Development of a semi-automated tool to measure fetal abdominal wall thickness during ultrasound at 20 weeks' gestation

OBJECTIVES

To develop a semi-automated tool for measuring fetal abdominal wall thickness (AWT). To validate the software using images captured by other centers and create a nomogram for fetal AWT between 18 and 20 weeks.

METHODS

A semiautomated tool that measured AWT was developed using images captured at the routine 20-week morphology scan. The software was developed using digital images captured routinely during scans of low-risk women. Inter- and intraobserver reliability was assessed between manual and semi-automated measures. The tool was validated using images acquired from other centers. Linear regression and quadratic polynomials were used to create a nomogram for AWT.

RESULTS

The semi-automated tool was able to measure AWT in all images. Interoperator reliability was 0.90 and 0.97 (P < 0.05) for manual and semi-automated methods, respectively. Measurement agreement varied between three operators from moderate to excellent (0.77, 0.87, 0.92), with overall agreement being good (0.85). The tool could be successfully applied to 89% of images from other centers. A nomogram was generated for AWT measurements of fetuses at 18-20 weeks in normal, low risk mothers.

CONCLUSION

Semi-automated measurement of AWT was feasible using images captured during the routine 20-week scan. This approach had lower inter- and intraobserver variability compared to manual measurement.

The Comparison of Convolutional Neural Networks and the Manual Measurement of Cobb Angle in Adolescent Idiopathic Scoliosis

STUDY DESIGN

Comparative study.

OBJECTIVE

To compare manual and deep learning-based automated measurement of Cobb angle in adolescent idiopathic scoliosis.

METHODS

We proposed a fully automated framework to measure the Cobb angle of AIS patients. Whole-spine images of 500 AIS individuals were collected. 200 digital radiographic (DR) images were labeled manually as training set, and the remaining 300 images were used to validate by mean absolute error (MAE), Pearson or spearman correlation coefficients, and intra/interclass correlation coefficients (ICCs). The relationship between accuracy of vertebral boundary identification and the subjective image quality score was evaluated.

RESULTS

The PT, MT, and TL/L Cobb angles were measured by the automated framework within 300 milliseconds. Remarkable 2.92° MAE, .967 ICC, and high correlation coefficient (r = .972) were obtained for the major curve. The MAEs of PT, MT, and TL/L were 3.04°, 2.72°, and 2.53°, respectively. The ICCs of these 3 curves were .936, .977, and .964, respectively. 88.7% (266/300) of cases had a difference range of ±5°, with 84.3% (253/300) for PT, 89.7% (269/300) for MT, and 93.0% (279/300) for TL/L. The decreased bone/soft tissue contrast (2.94 vs 3.26; P=.039) and bone sharpness (2.97 vs 3.35; P=.029) were identified in the images with MAE exceeding 5°.

CONCLUSION

The fully automated framework not only identifies the vertebral boundaries, vertebral sequences, the upper/lower end vertebras and apical vertebra, but also calculates the Cobb angle of PT, MT, and TL/L curves sequentially. The framework would shed new light on the assessment of AIS curvature.

Automated 2-Dimensional Measurement of Vestibular Schwannoma: Validity and Accuracy of an Artificial Intelligence Algorithm

OBJECTIVE

Validation of automated 2-dimensional (2D) diameter measurements of vestibular schwannomas on magnetic resonance imaging (MRI).

STUDY DESIGN

Retrospective validation study using 2 data sets containing MRIs of vestibular schwannoma patients.

SETTING

University Hospital in The Netherlands.

METHODS

Two data sets were used, 1 containing 1 scan per patient (n = 134) and the other containing at least 3 consecutive MRIs of 51 patients, all with contrast-enhanced T1 or high-resolution T2 sequences. 2D measurements of the maximal extrameatal diameters in the axial plane were automatically derived from a 3D-convolutional neural network compared to manual measurements by 2 human observers. Intra- and interobserver variabilities were calculated using the intraclass correlation coefficient (ICC), agreement on tumor progression using Cohen's kappa.

RESULTS

The human intra- and interobserver variability showed a high correlation (ICC: 0.98-0.99) and limits of agreement of 1.7 to 2.1 mm. Comparing the automated to human measurements resulted in ICC of 0.98 (95% confidence interval [CI]: 0.974; 0.987) and 0.97 (95% CI: 0.968; 0.984), with limits of agreement of 2.2 and 2.1 mm for diameters parallel and perpendicular to the posterior side of the temporal bone, respectively. There was satisfactory agreement on tumor progression between automated measurements and human observers (Cohen's κ = 0.77), better than the agreement between the human observers (Cohen's κ = 0.74).

CONCLUSION

Automated 2D diameter measurements and growth detection of vestibular schwannomas are at least as accurate as human 2D measurements. In clinical practice, measurements of the maximal extrameatal tumor (2D) diameters of vestibular schwannomas provide important complementary information to total tumor volume (3D) measurements. Combining both in an automated measurement algorithm facilitates clinical adoption.

