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The purpose of this study was to evaluate the use of a semiautomatic algorithm to simultaneously segment multiple high-dose-rate (HDR) gynecologic interstitial brachytherapy (ISBT) needles in three-dimensional (3D) transvaginal ultrasound (TVUS) images, with the aim of providing a clinically useful tool for intraoperative implant assessment.A needle segmentation algorithm previously developed for HDR prostate brachytherapy was adapted and extended to 3D TVUS images from gynecologic ISBT patients with vaginal tumors. Two patients were used for refining/validating the modified algorithm and five patients (8-12 needles/patient) were reserved as an unseen test data set. The images were filtered to enhance needle edges, using intensity peaks to generate feature points, and leveraged the randomized 3D Hough transform to identify candidate needle trajectories. Algorithmic segmentations were compared against manual segmentations and calculated dwell positions were evaluated.All 50 test data set needles were successfully segmented with 96% of algorithmically segmented needles having angular differences3° compared with manually segmented needles and the maximum Euclidean distance was2.1 mm. The median distance between corresponding dwell positions was 0.77 mm with 86% of needles having maximum differences3 mm. The mean segmentation time using the algorithm was30 s/patient.We successfully segmented multiple needles simultaneously in intraoperative 3D TVUS images from gynecologic HDR-ISBT patients with vaginal tumors and demonstrated the robustness of the algorithmic approach to image artifacts. This method provided accurate segmentations within a clinically efficient timeframe, providing the potential to be translated into intraoperative clinical use for implant assessment.

OBJECTIVE. This study assessed a machine learning-based dual-energy CT (DECT) tumor analysis prototype for semiautomatic segmentation and radiomic analysis of benign and malignant liver lesions seen on contrast-enhanced DECT. MATERIALS AND METHODS. This institutional review board-approved study included 103 adult patients (mean age, 65 ± 15 [SD] years; 53 men, 50 women) with benign (60/103) or malignant (43/103) hepatic lesions on contrast-enhanced dual-source DECT. Most malignant lesions were histologically proven; benign lesions were either stable on follow-up CT or had characteristic benign features on MRI. Low- and high-kilovoltage datasets were deidentified, exported offline, and processed with the DECT tumor analysis for semiautomatic segmentation of the volume and rim of each liver lesion. For each segmentation, contrast enhancement and iodine concentrations as well as radiomic features were derived for different DECT image series. Statistical analyses were performed to determine if DECT tumor analysis and radiomics can differentiate benign from malignant liver lesions. RESULTS. Normalized iodine concentration and mean iodine concentration in the benign and malignant lesions were significantly different (p < 0.0001-0.0084; AUC, 0.695-0.856). Iodine quantification and radiomic features from lesion rims (AUC, ≤ 0.877) had higher accuracy for differentiating liver lesions compared with the values from lesion volumes (AUC, ≤ 0.856). There was no difference in the accuracies of DECT iodine quantification (AUC, 0.91) and radiomics (AUC, 0.90) for characterizing liver lesions. CONCLUSION. DECT radiomics were more accurate than iodine quantification for differentiating solid benign and malignant hepatic lesions.

The present work aimed to evaluate the reproducibility of radiomics features derived from manual delineation and semiautomatic segmentation after enhancement using the Contrast Limited Adaptive Histogram Equalization (CLAHE) and Adaptive Histogram Equalization (AHE) techniques on a benign tumor of two-dimensional (2D) mammography images. Thirty mammogram images with known benign tumors were obtained from The Cancer Imaging Archive (TCIA) datasets and were randomly selected as subjects. The samples were enhanced for semiautomatic segmentation sets using the Active Contour Model in MATLAB 2019a before analysis by two independent observers. Meanwhile, the images without any enhancement were segmented manually. The samples were divided into three categories: (1) CLAHE images, (2) AHE images, and (3) manual segmented images. Radiomics features were extracted using algorithms provided by MATLAB 2019a software and were assessed with a reliable intra-class correlation coefficient (ICC) score. Radiomics features for the CLAHE group (ICC = 0.890 ± 0.554, p 0.05). Features in all three categories were more robust for the CLAHE compared to the AHE and manual groups. This study shows the existence in variation for the radiomics features extracted from tumor region that are segmented using various image enhancement techniques. Semiautomatic segmentation with image enhancement using CLAHE algorithm gave the best result and was a better alternative than manual delineation as the first two techniques yielded reproducible descriptors. This method should be applicable for predicting outcomes in patient with breast cancer.

Introduction The purpose of this study was to evaluate the variations in the volume of periapical lesions scored using a cone-beam computed tomographic periapical index (CBCTPAI) and to develop a new volume-based periapical index. Methods Cone-beam computed tomographic images were obtained from InteleViewer (Intelerad Medical Systems Incorporated, Montreal, Canada). Teeth with a periapical radiolucency or with a history of endodontic treatment were included in this study. Using 3-dimensional medical imaging processing software (Mimics Research; Materialise NV, Leuven, Belgium), the maximum diameter of 273 periapical lesions and their corresponding CBCTPAI score was determined. The software was then used to determine the volume of the lesions using a semiautomatic segmentation technique. Results There was a substantial variation in the volume for CBCTPAI scores 3, 4, and 5, which was demonstrated by the variance and range, thus making it difficult to use the current CBCTPAI as a method to predict volume and treatment outcomes. A new index, the cone-beam computed tomographic periapical volume index (CBCTPAVI), was developed using partition classification analysis. The results for the new index demonstrated high levels of sensitivity, specificity, precision, and area under the curve, all at 0.90 or more, except 1 sensitivity for CBCTPAVI 1 at 0.875. Overall, the accurate classification rate was 98.169%, and the root mean square error rate was low at 0.07. Conclusions The proposed CBCTPAVI will allow clinicians to classify lesions based on their true 3-dimensional size, accurately assess healing of lesions, and predict treatment outcomes.

