, and 2D measures, respectively (p = .11). Measurement errors for some sagittal measures were significantly lower with the 3D techniques. Both the Full 3D and Fast 3D techniques provided consistent measurements of axial plane vertebral rotation. ConclusionsSterEOS 3D reconstruction spine software creates reproducible measurements in all 3 planes of deformity in curves greater than 50°. Advancements in 3D scoliosis imaging are expected to improve our understanding and treatment of idiopathic scoliosis.

Clinical validation of coronal and sagittal spinal curve measurements based on three-dimensional vertebra vector parameters

For many decades, visualization and evaluation of three-dimensional (3D) spinal deformities have only been possible by two-dimensional (2D) radiodiagnostic methods, and as a result, characterization and classification were based on 2D terminologies. Recent developments in medical digital imaging and 3D visualization techniques including surface 3D reconstructions opened a chance for a long-sought change in this field. Supported by a 3D Terminology on Spinal Deformities of the Scoliosis Research Society, an approach for 3D measurements and a new 3D classification of scoliosis yielded several compelling concepts on 3D visualization and new proposals for 3D classification in recent years. More recently, a new proposal for visualization and complete 3D evaluation of the spine by 3D vertebra vectors has been introduced by our workgroup, a concept, based on EOS 2D/3D, a groundbreaking new ultralow radiation dose integrated orthopedic imaging device with sterEOS 3D spine reconstruction software. Comparison of accuracy, correlation of measurement values, intraobserver and interrater reliability of methods by conventional manual 2D and vertebra vector-based 3D measurements in a routine clinical setting. Retrospective, nonrandomized study of diagnostic X-ray images created as part of a routine clinical protocol of eligible patients examined at our clinic during a 30-month period between July 2007 and December 2009. In total, 201 individuals (170 females, 31 males; mean age, 19.88 years) including 10 healthy athletes with normal spine and patients with adolescent idiopathic scoliosis (175 cases), adult degenerative scoliosis (11 cases), and Scheuermann hyperkyphosis (5 cases). Overall range of coronal curves was between 2.4 and 117.5°. Analysis of accuracy and reliability of measurements was carried out on a group of all patients and in subgroups based on coronal plane deviation: 0 to 10° (Group 1; n=36), 10 to 25° (Group 2; n=25), 25 to 50° (Group 3; n=69), 50 to 75° (Group 4; n=49), and above 75° (Group 5; n=22). All study subjects were examined by EOS 2D imaging, resulting in anteroposterior (AP) and lateral (LAT) full spine, orthogonal digital X-ray images, in standing position. Conventional coronal and sagittal curvature measurements including sagittal L5 vertebra wedges were determined by 3 experienced examiners, using traditional Cobb methods on EOS 2D AP and LAT images. Vertebra vector-based measurements were performed as published earlier, based on computer-assisted calculations of corresponding spinal curvature. Vertebra vectors were generated by dedicated software from sterEOS 3D spine models reconstructed from EOS 2D images by thesame three examiners. Manual measurements were performed by each examiner, thrice for sterEOS 3D reconstructions and twice for vertebra vector-based measurements. Means comparison ttest, Pearson bivariate correlation analysis, reliability analysis by intraclass correlation coefficients for intraobserver reproducibility and interrater reliability were performed using SPSS v16.0 software. In comparison with manual 2D methods, only small and nonsignificant differences were detectable in vertebra vector-based curvature data for coronal curves and thoracic kyphosis, whereas the found difference in L1-L5 lordosis values was shown to be strongly related to the magnitude of corresponding L5 wedge. Intraobserver reliability was excellent for both methods, and interrater reproducibility was consistently higher for vertebra vector-based methods that was also found to be unaffected by the magnitude of coronal curves or sagittal plane deviations. Vertebra vector-based angulation measurements could fully substitute conventional manual 2D measurements, with similar accuracy and higher intraobserver reliability and interrater reproducibility. Vertebra vectors represent a truly 3D solution for clear and comprehensible 3D visualization of spinal deformities while preserving crucial parametric information for vertebral size, 3D position, orientation, and rotation. The concept of vertebra vectors may serve as a starting point to a valid and clinically useful alternative for a new 3D classification of scoliosis.