Remote and automated high-throughput powder diffraction measurements enabled by a robotic sample changer at SSRL beamline 2-1

The general-purpose powder diffractometer beamline (BL2-1) at the Stanford Synchrotron Radiation Lightsource (SSRL) is described. The evolution of design and performance of BL2-1 are presented, in addition to current operating specifications, applications and measurement capabilities. Recent developments involve a robotic sample changer enabling high-throughput X-ray diffraction measurements, applicable to mail-in and remote operations. In situ and operando capabilities to measure samples with different form factors (e.g. capillary, flat plate or thin film, and transmission) and under variable experimental conditions are discussed. Several example datasets and accompanying Rietveld refinements are presented.

B3X: a novel efficient algorithm for accurate automated auscultatory blood pressure estimation

Objective.The auscultatory technique is still considered the most accurate method for non-invasive blood pressure (NIBP) measurement, although its reliability depends on operator's skills. Various methods for automated Korotkoff sounds analysis have been proposed for reliable estimation of systolic (SBP) and diastolic (DBP) blood pressures. To this aim, very complex methodologies have been presented, including some based on artificial intelligence (AI). This study proposes a relatively simple methodology, named B3X, to estimate SBP and DBP by processing Korotkoff sounds recordings acquired during an auscultatory NIBP measurement.Approach.The beat-by-beat change in morphology of adjacent Korotkoff sounds is evaluated via their cross-correlation. The time series of the beat-by-beat cross-correlation and its first derivative are analyzed to locate the timings of SBP and DBP values. Extensive tests were performed on a public database of 350 annotated measurements, and the performance was evaluated according to the BHS, AAMI/ANSI, and International Organization for Standardization (ISO) quality standards.Main results.The proposed approach achieved 'A' scores for SBP and DBP in the BHS grading system, and passed the quality tests of AAMI/ANSI and ISO standards. The B3X algorithm outperformed two well-established algorithms for oscillometric NIBP measurement in both SBP and DBP estimation. It also outperformed four AI-based algorithms in DBP estimation, while providing comparable performance for SBP, at the cost of a much lower computational burden. The full code of the B3X algorithm is provided in a public repository.Significance.The very good performances ensured by the proposed B3X algorithm, at a low computational cost and without the need for parameter training, support its direct implementation into clinical blood pressure (BP) monitoring devices. The results of this study pave the way for solving/overcoming the trade-off between the accuracy of the auscultatory technique and the objectivity of oscillatory measurements, by bringing an automated auscultatory BP measurement method in clinical practice.

Automated measurement of infant and mother Duchenne facial expressions in the Face-to-Face/Still-Face

Although still-face effects are well-studied, little is known about the degree to which the Face-to-Face/Still-Face (FFSF) is associated with the production of intense affective displays. Duchenne smiling expresses more intense positive affect than non-Duchenne smiling, while Duchenne cry-faces express more intense negative affect than non-Duchenne cry-faces. Forty 4-month-old infants and their mothers completed the FFSF, and key affect-indexing facial Action Units (AUs) were coded by expert Facial Action Coding System coders for the first 30 s of each FFSF episode. Computer vision software, automated facial affect recognition (AFAR), identified AUs for the entire 2-min episodes. Expert coding and AFAR produced similar infant and mother Duchenne and non-Duchenne FFSF effects, highlighting the convergent validity of automated measurement. Substantive AFAR analyses indicated that both infant Duchenne and non-Duchenne smiling declined from the FF to the SF, but only Duchenne smiling increased from the SF to the RE. In similar fashion, the magnitude of mother Duchenne smiling changes over the FFSF were 2-4 times greater than non-Duchenne smiling changes. Duchenne expressions appear to be a sensitive index of intense infant and mother affective valence that are accessible to automated measurement and may be a target for future FFSF research.

Towards Automated Measurement of As-Built Components Using Computer Vision

Regular inspections during construction work ensure that the completed work aligns with the plans and specifications and that it is within the planned time and budget. This requires frequent physical site observations to independently measure and verify the completion percentage of the construction progress performed over periods of time. The current computer vision techniques for measuring as-built elements predominantly employ three-dimensional laser scanning or three-dimensional photogrammetry modeling to ascertain the geometric properties of as-built elements on construction sites. Both techniques require data acquisition from several positions and angles to generate sufficient information about the element's coordinates, making the deployment of these techniques on dynamic construction project sites challenging. This paper proposes a pipeline for automating the measurement of as-built components using artificial intelligence and computer vision techniques. The pipeline requires a single image obtained with a stereo camera system to measure the sizes of selected objects or as-built components. The results in this work were demonstrated by measuring the sizes of concrete walls and columns. The novelty of this work is attributed to the use of a single image and a single target for developing a fully automated computer vision-based method for measuring any given object. The proposed solution is suitable for use in measuring the sizes of as-built components in built assets. It has the potential to be further developed and integrated with building information modelling applications for use on construction projects for progress monitoring.

