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PubMed2005

Automated acquisition of cryo-electron micrographs for single particle reconstruction on an FEI Tecnai electron microscope.

AutoEM is a software package developed by Zhang et al. [J. Struct. Biol. 1356, 251] for semi-automated acquisition of cryo-electron micrographs from Tecnai series electron microscopes and is used frequently at the lowest level of automation. We report here on the new progress that we have made based on their preliminary work. A fourth low-dose state is created where the system can pre-select all the good holes in a grid square from a single CCD image taken at low magnification, making the system operative at much higher levels of automation. An additional control interface enables the operator to monitor the status of the program and the quality of the data, interact with the program, and direct the execution process according to intermediate results. When data acquisition is in progress, all useful information is automatically saved in certain text files which are easily accessible by a database. More detailed improvements and general advantages are illustrated and discussed. We have started to use the program to perform routine data collection. A number of applications show that the performance of the program is satisfactory and the quality of the micrographs and their power spectra acquired by the program is comparable to those manually collected under the same conditions.

Cryoelectron Microscopy↗
PubMed2006

Automated cryoEM data acquisition and analysis of 284742 particles of GroEL.

One of the goals in developing our automated electron microscopy data acquisition system, Leginon, was to improve both the ease of use and the throughput of the process of acquiring low dose images of macromolecular specimens embedded in vitreous ice. In this article, we demonstrate the potential of the Leginon system for high-throughput data acquisition by describing an experiment in which we acquired images of more than 280,000 particles of GroEL in a single 25 h session at the microscope. We also demonstrate the potential for an automated pipeline for molecular microscopy by showing that these particles can be subjected to completely automated procedures to reconstruct a three-dimensional (3D) density map to a resolution better than 8 A. In generating the 3D maps, we used a variety of metadata associated with the data acquisition and processing steps to sort and select the particles. These metadata provide a number of insights into factors that affect the quality of the acquired images and the resulting reconstructions. In particular, we show that the resolution of the reconstructed 3D density maps improves with decreasing ice thickness. These data provide a basis for assessing the capabilities of high-throughput macromolecular microscopy.

Chaperonin 60↗
PubMed2026

Automated CEAP Classification of Venous Duplex Reports Using Multimodal Artificial Intelligence.

OBJECTIVE: To develop and internally validate a prototype multimodal artificial intelligence system for automated CEAP (Clinical, Etiological, Anatomical and Pathophysiological) classification of venous duplex ultrasound (VDUS) reports, integrating natural language processing of free-text components with computer vision analysis of hand-drawn anatomical diagrams. METHODS: Single centre retrospective observational study using routinely collected clinical data. One thousand consecutive venous duplex ultrasound reports from Cambridge University Hospitals NHS Foundation Trust, UK (July 2024 - May 2025) were labelled according to the CEAP classification, excluding the Etiological component, which could not be reliably determined from duplex reports alone. Transfer learning was applied using ClinicalBERT for text and MobileNetV3 for diagrammatic data. Clinical classes were predicted from request line text. Text- and image-based pathophysiological models were developed for four anatomical territories (Great Saphenous Vein, Small Saphenous Vein, Deep system, Perforators), combined using late fusion with probability averaging. RESULTS: The clinical CEAP model achieved accuracy of 0.91, macro-F1 of 0.82, and macro-AUC of 0.98. Pathophysiological prediction varied, with text models broadly outperforming image models. Fusion yielded heterogeneous benefits, improving SSV performance but reducing Deep system accuracy. The performance of the final pathophysiological CEAP fusion models varied across anatomical territories: accuracy ranged from 0.70-0.92 and macro-AUC from 0.80-0.92. CONCLUSION: This study demonstrates the feasibility of automated CEAP classification from VDUS reports. Despite class imbalance affecting minority class predictions, the strong discriminatory performance validates this multimodal ML model for extracting clinically meaningful information from real-world data. This approach offers potential, pending external validation, to streamline vascular services through automated triage and guideline-compliant decision making.

Artificial intelligence↗
PubMed2025

Evaluating 12 automated, whole-genome sequencing analysis pipelines for Mycobacterium tuberculosis complex: a comparative study.