Objectives To assess the intraexaminer and interexaminer reliabilities of novel semiautomatic methods to segment the nasal cavity (NC) and pharyngeal airway (PA) and to determine the minimal cross-sectional area (CS) and hydraulic diameter (HD) of the PA. Materials and Methods To test reproducibility, two examiners analyzed the NC and PA independently in 10 retrospectively selected cone beam computed tomography (CBCT) images using semiautomatic segmentation. The PA centerline was determined to assess the minimal CS and HD. The intraclass correlation coefficient (ICC) was used to calculate intraexaminer and interexaminer reliabilities. Measurement errors were assessed by Dahlberg's formula and paired t-tests. The level of agreement was assessed using the Bland-Altman method. Results Intraexaminer and interexaminer reliabilities were excellent (minimal ICC, 0.960). The error of the method was good except for interexaminer values for the oropharynx (P = .016). The minimal CS and HD measurements were reliable (minimal ICC, 0.993; narrow limits of agreement). Conclusions The novel methods for analysis of the NC and PA are reliable. The minimal CS and HD demonstrated excellent reliabilities, which are critical to detect the most constricted part of the PA. Separation of the oropharynx from the voids close to the retroglossal area is not trivial and should be considered with caution.

This investigation was performed to analyze and evaluate anatomical and volumetric data of the sphenoid sinus by semiautomatic segmentation of cone beam computed tomography (CBCT) datasets.This analysis was carried out on cone beam computed tomography images of 100 patients. By using the discretionary software "ITK-Snap", the volumetric investigation of 197 sphenoid sinuses was conducted. The statistical analyses were carried out by using the paired and independent Student t-test. In addition, the Pearsons chi-square test was performed. P values P 0.05 were considered significant.The volumetric mean was 4.438 ± 2.434 cm3 for the right and 4.809 ± 3.000 for the left side. Results did not indicate statistically significant differences according to the side, irrespective of gender (P 0.05). The further investigation of differences between male and female patients did assess significant results (P 0.05), males (10.477 ± 3.851 cm3) present a larger total sinus volume than females (8.219 ± 3.574 cm3). In accordance to patients' age (median 54 years), smaller volumes were related to younger patients and larger volumes to older ones. But, no statistically significant results in accordance to age could be detected (χ2 = 1.258; P 0.05).Endoscopic sinus surgery of the vulnerable and intricate anatomy of the sphenoid sinus requires an explicit knowledge and orientation about the anatomical variations such as septums and volumetric capacity. Concerning this matter, semiautomatic segmentation of CBCT images can aid the surgeon in preoperative planning. Our investigation shows that a small sinus volume, that is, affecting female patients and a complex sinus anatomy by the occurrence of a septum, especially located close to neurovascular structures could essentially aggravate endoscopic sphenoid sinus surgery. In this regard, volumetric analysis of the sphenoid sinus by CBCT images can provide presurgical information and facilitates an individualized treatment.

OBJECTIVES The aims of this study were to (a) present a novel morphological contour interpolation (MCI) algorithm based method to evaluate grafted bone alterations following guided bone regeneration (GBR), (b) compare clinical and radiological outcomes of GBR with two different collagen membranes. MATERIALS AND METHODS The data were retrieved from an ongoing randomized controlled trial. Patients were randomly allocated into two groups: (a) control group (CG): Bio-Gide (b) test group (TG): bovine dermis-derived collagen membrane. Cone beam computed tomography examinations were performed 1 week (T0) and 6 months after surgery (T1). PES/WES at T1, grafted bone volume and density changes from T0 to T1 were recorded. RESULTS Thirty-six patients (16/20 in test/control group, respectively) were enrolled in the present study. Excellent inter-observer reliability (ICC ≥ 0.97) was revealed for repeated measurements using this method. Significant volumetric reduction of grafted bone were found in both groups (test group: from 0.60 to 0.39 cm3 , p

Background The clinical and research value of Computed Tomography (CT) volumetry of esophageal cancer tumor size remains controversial. Development in CT technique and image analysis has made CT volumetry less cumbersome and it has gained renewed attention. The aim of this study was to assess esophageal tumor volume by semi-automatic measurements as compared to manual. Methods A total of 23 esophageal cancer patients (median age 65, range 51–71), undergoing CT in the portal-venous phase for tumor staging, were retrospectively included between 2007 and 2012. One radiology resident and one consultant radiologist measured the tumor volume by semiautomatic segmentation and manual segmentation. Reproducibility of the respective measurements was assessed by intraclass correlation coefficients (ICC) and by average deviation from mean. Results Mean tumor volume was 46 ml (range 5-137 ml) using manual segmentation and 42 ml (range 3-111 ml) using semiautomatic segmentation. Semiautomatic measurement provided better inter-observer agreement than traditional manual segmentation. The ICC was significantly higher for semiautomatic segmentation in comparison to manual segmentation (0.86, 0.56, p

Objective To evaluate the accuracy of semiautomated segmentation of urinary stone size in computed tomography (CT) compared with manual measurement. Materials and Methods A total of 103 patients (32f, 71m ; mean age 52 years±18 that were diagnosed with urolithiasis and collected stones received standardized ex vivo CT-scans and radiography of the stones. Stone size was segmented semiautomatically using commercial software (syngo.via, Siemens, Germany) and compared with manual caliper measurement on digital radiography. Results Mean size was 4.4 mm in CT and 4.6 mm in radiography. Depending on number of stones analyzed per patient, estimation of stone size showed moderate to excellent correlation for both methods. There was no significant difference in overall size measurement. Conclusion Semiautomatic segmentation of urinary stone size in CT is possible and reduces measurement errors, allowing more precise estimation especially for smaller concrements. Neighboring stones may hamper segmentation of stone size.