Evaluation of a novel moving threshold gating strategy for assessment of reticulated platelets in dogs using the ADVIA 2120 analyzer

BACKGROUND

A novel method using a moving threshold (r-PLTmt) to determine canine r-PLTs (reticulated platelets) has been introduced for ADVIA 2120 software v6.11.7.

OBJECTIVES

We aimed to evaluate absolute (ar-PLTmt) and percent (%r-PLTmt) prior to and after visual inspection of scattergrams (ar-PLTmtv, %rPLTmtv) compared with flow cytometry (flow) and to determine reference intervals (RIs) in 120 dogs.

METHODS

For method comparison, 42 blood samples of healthy and thrombocytopenic dogs were included. Calculation of Spearman's rho, Bland-Altman, and Passing-Bablok analysis was performed. Coefficients of variation (CVs) were determined for three concentration levels.

RESULTS

Moderate correlations between %r-PLTmt and %r-PLTmtv (r_s 0.75-0.76) were seen compared with flow cytometry. The CV for medium %r-PLTs counts assessed with flow cytometry was 12.9%. Comparable CVs were obtained for ar-PLTmt (14.4%) and %r-PLTmt (15.7%), and ar-PLTmtv and %r-PLTmtv (10.9% and 12.9%, respectively). At low and high concentration levels, CVs for % and absolute r-PLTmt/rPLTmtv ranged between 23%-30% and 15%-20%. In patients with microcytic hypochromic erythrocytes, CVs for ar-PLTmt and %r-PLTmt were 36%-66%. Visual inspection of scattergrams resulted in a marked decrease in CV ranging between 15% and 20%. A proportional bias of 10.8% between %r-PLTmt and flow cytometry became lower (9.7%) after visual validation of scattergrams. Passing-Bablok analysis showed proportional and constant error. RIs for r-PLTmt and r-PLTmtv were 0.2%-3.8% and 0.6-10.2 × 10⁹ /L and 0.3%-4.5% and 1.1-10.3 × 10⁹ /L, respectively. Median values for %r-PLTmtv were higher in young adults (≤2 years) than in older dogs (P = 0.03).

CONCLUSIONS

r-PLTmt and r-PLTmtv were moderately correlated with flow cytometry. Visual inspection of scattergrams is recommended.

Novel method for the quantification of rosette area from images of Arabidopsis seedlings grown on agar plates

PREMISE

The agar-based culture of Arabidopsis seedlings is widely used for quantifying root traits. Shoot traits are generally overlooked in these studies, probably because the rosettes are often askew. A technique to assess the shoot surface area of seedlings grown inside agar culture dishes would facilitate simultaneous root and shoot phenotyping.

METHODS

We developed an image processing workflow in Python that estimates rosette area of Arabidopsis seedlings on agar culture dishes. We validated this method by comparing its output with other metrics of seedling growth. As part of a larger study on genetic variation in plant responses to nitrogen form and concentration, we measured the rosette areas from more than 2000 plate images.

RESULTS

The rosette area measured from plate images was strongly correlated with the rosette area measured from directly overhead and moderately correlated with seedling mass. Rosette area in the large image set was significantly influenced by genotype and nitrogen treatment. The broad-sense heritability of leaf area measured using this method was 0.28.

DISCUSSION

These results indicated that this approach for estimating rosette area produces accurate shoot phenotype data. It can be used with image sets for which other methods of leaf area quantification prove unsuitable.

Deep learning-based image analysis for automated measurement of eyelid morphology before and after blepharoptosis surgery

BACKGROUND AND AIM

Eyelid position and contour abnormality could lead to various diseases, such as blepharoptosis, which is a common eyelid disease. Accurate assessment of eyelid morphology is important in the management of blepharoptosis. We aimed to proposed a novel deep learning-based image analysis to automatically measure eyelid morphological properties before and after blepharoptosis surgery.

METHODS

This study included 135 ptotic eyes of 103 patients who underwent blepharoptosis surgery. Facial photographs were taken preoperatively and postoperatively. Margin reflex distance (MRD) 1 and 2 of the operated eyes were manually measured by a senior surgeon. Multiple eyelid morphological parameters, such as MRD1, MRD2, upper eyelid length and corneal area, were automatically measured by our deep learning-based image analysis. Agreement between manual and automated measurements, as well as two repeated automated measurements of MRDs were analysed. Preoperative and postoperative eyelid morphological parameters were compared. Postoperative eyelid contour symmetry was evaluated using multiple mid-pupil lid distances (MPLDs).

RESULTS

The intraclass correlation coefficients (ICCs) between manual and automated measurements of MRDs ranged from 0.934 to 0.971 (p < .001), and the bias ranged from 0.09 mm to 0.15 mm. The ICCs between two repeated automated measurements were up to 0.999 (p < .001), and the bias was no more than 0.002 mm. After surgery, MRD1 increased significantly from 0.31 ± 1.17 mm to 2.89 ± 1.06 mm, upper eyelid length from 19.94 ± 3.61 mm to 21.40 ± 2.40 mm, and corneal area from 52.72 ± 15.97 mm2 to 76.31 ± 11.31mm2 (all p < .001). Postoperative binocular MPLDs at different angles (from 0° to 180°) showed no significant differences in the patients.