BACKGROUND: Reliance on complex, custom-built bioinformatics pipelines is a barrier to the implementation of whole-genome sequencing (WGS) of Mycobacterium tuberculosis in high-burden settings in some low-income and middle-income countries (LMICs). Automated analysis pipelines could address this inequity in access to WGS-based diagnostics and surveillance. This study aimed to systematically evaluate the performance and usability of publicly available WGS pipelines for M tuberculosis. METHODS: We identified automated M tuberculosis WGS analysis pipelines through searches of PubMed and GitHub from database inception up to Aug 31, 2024. Accuracy, cost, accessibility, and scalability were assessed for each pipeline. We evaluated the accuracy of genotypic drug susceptibility testing (gDST) using publicly available sequences with phenotypic susceptibility data for 12 antituberculosis drugs. We estimated pooled sensitivity and specificity for each pipeline, across all drugs, by conducting a bivariate meta-analysis, with random effects representing between-drug variability. Lineage classifications were compared, and a previously epidemiologically well-characterised dataset was used to compare measures of genomic relatedness. FINDINGS: Among 28 candidate pipelines, 16 were excluded as they were unmaintained and inexecutable. 12 pipelines (11 compatible with Illumina and four compatible with Nanopore), all free to use, were included for evaluation. Six pipelines processed and stored data remotely, but for five of these six, scalability was limited by the need to upload sequences through web portals. For local processing pipelines, scalability was dependent on substantial local computational resources, data storage capacity, and command-line interfaces that limited user-friendliness. Only one of six remote-processing pipelines removed human DNA sequences before server upload. gDST was similarly accurate across ten of 11 Illumina-compatible pipelines and three of four Nanopore-compatible pipelines. All pipelines classified the main lineages consistently, although there were differences at sublineage resolution. Outputs from three of four pipelines reporting genomic relatedness were compatible with commonly cited single nucleotide polymorphism difference thresholds. INTERPRETATION: Numerous automated analysis pipelines capable of enhancing equity in M tuberculosis WGS are available. Given the overall similarities between the pipelines evaluated in this study in terms of gDST performance, lineage classification, and genomic relatedness inference, non-functional attributes such as availability, accessibility, scalability, and privacy could represent the point of difference for prospective users in LMICs with a high burden of tuberculosis. FUNDING: The Rhodes Trust, Wellcome, Ellison Institute of Technology, and the UK National Institute for Health and Care Research Oxford Biomedical Research Centre.

Mycobacterium tuberculosis↗
PubMed2005

A universal algorithm for an improved finite element mesh generation Mesh quality assessment in comparison to former automated mesh-generators and an analytic model.

The FE-modeling of complex anatomical structures is not solved satisfyingly so far. Voxel-based as opposed to contour-based algorithms allow an automated mesh generation based on the image data. Nonetheless their geometric precision is limited. We developed an automated mesh-generator that combines the advantages of voxel-based generation with improved representation of the geometry by displacement of nodes on the object-surface. Models of an artificial 3D-pipe-section and a skullbase were generated with different mesh-densities using the newly developed geometric, unsmoothed and smoothed voxel generators. Compared to the analytic calculation of the 3D-pipe-section model the normalized RMS error of the surface stress was 0.173-0.647 for the unsmoothed voxel models, 0.111-0.616 for the smoothed voxel models with small volume error and 0.126-0.273 for the geometric models. The highest element-energy error as a criterion for the mesh quality was 2.61x10(-2) N mm, 2.46x10(-2) N mm and 1.81x10(-2) N mm for unsmoothed, smoothed and geometric voxel models, respectively. The geometric model of the 3D-skullbase resulted in the lowest element-energy error and volume error. This algorithm also allowed the best representation of anatomical details. The presented geometric mesh-generator is universally applicable and allows an automated and accurate modeling by combining the advantages of the voxel-technique and of improved surface-modeling.

Algorithms↗
PubMed2004

Automated human frontal lobe identification in MR images based on fuzzy-logic encoded expert anatomic knowledge.

Identification of human brain structures in MR images comprises an area of increasing interest, which also presents numerous methodological challenges. Here we describe a new knowledge-based automated method designed to identify several major brain sulci and then to define the frontal lobes by using the identified sulci as landmarks. To identify brain sulci, sulcal images were generated by morphologic operations and then separated into different components based on connectivity analysis. Subsequently, the individual anatomic features were evaluated by using fuzzy membership functions. The crisp decisions, i.e., the identification of sulci, were made by taking the maximum of the summation of all the membership functions. The identification was designed in a hierarchical order. The longitudinal fissure was extracted first. The left and right central sulci were then identified based on the left and right hemispheres. Next, the lateral sulci were identified based on the central sulci and hemispheres. Finally, the left and right frontal lobes were defined from the two hemispheres. The method was evaluated by visual inspection, comparison with manual segmentation, and comparison with manually volumetric results in references. The average Jaccard similarities of left and right frontal lobes between the automated and manual segmentation were 0.89 and 0.91, respectively. The average Kappa indices of left and right frontal lobes between the automated and manual segmentation were 0.94 and 0.95, respectively. These results show relatively high accuracy of using this novel method for human frontal lobe identification and segmentation.