The aim of this study was to provide volumetric data of the pterygopalatine fossa by semiautomatic segmentation based upon cone beam computed tomography.Cone beam computed tomography (CBCT) images of 100 patients were analyzed. By using the open source software "ITK-Snap," the volumetric measurements of 200 pterygopalatine fossae were performed. For statistical investigations paired t test, and independent Student t test were performed. Also, the Pearsons chi-square test was applied. P values P 0.05 were considered significant.The mean volume was 578.376 mm for the right and 560.979 mm for the left side. The results indicated statistically significant differences according to the right and the left pterygopalatine fossa, regardless of gender (P 0.05). The analysis of differences between males and females did not show any significant results (P 0.05), although males present a slightly larger volume than females. According to the median age (59 years), younger patients presented smaller volumes, whereas older patients presented larger volumes. Nevertheless, no statistically significant differences according to age (χ = 3.520; P 0.05) could be found.Clinical intervention with the application of local anesthetics into the complex and vulnerable anatomy of the pterygopalatine fossa makes a thorough knowledge about the volumetric capacity indispensable. Therefore, the semiautomatic segmentation of CBCT images provides a useful, available and validated tool. Our results show that a final injected anesthetic volume larger than 1 ml exceeds the pterygopalatine fossa capacity considerably and could cause complications. To prevent this, volumetric analysis of this region can provide further information and enables an individualized patients' treatment.

The purpose of this study was to compare the accuracy of the planimetric methods on volume estimations by using cone beam computed tomography (CBCT). Thirty-one prepared intraosseous bone defects from thirteen bovine femur condyles were scanned with CBCT. The defect volumes were estimated by point counting (PC), manual segmentation (MS) and semiautomatic segmentation (SAS) methods at 0.3-mm section thickness without any intersection gap. The estimated volumes were compared with the results of the Archimedes’ method. The planimetric methods were analyzed using a Friedman’s two-way analysis of variance test. The estimated volumes of MS and SAS methods were compatible with the volumes of Archimedes’ method (p = 0.768, p = 0.140, respectively), but the volumes from the PC method were not compatible with Archimedes’ method (p

Purpose: A hybrid planar-SPECT/CT method for tumor dosimetry in 177Lu-DOTATATE therapy, applicable to datasets consisting of multiple conjugate-view images and one SPECT/CT, is developed and evaluated. Methods: The imaging protocol includes conjugate-view imaging at 1, 24, 96, and 168 h post infusion (p.i.) and a SPECT/CT acquisition 24 h p.i. The dosimetry method uses the planar images to estimate the shape of the time–activity concentration curve, which is then rescaled to absolute units using the SPECT-derived activity concentration. The resulting time-integrated activity concentration coefficient (TIACC) is used to calculate the tumor-absorbed dose. Semiautomatic segmentation techniques are applied for tumor delineation in both planar and SPECT images, where the planar image segmentation is accomplished using an active-rays-based technique. The selection of tumors is done by visual inspection of planar and SPECT images and applying a set of criteria concerning the tumor visibility and possible interference from superimposed activity uptakes in the planar images. Five different strategies for determining values from planar regions of interest (ROIs), based on entire or partial ROIs, and with and without background correction, are evaluated. Evaluation is performed against a SPECT/CT-based method on data from six patients where sequential conjugate-view and SPECT/CT imaging have been performed in parallel and against ground truths in Monte Carlo simulated images. The patient data are also used to evaluate the interoperator variability and to assess the validity of the developed criteria for tumor selection. Results: For patient images, the hybrid method produces TIACCs that are on average 6% below those of the SPECT/CT only method, with standard deviations for the relative TIACC differences of 8%–11%. Simulations show that the hybrid and SPECT-based methods estimate the TIACCs to within approximately 10% for tumors larger than around 10 ml, while for smaller tumors, all methods underestimate the TIACCs due to underestimations of the activity concentrations in the SPECT images. The planar image segmentation has a low operator dependence, with a median Dice similarity coefficient of 0.97 between operators. The adopted criteria for tumor selection manage to discriminate the tumors for which the absorbed-dose deviations between the hybrid and SPECT methods are the highest. Conclusions: The hybrid method is found suitable for studies of tumor-absorbed doses in radionuclide therapy, provided that selection criteria regarding the visibility and overlapping activities in the planar images are applied. (Less)

The authors' aim was to provide volumetric data of mandibular condyles based upon cone beam computed tomography with the means of semiautomatic segmentation.Retrospective chart review of 350 patients (700 mandibular condyles) with cone beam computerized tomography between February 2007 and December 2016. Univariate analysis was performed to analyze associations between variables. P values

Purpose To demonstrate papillary imaging of eyes with optic disc pits (ODP) or optic disc pit associated maculopathy (ODP-M) with ultrahigh-speed swept-source optical coherence tomography (SS-OCT) at 1.68 million A-scans/s. To generate 3D-renderings of the papillary area with 3D volume-reconstructions of the ODP and highly resolved en face images from a single densely-sampled megahertz-OCT (MHz-OCT) dataset for investigation of ODP-characteristics. Methods A 1.68 MHz-prototype SS-MHz-OCT system at 1050 nm based on a Fourier-domain mode-locked laser was employed to acquire high-definition, 3D datasets with a dense sampling of 1600 × 1600 A-scans over a 45° field of view. Six eyes with ODPs, and two further eyes with glaucomatous alteration or without ocular pathology are presented. 3D-rendering of the deep papillary structures, virtual 3D-reconstructions of the ODPs and depth resolved isotropic en face images were generated using semiautomatic segmentation. Results 3D-rendering and en face imaging of the optic disc, ODPs and ODP associated pathologies showed a broad spectrum regarding ODP characteristics. Between individuals the shape of the ODP and the appending pathologies varied considerably. MHz-OCT en face imaging generates distinct top-view images of ODPs and ODP-M. MHz-OCT generates high resolution images of retinal pathologies associated with ODP-M and allows visualizing ODPs with depths of up to 2.7 mm. Conclusions Different patterns of ODPs can be visualized in patients for the first time using 3D-reconstructions and co-registered high-definition en face images extracted from a single densely sampled 1050 nm megahertz-OCT (MHz-OCT) dataset. As the immediate vicinity to the SAS and the site of intrapapillary proliferation is located at the bottom of the ODP it is crucial to image the complete structure and the whole depth of ODPs. Especially in very deep pits, where non-swept-source OCT fails to reach the bottom, conventional swept-source devices and the MHz-OCT alike are feasible and beneficial methods to examine deep details of optic disc pathologies, while the MHz-OCT bears the advantage of an essentially swifter imaging process. Electronic supplementary material The online version of this article (10.1007/s00417-017-3857-9) contains supplementary material, which is available to authorized users.