CONCLUSION

This technique had high accuracy and repeatability for automatically measuring eyelid morphology, which allows objective assessment of blepharoptosis surgical outcomes. Using only patients' photographs, this technique has great potential in diagnosis and management of other eyelid-related diseases.

Computer-based three-dimensional measurement of carpal alignment: measurement techniques and normal ranges

The three-dimensional carpal alignment was measured in the neutral wrist position in 121 asymptomatic volunteers using computer-based cone-beam CT analysis. Normal values and the reliability of the automated analysis are reported. An analysis software based on segmentation of CT images and mathematical modelling was used to determine several axis variants based on different landmarks and to calculate the intercarpal angles automatically. Twenty wrists were imaged twice to determine intra-observer reliability. Mean values using the preferred axis variants were: scapholunate angle 57° (SD 9°), radiolunate angle 2° (SD 10°), lunocapitate angle -14° (SD 9°). Using alternate axis variants notably changed the angles produced. The intra-observer reliability of the analysis was excellent (mean intraclass correlation coefficient 0.97, SD 0.03). Computer-based CT analysis enables highly reproducible and automated assessment of carpal alignment. This study provides a reference database for measurement techniques and normal carpal angle values in three-dimensional imaging.

Dose-response relationship between World Trade Center dust exposure and hepatic steatosis

BACKGROUND

The World Trade Center (WTC) attack exposed thousands of workers to toxic chemicals that have been linked to liver diseases and cancers. This study examined the relationship between the intensity of WTC dust exposure and the risk of hepatic steatosis in the WTC General Responders Cohort (GRC).

METHODS

All low-dose computed tomography (CT) scans of the chest performed on the WTC GRC between September 11, 2001 and December 31, 2018, collected as part of the World Trade Center Health Program, were reviewed. WTC dust exposure was categorized into five groups based on WTC arrival time. CT liver density was estimated using an automated algorithm, statistics-based liver density estimation from imaging. The relationship between the intensity of WTC dust exposure and the risk of hepatic steatosis was examined using univariate and multivariable regression analyses.

RESULTS

Of the 1788 WTC responders, 258 (14.4%) had liver attenuation less than 40 Hounsfield units (HU < 40) on their earliest CT. Median time after September 11, 2001 and the earliest available CT was 11.3 years (interquartile range: 8.0-14.9 years). Prevalence of liver attenuation less than 40 HU was 17.0% for arrivals on September 11, 2001, 16.0% for arrivals on (September 12, 2001 or September 13, 2001), 10.9% for arrivals on September 14-30, 2001, and 9.0% for arrivals on January 10, 2001 or later (p = 0.0015). A statistically significant trend of increasing liver steatosis was observed with earlier arrival times (p < 0.0001). WTC arrival time remained a significant independent factor for decreased liver attenuation after controlling for other covariates.

CONCLUSIONS

Early arrival at the WTC site was significantly associated with increasing hepatic steatosis.

Automated Pleural Line Detection Based on Radon Transform Using Ultrasound

It is of vital importance to identify the pleural line when performing lung ultrasound, as the pleural line not only indicates the interface between the chest wall and lung, but offers additional diagnostic information. In the current clinical practice, the pleural line is visually detected and evaluated by clinicians, which requires experiences and skills with challenges for the novice. In this study, we developed a computer-aided technique for automated pleural line detection using ultrasound. The method first utilized the Radon transform to detect line objects in the ultrasound images. The relation of the body mass index and chest wall thickness was then applied to estimate the range of the pleural thickness, based on which the pleural line was detected together with the consideration of the ultrasonic properties of the pleural line. The proposed method was validated by testing 83 ultrasound data sets collected from 21 pneumothorax patients. The pleural lines were successfully identified in 76 data sets by the automated method (successful detection rate 91.6%). In those successful cases, the depths of the pleural lines measured by the automated method agreed with those manually measured as confirmed with the Bland-Altman test. The measurement errors were below 5% in terms of the pleural line depth. As a conclusion, the proposed method could detect the pleural line in an automated manner in the defined data set. In addition, the method may potentially act as an alternative to visual inspection after further tests on more diverse data sets are performed in future studies.

Improved Automated Foveal Avascular Zone Measurement in Cirrus Optical Coherence Tomography Angiography Using the Level Sets Macro

Purpose

To evaluate automated measurements of the foveal avascular zone (FAZ) using the Level Sets macro (LSM) in ImageJ as compared with the Cirrus optical coherence tomography angiography (OCTA) inbuilt algorithm and the Kanno–Saitama macro (KSM).

Methods

The eyes of healthy volunteers were scanned four times consecutively on the Zeiss Cirrus HD-OCT 5000 system. The FAZ metrics (area, perimeter, and circularity) were measured manually and automatically by the Cirrus inbuilt algorithm, the KSM, and the LSM. The accuracy and repeatability of all methods and agreement between automated and manual methods were evaluated.