Algorithms↗
PubMed2006

Technical aspects and evaluation methodology for the application of two automated brain MRI tumor segmentation methods in radiation therapy planning.

The purpose of this study was to design the steps necessary to create a tumor volume outline from the results of two automated multispectral magnetic resonance imaging segmentation methods and integrate these contours into radiation therapy treatment planning. Algorithms were developed to create a closed, smooth contour that encompassed the tumor pixels resulting from two automated segmentation methods: k-nearest neighbors and knowledge guided. These included an automatic three-dimensional (3D) expansion of the results to compensate for their undersegmentation and match the extended contouring technique used in practice by radiation oncologists. Each resulting radiation treatment plan generated from the automated segmentation and from the outlining by two radiation oncologists for 11 brain tumor patients was compared against the volume and treatment plan from an expert radiation oncologist who served as the control. As part of this analysis, a quantitative and qualitative evaluation mechanism was developed to aid in this comparison. It was found that the expert physician reference volume was irradiated within the same level of conformity when using the plans generated from the contours of the segmentation methods. In addition, any uncertainty in the identification of the actual gross tumor volume by the segmentation methods, as identified by previous research into this area, had small effects when used to generate 3D radiation therapy treatment planning due to the averaging process in the generation of margins used in defining a planning target volume.

Algorithms↗
PubMed2006

Analysis of EEG-fMRI data in focal epilepsy based on automated spike classification and Signal Space Projection.

Simultaneous acquisition of EEG and fMRI data enables the investigation of the hemodynamic correlates of interictal epileptiform discharges (IEDs) during the resting state in patients with epilepsy. This paper addresses two issues: (1) the semi-automation of IED classification in statistical modelling for fMRI analysis and (2) the improvement of IED detection to increase experimental fMRI efficiency. For patients with multiple IED generators, sensitivity to IED-correlated BOLD signal changes can be improved when the fMRI analysis model distinguishes between IEDs of differing morphology and field. In an attempt to reduce the subjectivity of visual IED classification, we implemented a semi-automated system, based on the spatio-temporal clustering of EEG events. We illustrate the technique's usefulness using EEG-fMRI data from a subject with focal epilepsy in whom 202 IEDs were visually identified and then clustered semi-automatically into four clusters. Each cluster of IEDs was modelled separately for the purpose of fMRI analysis. This revealed IED-correlated BOLD activations in distinct regions corresponding to three different IED categories. In a second step, Signal Space Projection (SSP) was used to project the scalp EEG onto the dipoles corresponding to each IED cluster. This resulted in 123 previously unrecognised IEDs, the inclusion of which, in the General Linear Model (GLM), increased the experimental efficiency as reflected by significant BOLD activations. We have also shown that the detection of extra IEDs is robust in the face of fluctuations in the set of visually detected IEDs. We conclude that automated IED classification can result in more objective fMRI models of IEDs and significantly increased sensitivity.

Cerebral Cortex↗
PubMed2005

Fully automated synthesis of [18F]fluoromisonidazole using a conventional [18F]FDG module.

We developed a new fully automated method for the synthesis of [18F]fluoromisonidazole ([18F]FMISO) by modifying a commercial FDG synthesizer and its disposable fluid pathway. A three-step procedure was used to prepare the tosylate precursor, 1-(2'-nitro-1'-imidazolyl)-2-O-tetrahydrofuranyl-3-O-toluenesulfonylpropanediol. Using glycerol as the starting material, the precursor was synthesized with a yield of 21%. The optimal labeling conditions for the automated synthesis of [18F]FMISO was 10 mg of precursor in acetonitrile (2 ml heated at 105 degrees C for 360 s, followed by heating at 75 degrees C for 280 s and hydrolysis with 1 N HCl at 105 degrees C for 300 s. Using 3.7 GBq of [18F]F- as a starting activity, [18F]FMISO was obtained with high end-of-synthesis (EOS) radiochemical yields of 58.5+/-3.5% for 60.0+/-5.2 min with high-performance liquid chromatography (HPLC) purification. When solid-phase purification steps were added, the EOS radiochemical yields were 54.5+/-2.8% (337+/-25 GBq/micromol) for 70.0+/-3.8 min (n=10 for each group, decay-corrected). With a high starting radioactivity of 37.0 GBq, we obtained radiochemical yields of 54.4+/-2.9% and 52.8+/-4.2%, respectively (n=3). The solid-phase purification removed unreacted [18F]fluoride and polar impurities before the HPLC procedure. Long-term tests showed a good stability of 98.2+/-1.5%. This new automated synthesis procedure combines high and reproducible yields with the advantage of using a disposable cassette system.