Purpose To assess variability in corneal ulcer measurements between ophthalmologists and reduce clinician-dependent variability using semiautomated segmentation of the ulcer from photographs. Methods Three ophthalmologists measured 50 patients' eyes for epithelial defects (EDs) and the stromal infiltrate (SI) size using slit-lamp (SL) calipers. SL photographs were obtained. An algorithm was developed for semiautomatic segmenting of the ED and SI in the photographs. Semiautomatic segmentation was repeated 3 times by different users (2 ophthalmologists and 1 trainee). Clinically significant variability was assessed with intraclass correlation coefficients (ICCs) and the percentage of pairwise measurements differing by ≥0.5 mm. Semiautomatic segmentation measurements were compared with manual delineation of the image by a corneal specialist (gold standard) using Dice similarity coefficients. Results Ophthalmologists' reliability in measurements by SL calipers had an ICC from 0.84 to 0.88 between examiners. Measurements by semiautomatic segmentation had an ICC from 0.96 to 0.98. SL measures of ulcers by clinical versus semiautomatic segmentation measures differed by ≥0.5 mm in 24% to 38% versus 8% to 28% (ED height); 30% to 52% versus 12% to 34% (ED width); 26% to 38% versus 10% to 32% (SI height); and 38% to 58% versus 14% to 34% (SI width), respectively. Average Dice similarity coefficients between manual and repeated semiautomatic segmentation ranged from 0.83 to 0.86 for the ED and 0.78 to 0.83 for the SI. Conclusions Variability exists when measuring corneal ulcers, even among ophthalmologists. Photography and computerized methods for quantifying the ulcer size could reduce variability while remaining accurate and impact quantitative measurement endpoints.

Background and objective Recent evidence points toward an active immunological role of intra-abdominal adipose tissue in Crohn disease (CD). We quantified the abdominal adipose tissue compartments using magnetic resonance imaging (MRI) in 27 pediatric patients with CD compared with 14 controls undergoing MRI examination for other reasons. Methods Total (TAAT), subcutaneous (SCAT) and intra-abdominal (IAAT) adipose tissue areas were measured by semiautomatic segmentation on a transverse slice centered on the umbilicus (mean ± standard deviation in square centimeter) using standard T1-weighted sequences. IAAT/TAAT and IAAT/height ratios were calculated and analyzed for associations with disease duration, phenotype, or therapy. Results Patients with CD (median age 15.0 years, range 7.7-17.9, 18/27 boys, median disease duration 29 months, range 0-136) compared to controls (median age 13.9 years, range 3.3-17.8, 4/14 boys) had higher IAAT area (42.3 ± 21.0 vs 28.7 ± 11.6, P = 0.0494) but similar SCAT and TAAT areas (104.6 ± 72.8 vs 96.5 ± 50.8, P = 0.8170 and 146.9 ± 87.3 vs 125.3 ± 61.5, P = 0.7417, respectively). IAAT/TAAT ratio was higher in patients with CD compared to controls (0.32 ± 0.10 vs 0.24 ± 0.04, P = 0.0081). Patients with disease duration >2 years (n = 14) had higher IAAT/TAAT ratio than those with shorter disease and controls (0.35 ± 0.10 vs 0.28 ± 0.08, P = 0.0288 and 0.24 ± 0.04, P = 0.0009, respectively). In these patients, increased IAAT/height ratio was associated with complicated disease (P = 0.043, r = 0.573). No association was found between IAAT/TAAT ratio and actual disease activity or therapy. Conclusions IAAT is increased in pediatric CD and correlates with disease duration. Assessment of IAAT accumulation may be considered in future MRI scores for inflammation and bowel damage in CD and during follow-up of different therapeutic interventions.

The aims of this study were to evaluate the intra- and interobserver reproducibility of manual segmentation of bone sarcomas in magnetic resonance imaging (MRI) studies and to compare manual and semiautomatic segmentation methods. This retrospective study included twelve osteosarcoma and eight Ewing sarcoma MRI studies performed prior to any therapeutic intervention. All cases were histopathologically confirmed. Three radiologists used 3D-Slicer software to perform manual segmentation of bone sarcomas in a blinded and independent manner. One radiologist segmented manually and also performed semiautomatic segmentation with the GrowCut tool. Segmentation exercises were timed for comparison. The dice similarity coefficient (DSC) and Hausdorff distance (HD) were used to evaluate similarity between the segmentation results and further statistical analyses were performed to compare DSC, HD, and volumetric results. Manual segmentation was reproducible with intraobserver DSC varying from 0.83 to 0.97 and HD from 3.37 to 28.73 mm. Interobserver DSC of manual segmentation showed variation from 0.73 to 0.97 and HD from 3.93 to 33.40 mm. Semiautomatic segmentation compared to manual segmentation resulted in DSCs of 0.71−0.96 and HDs of 5.38−31.54 mm. Semiautomatic segmentation required significantly less time compared to manual segmentation (P value ≤0.05). Among all situations compared, tumor volumetry did not show significant statistical differences (P value >0.05). We found excellent intra- and interobserver agreement for manual segmentation of osteosarcoma and Ewing sarcoma. There was high similarity between manual and semiautomatic segmentation, with a significant reduction of segmentation time using the semiautomatic method.