Results

The LSM segmented the FAZ with an average Dice coefficient of 0.9243. Compared with the KSM and the Cirrus inbuilt algorithm, the LSM outperformed them by 0.02 and 0.19, respectively, for Dice coefficients. Both the LSM (intraclass correlation coefficient [ICC] = 0.908; coefficient of variation [CoV] = 9.664%) and manual methods (ICC ≥ 0.921, CoV ≤ 8.727%) showed excellent repeatability for the FAZ area, whereas the other methods presented moderate to good repeatability (ICC ≤ 0.789, CoV ≥ 15.788%). Agreement with manual FAZ area measurement was excellent for both the LSM and KSM but not for the Cirrus inbuilt algorithm (LSM, ICC = 0.930; KSM, ICC = 0.928; Cirrus, ICC = 0.254).

Conclusions

The LSM exhibited greater accuracy and reliability compared to the KSM and inbuilt automated methods and may be an improved and accessible option for automated FAZ segmentation.

Translational Relevance

The LSM may be a suitable automated and customizable tool for FAZ quantification of Cirrus HD-OCT 5000 images, providing results comparable to those for manual measurement.

Automated Ultrasound Measurement of the Inferior Vena Cava: An Animal Study

Because of continuous movement and variation in diameter of the inferior vena cava (IVC) with respiration, the measurements on IVC are labor-intensive and with considerable inter-operator variations. Some computer-assisted techniques have been developed to track the movement of the IVC semi-automatically. However, existing methods predominantly rely on reference marker selection and require many manual inputs. In this study, we developed a cross-correlation (CC)-based method for automated IVC movement tracking and measurement, which requires minimal manual input and avoids manual selection of reference markers. Based on the CC method, two approaches, named direct and relative approaches, were used to calculate the maximum, minimum, and variation of the IVC diameter, and compared with the manual measurement. Fifty-four ultrasound cine-loops collected from nine pigs were tested. The results reveal that both the proposed approaches were well agreed with the manual measurement. The errors of the direct approach were less than 9%, while those of relative approach were as high as 26.7%. It is concluded that the proposed direct approach is superior for IVC diameter measurements, which can be comparable with manual counterpart, serving as an alternative to traditional IVC measurement.

Reproducibility of pelvic sagittal inclination while acquiring radiographs in supine and standing postures

PURPOSE

Pelvic position on the sagittal plane is usually evaluated with the pelvic sagittal inclination (PSI) angle from a single radiograph. However, the reproducibility of pelvic positioning has not been investigated, and thus, the validity of measuring the PSI from a single film/time point is not understood. Herein, the reproducibility of a patient's pelvic positions in supine and standing postures was analyzed.

METHODS

A total of 34 patients who underwent either a pelvic osteotomy or total hip arthroplasty were enrolled in this study. Preoperative radiographs in both supine and standing postures were acquired twice (first X-ray and second X-ray) within 6 months; preoperative computed tomography (CT) images of the full pelvis were also acquired in a supine posture (preop-CT). To eliminate measurement variability, each PSI was automatically measured from radiographs and CT images through the use of CT segmentation and landmark localization followed by intensity-based 2D-3D registration. The absolute difference of PSI among each image was calculated and the intra-class correlation coefficient (ICC) in each posture was also analyzed.

RESULTS

The median absolute differences of PSI in the supine posture were 1.3° between the first and second X-rays, 1.2° between the first X-ray and preop-CT, and 1.3° between the second X-ray and preop-CT. The median absolute difference of PSI in the standing posture was 1.5°. The ICC was 0.965 (95% CI: 0.939-0.981) in supine and 0.977 (95% CI: 0.954-0.988) during standing.

CONCLUSIONS

Pelvic positions in supine and standing postures are reproducible. Thus, measuring the PSI from a single radiograph is reliable.

A Novel Approach for Automated Eyelid Measurements in Blepharoptosis Using Digital Image Analysis

Purpose: To propose a novel approach for automated measurements of margin reflex distance (MRD) using digital image analysis and to evaluate the agreement between automated and manual measurements of MRD. Materials and Methods: This observational study included 132 eyes of 66 volunteers referred to an oculoplastic clinic for blepharoptosis. Preoperative facial photographs of participants were taken. MRD1 and MRD2 were measured manually by a senior surgeon and automatically by our image-based algorithm. Correlation analyses and Bland-Altman analyses were performed to evaluate the agreement between the two measurements. Results: A strong positive correlation was observed between automated and manual MRD1 measurements, with Spearman's r = 0.968 (95% confidence interval [CI] = 0.949-0.976; P < .001) and intraclass correlation coefficient (ICC) = 0.966 (95% CI = 0.953-0.976; P < .001). The bias between automated and manual MRD1 measurements was 0.02 mm (95% CI = -0.06-0.10 mm), with 95% limits of agreement (LoA) = -0.88 to 0.92 mm. Agreement also existed in MRD2 measurements, with Spearman's r = 0.803 (95% CI = 0.716-0.865; P < .001), ICC = 0.833 (95% CI = 0.772-0.879; P < .001), and bias = 0.34 mm (95% CI = 0.26-0.42 mm), 95% LoA = -0.54 to 1.22 mm. Conclusions: Automated eyelid measurements in blepharoptosis using the image-based approach compare favorably with clinical manual measurements. This novel approach allows an objective assessment of ptosis with high accuracy.