Automatic polyp detection and measurement with computed tomographic colonography: A phantom study

PurposeThe purpose of this study is to assess the performance of computer-aided detection (CAD) software in detecting and measuring polyps for CT Colonography, based on an in vitro phantom study.Material and methodsA colon phantom was constructed with a PVC pipe of 3.8 cm diameter. Nine simulated polyps of various sizes (3.2mm-25.4mm) were affixed inside the phantom that was placed in a water bath. The phantom was scanned on a 64-slice CT scanner with tube voltage of 120 kV and current of 205 mAs. Two separate scans were performed, with different slice thickness and reconstruction interval. The first scan (thin) had a slice thickness of 1mm and reconstruction interval 0.5mm. The second scan (thick) had a slice thickness of 2mm and reconstruction interval of 1mm. Images from both scans were processed using CT Colonography software that automatically segments the colon phantom and applies CAD that automatically highlights and provides the size (maximum and minimum diameters, volume) of each polyp. Two readers independently measured each polyp (two orthogonal diameters) using both 2D and 3D views. Readers’ manual measurements (diameters) and automatic measurements from CAD (diameters and volume) were compared to actual polyp sizes as measured by mechanical calipers.ResultsAll polyps except the smallest (3.2mm) were detected by CAD. CAD achieved 100% sensitivity in detecting polyps ≥6mm. Mean errors in CAD automated volume measurements for thin and thick slice scans were 8.7% and 6.8%, respectively. Almost all CAD and manual readers’ 3D measurements overestimated the size of polyps to variable extent. Both over- and underestimation of polyp sizes were observed in the readers’ manual 2D measurements. Overall, Reader 1 (expert) had smaller mean error than Reader 2 (non-expert).ConclusionCAD provided accurate size measurements for all polyps, and results were comparable to the two readers' manual measurements

Manual and Automated Polyp Measurement: Comparison of CT Colonography With Optical Colonoscopy

The purpose of this study was to assess (1) the agreement of two-dimensional (2D) and three-dimensional (3D) manual and automated polyp linear diameter measurements at CT colonography (CTC), with optical colonoscopic equivalents and (2) intraobserver and interobserver agreement of the CTC measurements. Using the same CTC system, two radiologists independently measured the maximum linear diameter of 44 polyps (reference size 3-15 mm) matched on CTC and optical colonoscopy: manual 2D optimized multiplanar reformatted planes with standard window settings (level 1500 HU, width -200 HU), manual 3D measurement with software calipers and automated 3D measurement with software. After 2 weeks, polyps were measured again. Compatibility of CTC measurement with that of optical colonoscopy and measurement reproducibility was assessed statistically. In the manual measurement, 44 polyps were analyzed and 41 in automated measurement; three polyps could not be extracted. Although the measurement difference was noted for automated, manual 3D, and manual 2D measurements, statistically supported agreement with optical colonoscopic measurement was noted only with manual 2D measurement for both observers. However, 95% limits of agreement were wide for all the measurement methods. When categorized according to the optical colonoscopic measurement, manual 2D, 3D, and automated measurements showed "good" agreement. Although intraobserver and interobserver agreement was good with manual measurement, intraobserver and interobserver agreement was excellent with automated measurement. Manual 2D measurements demonstrated trends of better approximation to optical colonoscopy measurements than manual 3D or automated measurements. And automated measurement eliminated intraobserver and interobserver variability. For noninvasive CTC surveillance, manual 2D measurements are expected to measure medium-sized polyps with sufficient agreement with optical colonoscopic measurements and excellent intraobserver and interobserver variability, especially if combined with automated measurement.

CT Colonography: Automated Measurement of Colonic Polyps Compared with Manual Techniques—Human in Vitro Study

To prospectively investigate the relative accuracy and reproducibility of manual and automated computer software measurements by using polyps of known size in a human colectomy specimen. Institutional review board approval was obtained for the study; written consent for use of the surgical specimen was obtained. A colectomy specimen containing 27 polyps from a 16-year-old male patient with familial adenomatous polyposis was insufflated, submerged in a container with solution, and scanned at four-section multi-detector row computed tomography (CT). A histopathologist measured the maximum dimension of all polyps in the opened specimen. Digital photographs and line drawings were produced to aid CT-histologic measurement correlation. A novice (radiographic technician) and an experienced (radiologist) observer independently estimated polyp diameter with three methods: manual two-dimensional (2D) and manual three-dimensional (3D) measurement with software calipers and automated measurement with software (automatic). Data were analyzed with paired t tests and Bland-Altman limits of agreement. Seven polyps (<or=6-mm diameter) could not be extracted by using the software; 20 polyps (5-15-mm diameter) remained for analysis. Automated measurement was not significantly different from histologic size for the experienced reader (mean difference, 0.63 mm; P=.06) or novice reader (mean difference, 0.58 mm; P=.12). With manual 2D measurement and manual 3D measurement, the experienced reader (1.21-mm mean difference, P<.001, and 0.68-mm mean difference, P=.03, respectively) and novice reader (1.54-mm mean difference, P<.001, and 0.84-mm mean difference, P=.002, respectively) significantly underestimated polyp size. Interobserver agreement was good and similar for all three methods (95% limits of agreement span, approximately 2.5 mm). Intraobserver agreement was related to reader experience, with differences of up to 2.5 mm within expected limits of agreement. For polyps smaller than 1 cm, measurement differences of up to 2.5 mm are within the expected limits of inter- and intraobserver agreement for all measurement techniques. Automated and manual 3D polyp measurements are more accurate than manual 2D measurements.