A prerequisite for many analysis tasks in modern comparative biology is the segmentation of 3-dimensional (3D) images of the specimens being investigated (e.g. from microCT data). Depending on the specific imaging technique that was used to acquire the images and on the image resolution, different segmentation tools are required. While some standard tools exist that can often be applied for specific subtasks, building whole processing pipelines solely from standard tools is often difficult. Some tasks may even necessitate the implementation of manual interaction tools to achieve a quality that is sufficient for subsequent analysis. In this work, we present a pipeline of segmentation tools that can be used for the semiautomatic segmentation and quantitative analysis of voids in tissue (i.e. internal structural porosity). We use this pipeline to analyze lacuno-canalicular networks in stingray tesserae from 3D images acquired with synchrotron microCT.•The first step of this pipeline, the segmentation of the tesserae, was performed using standard marker-based watershed segmentation.•The efficient processing of the next two steps, that is, the segmentation of all lacunae spaces belonging to a specific tessera and the separation of these spaces into individual lacunae required recently developed, novel tools.•For error correction, we developed an interactive method that allowed us to quickly split lacunae that were accidentally merged, and to merge lacunae that were wrongly split.•Finally, the tesserae and their corresponding lacunae were subdivided into structural wedges (i.e. specific anatomical regions) using a semi-manual approach. With this processing pipeline, analysis of a variety of interconnected structural networks (e.g. vascular or lacuno-canalicular networks) can be achieved in a comparatively high-throughput fashion. In our study system, we were able to efficiently segment more than 12,000 lacunae in high-resolution scans of nine tesserae, providing a robust data set for statistical analysis., Graphical abstract Image, graphical abstract

© 2019 American Society for Surgery of the Hand Purpose: Anthropometric assessment of bony structures in the body is important for preoperative computer-aided surgery, implant design, finite element modeling, and biomechanical studies investigating joint structure and function. The use of the contralateral limb in surgery and clinical practice relies on the assumption that the right and left limbs of an individual are symmetric. Therefore, the purpose of this study was to quantify the bilateral symmetry of the bony structures of the distal radius using 3-dimensional (3D) computed tomography. Methods: We collected computed tomography images of 37 paired, fresh-frozen, healthy cadaveric male upper limbs (aged 75.4 ± 8.3 years). Three-dimensional reconstructed models were created using semiautomatic segmentation. Using the 3D models, we measured 3D radial inclination, 3D volar tilt, 3D radial height, medial volar cortical angle, middle volar cortical angle, and lateral volar cortical angle and compared them between sides. Results: There were no statistically significant differences measured between right and left distal radius in 37 paired wrists. Mean radial height was 12.81 mm (SD, 1.74 mm) on the left and 12.88 mm (SD, 1.72 mm) on the right. Mean volar tilt was 10.74° (SD, 3.74°) and 10.77° (SD, 3.19°) and radial inclination was 24.05° (SD, 2.63°) and 24.18° (SD, 3.41°) on the left and right, respectively. Mean volar cortical angle across the radius was 140.9° (SD, 7.9°) on the left and 140.1° (SD, 7.9°) on the right. Conclusions: Direct bilateral comparison of the distal radius and wrist joints is useful to predict normal anatomy of the injured radius, because bilateral similarities exist. Clinical relevance: This article provides a comprehensive list of measurements of the distal radius compared bilaterally using a 3D model. From this study, we found that the contralateral radius can be used as a benchmark with which to compare fracture reduction and to manage malunions during the preoperative planning of corrective osteotomies. It can also be used to define normal anatomy.

OBJECTIVES/HYPOTHESIS High-speed videoendoscopy (HSV) has potential to objectively quantify vibratory vocal fold characteristics during phonation. Glottal Analysis Tools (GAT) version 2018, developed in Erlangen, Germany, is software for determining various glottal area waveform (GAW) quantities. Before having GAT analyze HSV videos, segmenters have to define glottis manually across videos in a semiautomatic segmentation protocol. Such interventions are hypothesized to induce variability of subsequent GAW measure computation across segmenters and may attenuate GAT measures' reliability to a certain point. This study explored intersegmenter variability in GAT's GAW measures based on semiautomatic image processing. STUDY DESIGN Cohort study of rater reliability. METHODS In total, 20 HSV videos from normophonic and dysphonic subjects with various laryngeal disorders were selected for this study and segmented by three trained segmenters. They separately segmented glottis areas in the same frame sets of the videos. Upon analysis of GAW, GAT offers 46 measures related to topologic GAW dynamic characteristics, GAW periodicity and perturbation characteristics, and GAW harmonic components. To address GAT's reliability, intersegmenter-based variability in these measures was examined with intraclass correlation coefficient (ICC). RESULTS In general, ICC behavior of the 46 GAW measures across three raters was highly acceptable. ICC of one parameter was moderate (0.5

Fetuses at the extremes of growth abnormalities carry a risk of perinatal morbidity and death. Their identification traditionally is done by 2-dimensional ultrasound imaging, the performance of which is not always optimal. Magnetic resonance imaging superbly depicts fetal anatomy and anomalies and has contributed largely to the evaluation of high-risk pregnancies. In 1994, magnetic resonance imaging was introduced for the estimation of fetal weight, which is done by measuring the fetal body volume and converting it through a formula to fetal weight. Approximately 10 studies have shown that magnetic resonance imaging is more accurate than 2-dimensional ultrasound imaging in the estimation of fetal weight. Yet, despite its promise, the magnetic resonance imaging technique currently is not implemented clinically. Over the last 5 years, this technique has evolved quite rapidly. Here, we review the literature data, provide details of the various measurement techniques and formulas, consider the application of the magnetic resonance imaging technique in specific populations such as patients with diabetes mellitus and twin pregnancies, and conclude with what we believe could be the future perspectives and clinical application of this challenging technique. The estimation of fetal weight by ultrasound imaging is based mainly on an algorithm that takes into account the measurement of biparietal diameter, head circumference, abdominal circumference, and femur length. The estimation of fetal weight by magnetic resonance imaging is based on one of the 2 formulas: (1) magnetic resonance imaging-the estimation of fetal weight (in kilograms)=1.031×fetal body volume (in liters)+0.12 or (2) magnetic resonance imaging-the estimation of fetal weight (in grams)=1.2083×fetal body volume (in milliliters)ˆ0.9815. Comparison of these 2 formulas for the detection of large-for-gestational age neonates showed similar performance for preterm (P=.479) and for term fetuses (P=1.000). Literature data show that the estimation of fetal weight with magnetic resonance imaging carries a mean or median relative error of 2.6 up to 3.7% when measurements were performed at