Automated Measurement of the Foveal Avascular Zone in Swept-Source Optical Coherence Tomography Angiography Images

Purpose

The purpose of this study was to evaluate automated measurement of the foveal avascular zone (FAZ) area using the Kanno-Saitama macro (KSM) software in Image J with swept-source optical coherence tomography angiography (SS-OCTA) images.

Methods

In this cross-sectional study, one photographer scanned the macular area (3 × 3 mm) of healthy volunteers twice on the same day, at the same time. The FAZ area was measured from the en face image of the superficial retinal layer by two masked examiners, using the KSM and the Advanced Retina Imaging (ARI)-network method in Carl Zeiss online analysis. Intra- and interscan reproducibility and FAZ area were compared among the methods.

Results

Forty eyes of 22 healthy volunteers were included in the analysis. The mean ± SD age of the subjects was 34.6 ± 12.4 years. Intra- and interscan intraclass coefficients ranged from 0.997 to 1.000 and 0.989 to 0.995, respectively. The mean FAZ area was 0.264 ± 0.08 mm² by the KSM, 0.245 ± 0.08 mm² by the ARI, and 0.281 ± 0.09 mm² by the manual method. The mean difference between the KSM and manual methods was 0.015 mm², which was significantly smaller than the mean difference between the ARI and manual methods (0.034 mm²; P < 0.001).

Conclusions

Automated determination of the FAZ area is feasible and yields results comparable to those obtained by manual measurement. The FAZ area measured with the KSM program is less user dependent and could potentially contribute to our understanding of the pathophysiology of various retinal diseases, particularly underlying vascular diseases.

Translational Relevance

This study demonstrates a novel automated determination of the FAZ area using the Image J macro program in SS-OCTA images. This program was feasible and yields results comparable to those obtained by manual measurement.

Automated Identification and Localization of the Inferior Vena Cava Using Ultrasound: An Animal Study

Ultrasound measurement of the inferior vena cava (IVC) is widely implemented in the clinic. However, the process is time consuming and labor intensive, because the IVC diameter is continuously changing with respiration. In addition, artificial errors and intra-operator variations are always considerable, making the measurement inconsistent. Research efforts were recently devoted to developing semiautomated methods. But most required an initial identification of the IVC manually. As a first step toward fully automated IVC measurement, in this paper, we present an intelligent technique for automated IVC identification and localization. Forty-eight ultrasound data sets were collected from eight pigs, each of which included two frames in B-mode and color mode (C-mode) collected at the inspiration, and two cine loops in B-mode and C-mode. Static and dynamic automation algorithms were applied to the data sets for identifying and localizing the IVC. The results were evaluated by comparing with the manual measurement of experienced clinicians. The automated approaches successfully identified the IVC in 47 cases (success rate: 97.9%). The automated localization of the IVC is close to the manual counterpart, with the difference within one diameter. The automatically measured diameters are close to those measured manually, with most differences below 15%. It is revealed that the proposed method can automatically identify the IVC with high success rate and localize the IVC with high accuracy. But the study with high accuracy was conducted under good control and without considering difficult cases, which deserve future explorations. The method is a first step toward fully automated IVC measurement, which is suitable for point-of-care applications.

Comparison of Manual and Automated Measurements of Tracheobronchial Airway Geometry in Three Balb/c Mice

Mammalian lungs are comprised of large numbers of tracheobronchial airways that transition from the trachea to alveoli. Studies as wide ranging as pollutant deposition and lung development rely on accurate characterization of these airways. Advancements in CT imaging and the value of computational approaches in eliminating the burden of manual measurement are providing increased efficiency in obtaining this geometric data. In this study, we compare an automated method to a manual one for the first six generations of three Balb/c mouse lungs. We find good agreement between manual and automated methods and that much of the disagreement can be attributed to method precision. Using the automated method, we then provide anatomical data for the entire tracheobronchial airway tree from three Balb/C mice. Anat Rec, 2017. © 2017 Wiley Periodicals, Inc. Anat Rec, 300:2046-2057, 2017. © 2017 Wiley Periodicals, Inc.

Carotid inter-adventitial diameter is more strongly related to plaque score than lumen diameter: An automated tool for stroke analysis

PURPOSE

To compare the strength of correlation between automatically measured carotid lumen diameter (LD) and interadventitial diameter (IAD) with plaque score (PS).

METHODS

Retrospective study on a database of 404 common carotid artery B-mode sonographic images from 202 diabetic patients. LD and IAD were computed automatically using an advanced computerized edge detection method and compared with two distinct manual measurements. PS was computed by adding the maximal thickness in millimeters of plaques in segments taken from the internal carotid artery, bulb, and common carotid artery on both sides.