Drug Evaluation, Preclinical↗
PubMed2005

Automated purification of recombinant proteins: combining high-throughput with high yield.

Protein crystallography, mapping protein interactions, and other functional genomic approaches require purifying many different proteins, each of sufficient yield and homogeneity, for subsequent high-throughput applications. To fill this requirement efficiently, there is a need to develop robust, automated, high-throughput protein expression, and purification processes. We developed and compared two alternative workflows for automated purification of recombinant proteins based on expression of bacterial genes in Escherichia coli (E. coli). The first is a filtration separation protocol in which proteins of interest are expressed in a large volume, 800 ml of E. coli cultures, then isolated by filtration purification using Ni-NTA-Agarose (Qiagen). The second is a smaller scale magnetic separation method in which proteins of interest are expressed in a small volume, 25 ml, of E. coli cultures then isolated using a 96-well purification system with MagneHis Ni2+ Agarose (Promega). Both workflows provided comparable average yields of proteins, about 8 microg of purified protein per optical density unit of bacterial culture measured at 600 nm. We discuss advantages and limitations of these automated workflows, which can provide proteins with more than 90% purity and yields in the range of 100 microg to 45 mg per purification run, as well as strategies for optimizing these protocols.

Bacterial Proteins↗
PubMed2006

A semi-automated large-scale process for the production of recombinant tagged proteins in the Baculovirus expression system.

The efficient preparation of recombinant proteins at the lab-scale level is essential for drug discovery, in particular for structural biology, protein interaction studies and drug screening. The Baculovirus insect-cell expression system is one of the most widely applied and highly successful systems for production of recombinant functional proteins. However, the use of eukaryotic cells as host organisms and the multi-step protocol required for the generation of sufficient virus and protein has limited its adaptation to industrialized high-throughput operation. We have developed an integrated large-scale process for continuous and partially automated protein production in the Baculovirus system. The instrumental platform includes parallel insect-cell fermentation in 10L BioWave reactors, cell harvesting and lysis by tangential flow filtration (TFF) using two custom-made filtration units and automated purification by multi-dimensional chromatography. The use of disposable materials (bags, filters and tubing), automated cleaning cycles and column regeneration, prevent any cross-contamination between runs. The preparation of the clear cell lysate by sequential TFF takes less than 2 h and represents considerable time saving compared to standard cell harvesting and lysis by sonication and ultra-centrifugation. The process has been validated with 41 His-tagged proteins with molecular weights ranging from 20 to 160 kDa. These proteins represented several families, and included 23 members of the deubiquitinating enzyme (DUB) family. Each down-stream unit can process four proteins in less than 24 h with final yields between 1 and 100 mg, and purities between 50 and 95%.

Animals↗
PubMed2006

An automated method for the extraction of regional data from PET images.

Manual drawing of regions of interest (ROIs) on brain positron emission tomography (PET) images is labour intensive and subject to intra- and inter-individual variations. To standardize analysis and improve the reproducibility of PET measures, we have developed image analysis software for automated quantification of PET data. The method is based on the individualization of a set of standard ROIs using a magnetic resonance (MR) image co-registered with the PET image. To evaluate the performance of this automated method, the software-based quantification has been compared with conventional manual quantification of PET images obtained using three different PET radiotracers: [(11)C]-WAY 100635, [(11)C]-raclopride and [(11)C]-DASB. Our results show that binding potential estimates obtained using the automated method correlate highly with those obtained by trained raters using manual delineation of ROIs for frontal and temporal cortex, thalamus, and striatum (global intraclass correlation coefficient >0.8). For the three radioligands, the software yields time-activity data that are similar (within 8%) to those obtained by manual quantification, eliminates investigator-dependent variability, considerably shortens the time required for analysis and thus provides an alternative method for accurate quantification of PET data.