Purpose To develop a semiautomatic method for rapid segmentation of myocardial tissue phase mapping (TPM) data. Methods Manual segmentation of the myocardium was performed at end-diastole and end-systole. The points in both user-defined masks were then automatically tracked over the entire cardiac cycle using temporal integration of the velocity field. Paths that failed to visit both masks at the expected times were excluded, after which masks for all time points were generated automatically from the accepted paths. Midventricular and basal phase contrast TPM slices from 12 rats were segmented using the proposed method and fully manual segmentation. The results were compared using Dice's metric and Bland–Altman analysis, and interobserver variability was assessed. Results The semiautomatic method reduced the average user input time from 21 min to 1 min per slice. The Dice metrics between the methods were 0.88 ± 0.03 (midventricular) and 0.83 ± 0.06 (basal), and Bland–Altman limits of agreement of peak systolic and diastolic regional velocities were: midventricular: 0.05 ± 0.65 cm/s, −0.02 ± 0.42 cm/s, and −0.03 ± 0.40 cm/s (radial, tangential, longitudinal); basal: −0.04 ± 0.73 cm/s, 0.03 ± 0.60 cm/s, and −0.04 ± 0.48 cm/s (radial, tangential, longitudinal). Interobserver variability following semiautomatic segmentation was lower than for manual segmentation. Conclusion The proposed method reduced the segmentation time substantially and exhibited well-preserved data quality and excellent interobserver limits of agreement. Magn Reson Med 78:1199–1207, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Introduction Our objectives were to assess reliability, validity, and time efficiency of semiautomatic segmentation using Segura software of the nasal and pharyngeal airways, against manual segmentation with point-based analysis with color mapping. Methods Pharyngeal and nasal airways from 10 cone-beam computed tomography image sets were segmented manually and semiautomatically using Segura (University of Alberta, Edmonton, Alberta, Canada). To test intraexaminer and interexaminer reliabilities, semiautomatic segmentation was repeated 3 times by 1 examiner and then by 3 examiners. In addition to volume and surface area, point-based analysis was completed to assess the reconstructed 3-dimensional models from Segura against manual segmentation. The times of both methods of segmentation were also recorded to assess time efficiency. Results The reliability and validity of Segura were excellent (intraclass correlation coefficient, >0.9 for volume and surface area). Part analysis showed small differences between the Segura and manually segmented 3-dimensional models (greatest difference did not exceed 4.3 mm). Time of segmentation using Segura was significantly shorter than that for manual segmentation, 49 ± 11.0 vs 109 ± 9.4 minutes ( P Conclusions Semiautomatic segmentation of the pharyngeal and nasal airways using Segura was found to be reliable, valid, and time efficient. Part analysis with color mapping was the key to explaining differences in upper airway volume and provides meaningful and clinically relevant analysis of 3-dimensional changes.

Objective This study aimed to evaluate the tumor doubling time of invasive lung adenocarcinoma according to the International Association of the Study for Lung Cancer (IASLC)/American Thoracic Society (ATS)/European Respiratory Society (ERS) histologic classification. Materials and methods Among the 2905 patients with surgically resected lung adenocarcinoma, we retrospectively included 172 patients (mean age, 65.6 ± 9.0 years) who had paired thin-section non-contrast chest computed tomography (CT) scans at least 84 days apart with the same CT parameters, along with 10 patients with squamous cell carcinoma (mean age, 70.9 ± 7.4 years) for comparison. Three-dimensional semiautomatic segmentation of nodules was performed to calculate the volume doubling time (VDT), mass doubling time (MDT), and specific growth rate (SGR) of volume and mass. Multivariate linear regression, one-way analysis of variance, and receiver operating characteristic curve analyses were performed. Results The median VDT and MDT of lung cancers were as follows: acinar, 603.2 and 639.5 days; lepidic, 1140.6 and 970.1 days; solid/micropapillary, 232.7 and 221.8 days; papillary, 599.0 and 624.3 days; invasive mucinous, 440.7 and 438.2 days; and squamous cell carcinoma, 149.1 and 146.1 days, respectively. The adjusted SGR of volume and mass of the solid-/micropapillary-predominant subtypes were significantly shorter than those of the acinar-, lepidic-, and papillary-predominant subtypes. The histologic subtype was independently associated with tumor doubling time. A VDT of 465.2 days and an MDT of 437.5 days yielded areas under the curve of 0.791 and 0.795, respectively, for distinguishing solid-/micropapillary-predominant subtypes from other subtypes of lung adenocarcinoma. Conclusion The tumor doubling time of invasive lung adenocarcinoma differed according to the IASCL/ATS/ERS histologic classification.

BACKGROUND AND PURPOSE: Aneurysm volume pulsation is a potential predictor of intracranial aneurysm rupture. We evaluated whether 7T MR imaging can quantify aneurysm volume pulsation. MATERIALS AND METHODS: In Stage I of the study, 10 unruptured aneurysms in 9 patients were studied using a high-resolution (0.6-mm, isotropic) 3D gradient-echo sequence with cardiac gating. Semiautomatic segmentation was used to measure aneurysm volume (in cubic millimeters) per cardiac phase. Aneurysm pulsation was defined as the relative increase in volume between the phase with the smallest volume and the phase with the largest volume. The accuracy and precision of the measured volume pulsations were addressed by digital phantom simulations and a repeat image analysis. In Stage II, the imaging protocol was optimized and 9 patients with 9 aneurysms were studied with and without administration of a contrast agent. RESULTS: The mean aneurysm pulsation in Stage I was 8% ± 7% (range, 2%–27%), with a mean volume change of 15 ± 14 mm 3 (range, 3–51 mm 3 ). The mean difference in volume change for the repeat image analysis was 2 ± 6 mm 3 . The artifactual volume pulsations measured with the digital phantom simulations were of the same magnitude as the volume pulsations observed in the patient data, even after protocol optimization in Stage II. CONCLUSIONS: Volume pulsation quantification with the current imaging protocol on 7T MR imaging is not accurate due to multiple imaging artifacts. Future studies should always include aneurysm-specific accuracy analysis.

Aim: To find the correlation between nasal airway volume and the craniofacial morphology using cone beam computed tomography (CBCT). Materials and Methods: This study consisted of preorthodontic anonymized CBCT scans of 34 healthy adults in the age span of 18-28 years. The volume was calculated using Dolphin 3D R software 11.5 version using semiautomatic segmentation method to calculate nasal volume after determining the nasal airway boundary. The subjects were grouped according to sagittal skeletal relation, craniofacial width, facial index, and facial form. Results: There was statistically significant correlation between nasal volume and craniofacial width (P = 0.009). Conclusion: Nasal volume was correlated only with width of the face and not with width/length ratio of face that could have affected the nasal volume.