RESULTS

The coefficient of correlation was 0.19 (p < 0.007) between LD and PS, and 0.25 (p < 0.0006) between IAD and PS. After excluding 10 outliers, coefficient of correlation was 0.25 (p < 0.0001) between LD and PS, and 0.38 (p < 0.0001) between IAD and PS. The precision of merit of automated versus the two manual measurements was 96.6% and 97.2% for LD, and 97.7% and 98.1%, for IAD, respectively.

CONCLUSIONS

Our automated measurement system gave satisfying results in comparison with manual measurements. Carotid IAD was more strongly correlated to PS than carotid LD in this population sample of Japanese diabetic patients.

QT dynamics evaluated on fully automated QT measurement in children

BACKGROUND

The association between QT interval and heart rate (HR), QT dynamics, has been reported to vary greatly between individuals. We investigated QT dynamics using fully automated QT interval measurement with a commercially available multifunctional electrocardiogram (ECG) recorder.

METHODS

The study group included 17 otherwise healthy subjects (mean age, 12.7 years; 11 girls, 6 boys), who were undergoing exercise test for arrhythmia evaluation. The subjects had single premature ventricular contraction.

RESULTS

Mean corrected QT interval (Fridericia) at rest was 412 ± 19 ms (male, 408 ± 20 ms; female, 414 ± 19 ms), manually measured with a digitizer, using the tangent method. We assessed QT interval/HR slope during the whole exercise test, the exercise phase, and the recovery from exercise phase; the slopes were calculated offline after excluding wide QRS complex and were -1.15 ± 0.26 (r(2) = 0.65), -1.18 ± 0.30 (r(2) = 0.62), and -1.11 ± 0.25 (r(2) = 0.70), respectively. Estimated QT interval at HR 60 beats/min (QT60) was calculated using the regression line formula and was 383 ± 24 ms, 387 ± 28 ms, and 375 ± 21 ms, respectively. QT60 of the total exercise test correlated with the corrected QT interval at rest (P = 0.04, r(2) = 0.25).

CONCLUSIONS

Assessment of QT dynamics is feasible on fully automated QT interval measurement with this ECG recorder. Further studies are required in larger populations to confirm the accuracy and precision of QT measurement and QT dynamics using this new multifunctional ECG.

Automated liver elasticity calculation for MR elastography

PURPOSE

MR elastography (MRE) is a phase-contrast MRI technique that is used to quantitatively assess liver stiffness for staging hepatic fibrosis. The current approach requires manual selection of a region of interest (ROI) with good wave quality from which to measure stiffness. The purpose of this work was to develop and evaluate a fully automated approach for measuring hepatic stiffness from MRE images to further reduce measurement variability.

MATERIALS AND METHODS

An automated liver elasticity calculation (ALEC) algorithm was developed to address reader stiffness measurement variability. ALEC has three stages: initial tissue estimation, segmentation, and ROI cleanup. Stiffnesses measured by the algorithm were compared with technicians and an expert radiologist in a set of 121 clinical cases acquired at 1.5 Tesla. Intra-class correlation (ICC), Bland-Altman analysis, and a noninferiority test were performed to evaluate whether the algorithm can be used in place of manual analysis by technicians.

RESULTS

The stiffness measurement difference with the expert was 1.42% ± 11.17% (mean ± standard deviation) for the algorithm and 1.82% ± 13.65% for the technicians. The ICCs were 0.981 and 0.984, respectively. Both the algorithm and technicians were equivalent to the expert within a 5% significance margin (P < 0.01). The algorithm had no failures in the 119 cases that were considered analyzable by the human readers.

CONCLUSION

The results of this study show that the newly developed automated algorithm is able to measure stiffness in clinical liver MRE exams with an accuracy that is equivalent to that of an expert radiologist. ALEC may be useful for analysis of archived data and suitable for performing multi-center studies.

Statistical evaluation of reproducibility of automated ECG measurements: an example from arrhythmogenic right ventricular dysplasia/cardiomyopathy clinic

BACKGROUND

Arrhythmogenic right ventricular dysplasia/cardiomyopathy (ARVD/C) is characterized by delay in depolarization of the right ventricle, detected by prolonged terminal activation duration (TAD) in V1-V3. However, manual ECG measurements have shown moderate-to-low intra- and inter-reader agreement. The goal of this study was to assess reproducibility of automated ECG measurements in the right precordial leads.

METHODS

Pairs of ECGs recorded in the same day from Johns Hopkins ARVD/C Registry participants [n=247, mean age 35.2±15.6 y, 58% men, 92% whites, 11(4.5%) with definite ARVD/C] were retrospectively analyzed. QRS duration, intrinsicoid deflection, TAD, and T-wave amplitude in the right precordial leads, as well as averaged across all leads QRS duration, QRS axis, T axis, QTc interval, and heart rate was measured automatically, using 12SL TM algorithm (GE Healthcare, Wauwatosa, WI, USA). Intrinsicoid deflection was measured as the time from QRS complex onset to the alignment point of the QRS complex. TAD was calculated as the difference between QRS duration and intrinsicoid in V1, V2, V3. Reproducibility was quantified by Bland-Altman analysis (bias with 95% limits of agreement), Lin's concordance coefficient, and Bradley-Blackwood procedure.