Brain↗
PubMed2005

Benefits of automated crystallization plate tracking, imaging, and analysis.

We describe the design of a database and software for managing and organizing protein crystallization data. We also outline the considerations behind the design of a fast web interface linking protein production data, crystallization images, and automated image analysis. The database and associated interfaces underpin the Oxford Protein Production Facility (OPPF) crystallization laboratory, collecting, in a routine and automatic manner, up to 100,000 images per day. Over 17 million separate images are currently held in this database. We discuss the substantial scientific benefits automated tracking, imaging, and analysis of crystallizations offers to the structural biologist: analysis of the time course of the trial and easy analysis of trials with related crystallization conditions. Features of this system address requirements common to many crystallographic laboratories that are currently setting up (semi-)automated crystallization imaging systems.

Crystallization↗
PubMed2005

Association of automated and human observer lesion detecting ability using phantoms.

A set of tissue-mimicking phantoms containing spherical negative contrast simulated lesions was employed to associate an automated method for determining detectability with human observers. Six alternative methods for computing the lesion signal-to-noise ratio (LSNR) were employed for quantifying automated detecting ability. The six methods differ regarding effective lesion area and whether or not gradients in local mean background echo levels were accounted for. The two-alternative-forced-choice (TAFC) technique was used to associate detecting ability of human observers with LSNR values. Although the six methods gave similar results, one method exhibited the least dependency on lesion diameter and is recommended; that method accounts for gradients in local mean background echo levels and employs an effective sphere area of 2/pi times the projected sphere area. A reasonable LSNR detection threshold value of -2.0 was found to apply for nominal transducer frequencies from 4 through 6 MHz and for lesion diameters from 2 through 5 mm. This result allows rapid human-observer-calibrated automated determination of the depth range of detectability as a function of sphere diameter and contrast.

Humans↗
PubMedDate not supplied

Automated electrophysiology in the preclinical evaluation of drugs for potential QT prolongation.

INTRODUCTION: The human ether-a-go-go-related gene (hERG) potassium channel plays a major role in the electrical conductances involved in human heart repolarization. Drugs that decrease hERG K(+) currents are at risk to produce a prolongation of the cardiac action potential, resulting in an increase of the QT interval. Drug-induced QT prolongation or acquired long QT (aLQT) can lead to a fatal arrhythmia known as Torsade de Pointes (TdP). Electrophysiological methods are the best approach to evaluate potential drug candidates for hERG current inhibition. Here we identify limitations with the PatchXpress 7000A automated electrophysiology instrument and describe hERG protocol optimizations necessary for reliable preclinical assessment. METHODS: The PatchXpress 7000A automated electrophysiology system was used to evaluate a group of drugs with known hERG activity under voltage clamp conditions. We used a recombinant cell line expressing hERG, and assessed the inhibition of hERG K(+) currents at different drug concentrations. These data were used to determine hERG IC(50) values and compare assay parameters under different recording conditions. RESULTS: We found that due to limitations with the PatchXpress 7000A instrument, repeated compound additions were critical for achieving steady state drug concentrations that generated data comparable to standard patch clamp methods, particularly when similar voltage pulse protocols were implemented. Some discrepancies were observed between the PatchXpress 7000A and standard patch clamp techniques including shifts in IC(50) values for very hydrophobic compounds. Most hERG IC(50) values were within 3-fold of standard patch clamp IC(50) values. DISCUSSION: Automation of electrophysiology technologies has greatly improved the throughput of assessing lead drug candidates for hERG liability. To maintain hERG data quality comparable to standard patch clamp techniques, the PatchXpress 7000A instrument limitations should be recognized and protocols optimized accordingly to ensure accuracy.

Animals↗
PubMed2004

Expression of HER2neu (c-erbB-2) and epidermal growth factor receptor in cervical cancer: prognostic correlation with clinical characteristics, and comparison of manual and automated imaging analysis.