We developed a medical image segmentation and preoperative planning application which implements a semiautomatic and a hybrid semiautomatic liver segmentation algorithm. The aim of this study was to evaluate the feasibility of computer-assisted liver tumor surgery using these algorithms which are based on thresholding by pixel intensity value from initial seed points. A random sample of 12 patients undergoing elective high-risk hepatectomies at our institution was prospectively selected to undergo computer-assisted surgery using our algorithms (June 2013-July 2014). Quantitative and qualitative evaluation was performed. The average computer analysis time (segmentation, resection planning, volumetry, visualization) was 45 min/dataset. The runtime for the semiautomatic algorithm was

There is growing interest in minimally invasive breast cancer therapy. Eligibility of patients is, however, dependent on several factors related to the tumor and treatment technology. The aim of this study is to assess the proportion of patients eligible for minimally invasive breast cancer therapy for different safety and treatment margins based on breast tumor location. Patients with invasive ductal cancer were selected from the MARGINS cohort. Semiautomatic segmentation of tumor, skin, and pectoral muscle was performed in Magnetic Resonance images. Shortest distances of tumors to critical organs (ie, skin and pectoral muscle) were calculated. Proportions of eligible patients were determined for different safety and treatment margins. Three-hundred-forty-eight patients with 351 tumors were included. If a 10 mm safety margin to skin and pectoral muscle is required without treatment margin, 72.3% of patients would be eligible for minimally invasive treatment. This proportion decreases to 45.9% for an additional treatment margin of 5 mm. Shortest distances between tumors and critical organs are larger in older patients and in patients with less aggressive tumor subtypes. If a 10 mm safety margin to skin and pectoral muscle is required, more than two-thirds of patients would be eligible for minimally invasive breast cancer therapy.

Manual segmentation of hepatic metastases in ultrasound images acquired from patients suffering from pancreatic cancer is common practice. Semiautomatic measurements promising assistance in this process are often assessed using a small number of lesions performed by examiners who already know the algorithm. In this work, we present the application of an algorithm for the segmentation of liver metastases due to pancreatic cancer using a set of 105 different images of metastases. The algorithm and the two examiners had never assessed the images before. The examiners first performed a manual segmentation and, after five weeks, a semiautomatic segmentation using the algorithm. They were satisfied in up to 90% of the cases with the semiautomatic segmentation results. Using the algorithm was significantly faster and resulted in a median Dice similarity score of over 80%. Estimation of the inter-operator variability by using the intra class correlation coefficient was good with 0.8. In conclusion, the algorithm facilitates fast and accurate segmentation of liver metastases, comparable to the current gold standard of manual segmentation., Comment: 7 pages, 3 Figures, 3 Tables, 46 References

The goal of this study was to develop a semiautomatic segmentation technique of the abdominal aorta to determine the arterial input function (AIF). A total of 24 patients having therapy naive abdominal cancers were imaged using DCE-MRI on a 3T MR scanner. DCE-MRI continued for 4.2 minutes with 2.1 seconds temporal resolution (120 acquisitions). Gadoteridol (0.1 mmol/kg) was infused intravenously at 30 seconds after starting DCE-MRI, and flushed with 20-ml saline (2 ml/s). Patients were instructed to hold breath after maximal inhalation, and repeat as needed to full inspiration. The location of the abdominal aorta was manually identified, but its segmentation and motion tracking were automatically implemented. AIFs determined in the aortic region with and without tracking motion were statistically compared. The aortic region was further segmented into multiple smaller regions, and the AIF change according to the size of the region of interest (ROI) was examined. The displacement of the abdominal aorta during DCE-MRI was 3.4±2.3 (mean±SD) mm. The root mean square error (RMSE) of AIF from the best fitting curve was 0.110±0.010 mM after motion correction, which was significantly smaller than that before motion correction (0.134±0.016 mM; p

Objective: to provide a proof-of-concept tool for segmenting chronic wounds and transmitting the results as instructions and coordinates to a bioprinter robot and thus facilitate the treatment of chronic wounds. Methods: several segmentation methods used for measuring wound geometry, including edge-detection and morphological operations, region-growing, Livewire, active contours, and texture segmentation, were compared on 26 images from 15 subjects. Ground-truth wound delineations were generated by a dermatologist. The wound coordinates were converted into G-code understandable by the bioprinting robot. Due to its desirable properties, alginate hydrogel was synthesized by dissolving 16% (w/v) sodium-alginate and 4% (w/v) gelatin in deionized water and used for cell encapsulation. Results: Livewire achieved the best performance, with minimal user interaction: 97.08%, 99.68% 96.67%, 96.22, 98.15, and 32.26, mean values, respectively, for accuracy, sensitivity, specificity, Jaccard index, Dice similarity coefficient, and Hausdorff distance. The bioprinter robot was able to print skin cells on the surface of skin with a 95.56% similarity between the bioprinted patch's dimensions and the desired wound geometry. Conclusion: we have designed a novel approach for the healing of chronic wounds, based on semiautomatic segmentation of wound images, improving clinicians’ control of the bioprinting process through more accurate coordinates. Significance: this study is the first to perform wound bioprinting based on image segmentation. It also compares several segmentation methods used for this purpose to determine the best.

Electron tomography is a powerful tool for visualizing subcellular organelles. With the advances in cryo-fixation techniques, it is now possible to reconstruct complex structures in cells preserved close to their native states in three-dimension (3D) using electron tomography. In order to better visualize these objects, 3D models are made from outlines of organelles in individual tomographic slices, which can be used to display morphological features and quantify structural parameters. While outlines of simple organelles can be drawn by hand fairly quickly, it is possible to accelerate 3D modeling of more complex organelles by means of semiautomatic segmentation. In this chapter, we use the example of reconstructing Golgi cisternae of a plant cell into 3D models using the semiautomatic protocol.