RESULTS

Bland-Altman analysis revealed satisfactory reproducibility of tested parameters. V1 QRS duration bias was -0.10ms [95% limits of agreement -12.77 to 12.56ms], V2 QRS duration bias -0.09ms [-11.13 to 10.96ms]; V1 TAD bias 0.14ms [-13.23 to 13.51ms], V2 TAD bias 0.008ms [-12.42 to 12.44ms].

CONCLUSION

Comprehensive statistical evaluation of reproducibility of automated ECG measurements is important for appropriate interpretation of ECG. Automated ECG measurements are reproducible to within 25%.

An automated inner dimensional measurement system based on a laser displacement sensor for long-stepped pipes

A novel measurement prototype based on a mobile vehicle that carries a laser scanning sensor is proposed. The prototype is intended for the automated measurement of the interior 3D geometry of large-diameter long-stepped pipes. The laser displacement sensor, which has a small measurement range, is mounted on an extended arm of known length. It is scanned to improve the measurement accuracy for large-sized pipes. A fixing mechanism based on two sections is designed to ensure that the stepped pipe is concentric with the axis of rotation of the system. Data are acquired in a cylindrical coordinate system and fitted in a circle to determine diameter. Systematic errors covering arm length, tilt, and offset errors are analyzed and calibrated. The proposed system is applied to sample parts and the results are discussed to verify its effectiveness. This technique measures a diameter of 600 mm with an uncertainty of 0.02 mm at a 95% confidence probability. A repeatability test is performed to examine precision, which is 1.1 μm. A laser tracker is used to verify the measurement accuracy of the system, which is evaluated as 9 μm within a diameter of 600 mm.

Automated versus manual measurement of the QT interval and corrected QT interval

BACKGROUND

The International Conference on Harmonization E14 Guideline specifies detailed assessment of QT interval or corrected QT interval prolongation when developing new drugs. We recently devised new software to precisely measure the QT interval.

METHODS AND RESULTS

The QT intervals of all leads for a selected single heart beat were compared between automated measurement with the new software from Fukuda Denshi and manual measurement. With both automated and manual measurement, QT intervals obtained by the tangent method were shorter than those obtained by the differential threshold method, but the extent of correction was smaller. QT interval data obtained by the differential threshold method were more similar to values obtained by visual measurement than were data obtained by the tangent method, but the extent of correction was larger. Variability was related to the T-wave amplitude and to setting the baseline and tangent in the tangent method, while skeletal muscle potential noise affected the differential threshold method. Drift, low-amplitude recordings, and T-wave morphology were problems for both methods. Among the 12 leads, corrections were less frequent for leads II and V(3) -V(6) .

CONCLUSION

We conclude that, for a thorough assessment of the QT/QTc interval, the tangent method or the differential threshold method appears to be suitable because of smaller interreader differences and better reproducibility. Correction of data should be done by readers who are experienced in measuring the QT interval. It is also important for electrocardiograms to have little noise and for a suitable heart rate and appropriate leads to be selected.

Automated quantification of aortic regurgitant volume and regurgitant fraction using the digital colour Doppler velocity profile integration method in patients with aortic regurgitation

BACKGROUND

The recently introduced automated cardiac flow measurement (ACM) technique provides a quick and an accurate automated calculation of stroke volume and cardiac output. This is obtained by spatio-temporal integration of digital Doppler velocity profile data.

OBJECTIVE

To evaluate the use of the ACM method in the non-invasive assessment of aortic regurgitant volume and per cent regurgitant fraction (%RF) in patients with aortic regurgitation.

METHODS

Aortic outflow volume and mitral inflow volume were calculated by the ACM method in 22 patients with isolated aortic regurgitation. Aortic regurgitant volume and %RF were calculated using the following equations: aortic regurgitant volume = [aortic outflow volume] - [mitral inflow volume]; %RF = [aortic regurgitant volume]/[aortic outflow volume] x 100. The results were compared with those obtained using pulsed Doppler cross sectional echocardiography (PD-2D).

RESULTS

Aortic regurgitant volumes measured by the ACM method showed a good correlation with the PD-2D measurements (r = 0.95, y = 0.9x + 3.9, SEE = 8.6 ml); the mean (SD) difference between the two methods was -1.5 (8.5) ml. %RF estimated by the ACM method also correlated well with the values obtained by the PD-2D method (r = 0.91, y = 0.9x + 4.9, SEE = 6.0%); the mean difference between the two methods was -1.5 (6.0)%. Total time required for aortic regurgitant volume (for one cardiac cycle) by the ACM method was significantly shorter than by the PD-2D method (130 (16) v 230 (32) s, p < 0.01).

CONCLUSIONS

The newly developed the ACM method is quick and accurate in the automated assessment of aortic regurgitant volume and per cent regurgitant fraction in patients with isolated aortic regurgitation.