OBJECTIVES: To evaluate HER2neu and epidermal growth factor receptor (EGFR) expression with respect to overall survival and disease-free survival (DFS), and correlate expression with pretreatment factors. Comparative evaluations of manual and automated immunohistochemical imaging systems for HER2neu and EGFR expression were made. METHODS: Fifty-five patients with stages I-IVA carcinoma of the cervix were treated with definitive radiation therapy. Immunohistochemistry was performed for HER2neu and EGFR, and scored by both manual and automated methods. Univariate and multivariate analyses were performed with disease-free survival (DFS) and overall survival (OS) as primary endpoints, and biomarkers were evaluated for correlation between prognostic factors. RESULTS: Strong correlations in HER2neu and EGFR protein expression were observed between digitally and manually analyzed staining (P <== 0.0001). Increased FIGO stage and decreased HER2neu expression were significant for reduced DFS on univariate analysis (P <== 0.001 and P = 0.03, respectively). Increased FIGO stage, decreased HER2neu expression, and increased membranous staining of EGFR were significant for diminished OS on univariate analysis (P <== 0.0001, P = 0.002, and P = 0.043, respectively). Multivariate analysis revealed only increased membranous staining of EGFR associated with diminished DFS and OS (P = 0.046 and P = 0.012, respectively). Overexpression of HER2neu correlated significantly with adenocarcinoma, and overexpression of EGFR correlated significantly with squamous cell carcinoma histology (P = 0.038 and P = 0.035). Inverse correlations were observed between HER2neu expression and clinical stage, EGFR membranous staining, and EGFR distribution (P = 0.007, P = 0.006, and P = 0.034, respectively). CONCLUSIONS: Increased expression of HER2neu and decreased EGFR membranous staining identified patients with improved DFS and OS on univariate analysis, although only decreased EGFR membranous staining was significant on multivariate analysis. We also found strong correlation of results between manually and automated imaging methods.

Analysis of Variance↗
PubMed1997

Automated morphometry of coronary arteries with digital image analysis of intravascular ultrasound.

We designed and tested digital image processing strategies to perform fully automated segmentation of luminal and medial-adventitial boundaries in intravascular ultrasound images of human coronary arteries. Automated segmentation is an essential tool for advanced techniques of clinical visualization and quantitative measurement. Vascular compliance measurements and three-dimensional reconstructions are demonstrated as examples of such applications. Digital image processing was performed in three phases: (1) preprocessing, including a polar transform, local contrast enhancement, and speckle noise filtering; (2) segmentation, involving radial scanning, region growing, or cost-function minimization techniques; and (3) postprocessing, involving dropout filtering and outline smoothing. Cross-sectional areas were compared with manual tracings from experienced operators and showed good agreement. The algorithm bias ranged from -0.34 to 1.18 mm2; interclass and intraclass correlation coefficients ranged from 0.83 to 0.94. The designed techniques currently allow fully automated segmentation without operator interaction of the luminal and, if present, medial-adventitial boundary.

Adult↗
PubMed1997

Automated assessment of mitral regurgitant volume and regurgitant fraction by a newly developed digital color Doppler velocity profile integration method.

Recent development of the automated cardiac flow measurement (ACFM) method has provided automated measurement of stroke volume and cardiac output by spatial and temporal integration of digital Doppler velocity profile data. The purpose of this study was to evaluate the clinical usefulness of the ACFM method using digital color Doppler velocity profile integration in the assessment of mitral regurgitant volume and regurgitant fraction from measurements of both aortic outflow and mitral inflow volumes. We calculated both aortic outflow and mitral inflow volumes from the apical approach with the ACFM and pulsed Doppler (PD) methods in 20 patients with isolated mitral regurgitation. Mitral regurgitant volume and regurgitant fraction were calculated by the following equation: mitral regurgitant volume = (mitral inflow volume) - (aortic outflow volume), % regurgitant fraction = (mitral regurgitant volume)/(mitral inflow volume) x 100. Mitral regurgitant volume and regurgitant fraction were compared with that determined by the PD method. Mitral regurgitant volume measurement by the ACFM method showed a good correlation with that measured by the PD method (r = 0.90, y = 0.77x + 11.6, SEE = 9.0 ml); the mean differences between PD and ACFM measurements was -1.7 +/- 12.5 ml. Regurgitant fraction estimated by the ACFM method correlated well with that of the PD method (r = 0.92, y = 0.98x + 2.1, SEE = 8.8%). The mean difference for the measurement of regurgitant fraction between the PD and ACFM methods was 0.8 +/- 6.6%. Total time required for mitral regurgitant volume calculation in 1 cardiac cycle by the ACFM method was significantly shorter than that of the PD method (126 +/- 15 seconds vs 228 +/- 36 seconds, p <0.01). In conclusion, the newly developed ACFM method is simple, quick, and accurate in the automated assessment of mitral regurgitant volume and regurgitant fraction.

Adult↗