International audience; Background - Patient-specific anatomy may influence the final intraventricular positioning of inflow cannula in left ventricular assist device (LVAD) recipients. An association exists between such positioning and clinical outcomes (specifically, orientation toward the interventricular septum has negative prognostic implications). Alternative commercially available LVADs are characterized by markedly different design, with potential consequences on intrathoracic fitting among individual patients. Material and methods - A cohort of 13 LVAD recipients (either HeartMate II-group A or Jarvik 2000 Flowmaker-group B) was evaluated. On postoperative computed tomography scans, we reconstructed the implanted LVAD (semiautomatic segmentation), defined the target mitral orifice (3D Slicer software), and built a coordinate system to quantify the coaxiality of the cannula with the mitral valve axis (angles φ and θ, expressed as percentage variation from the ideal value φ = θ = 0°). Results - Group A presented significantly greater average percentage variation of the φ angle (significantly greater orientation of the intraventricular cannula toward the interventricular septum; 33.2% ± 32.1% versus 1.9% ± 0.9%, P = 0.001). Group A presented significantly greater average percentage variation of the θ angle (52.7% ± 23.6% versus 14.5% ± 6.3%, P = 0.013). Conclusions - The device assessed in group B showed in the present series better average coaxiality with the mitral orifice. Such finding is related with its design (total intraventricular placement) and interaction with thoracic structures. The present method is being integrated in the development of LVAD virtual implantation tools and may help physicians in patient-specific selection among alternative devices.

In 2005, an application for surgical planning called AYRA $${\textregistered }$$ was designed and validated by different surgeons and engineers at the Virgen del Rocio University Hospital, Seville (Spain). However, the segmentation methods included in AYRA and in other surgical planning applications are not able to segment accurately tumors that appear in soft tissue. The aims of this paper are to offer an exhaustive validation of an accurate semiautomatic segmentation tool to delimitate retroperitoneal tumors from CT images and to aid physicians in planning both radiotherapy doses and surgery. A panel of 6 experts manually segmented 11 cases of tumors, and the segmentation results were compared exhaustively with: the results provided by a surgical planning tool (AYRA), the segmentations obtained using a radiotherapy treatment planning system (Pinnacle $$^{\textregistered }$$ ), the segmentation results obtained by a group of experts in the delimitation of retroperitoneal tumors and the segmentation results using the algorithm under validation. 11 cases of retroperitoneal tumors were tested. The proposed algorithm provided accurate results regarding the segmentation of the tumor. Moreover, the algorithm requires minimal computational time—an average of 90.5% less than that required when manually contouring the same tumor. A method developed for the semiautomatic selection of retroperitoneal tumor has been validated in depth. AYRA, as well as other surgical and radiotherapy planning tools, could be greatly improved by including this algorithm.

Epicardial adipose tissue (EAdT) is metabolically active and likely contributes to atrial fibrillation (AF) through the release of inflammatory cytokines into the myocardium or through its rich innervation with ganglionated plexi at the pulmonary vein ostia. The electrophysiologic mechanisms underlying the association between EAdT and AF remain unclear.The purpose of this study was to investigate the association of EAdT with adjacent myocardial substrate.Thirty consecutive patients who underwent cardiac computed tomography as well as electroanatomic mapping in sinus rhythm before an initial AF ablation procedure were studied. Semiautomatic segmentation of atrial EAdT was performed and registered anatomically to the voltage map.In multivariable regression analysis clustered by patient, age (-0.01 per year) and EAdT (-0.29) were associated with log bipolar voltage as well as low-voltage zones (0.5 mV). Age (odds ratio [OR]: 1.02 per year), male gender (OR: 3.50), diabetes (OR: 2.91), hypertension (OR: 2.55), and EAdT (OR: 8.56) were associated with fractionated electrograms, and age (OR: 2.80), male gender (OR: 3.00), and EAdT (OR: 7.03) were associated with widened signals. Age (OR: 1.03 per year) and body mass index (OR: 1.06 per kg/mThe presence of overlaying EAdT was associated with lower bipolar voltage and electrogram fractionation as electrophysiologic substrates for AF. EAdT was not a statistical mediator of the association between clinical variables and AF substrate. Body mass index was directly associated with the presence of EAdT in patients with AF.

PURPOSE To develop image analysis software usable by nonexpert graders to segment geographic atrophy (GA) from dry AMD and to quantify rim area focal hyperautofluorescence (RAFH) surrounding GA on fundus autofluorescence (FAF) images. To compare the GA progression predictions based on RAFH with those of a validated qualitative classification system. METHODS Retrospective analysis of serial FAF images from 49 eyes of 30 subjects with GA was performed using MATLAB-based software (MathWorks, Natick, MA, USA). Correlation between RAFH and progression of GA was analyzed using Spearman correlation. Comparisons of lesion growth rate between RAFH tertiles used generalized estimating equations and Kruskal-Wallis testing. Interobserver variability in lesion size, growth rate and RAFH were compared between two expert and one nonexpert grader using Bland-Altman statistics. RESULTS Rim area focal hyperautofluorescence was positively correlated with GA progression rate (ρ = 0.49, P < 0.001). Subjects in the middle or highest RAFH tertile were at greater risk of progression (P = 0.005 and P = 0.001, respectively). Mean difference in RAFH was 0.012 between expert and -0.005 to 0.017 between expert and nonexperts. Mean difference in lesion size (mm2) was 0.11 between expert and -0.29 to 0.41 between expert and nonexperts. Mean difference in lesion growth rate (mm2/mo) was 0.0098 between expert and -0.027 to 0.037 between expert and nonexperts. Risk stratification based on RAFH tertile was 96% identical across all graders. CONCLUSIONS Our semiautomated image analysis software facilitates stratification of progression risk based on RAFH and enabled a nonexpert grader with minimal training to obtain results comparable to expert graders. Predictions based on RAFH were similar to those of a validated qualitative classification system.

The aim of this study is to determine the magnitude of change in spleen volume on CT in subjects sustaining blunt abdominal trauma without hemorrhage relative to patients without disease and how the spleen volumes are distributed. Sixty-seven subjects with blunt abdominal trauma and 101 control subjects were included in this retrospective single-center, IRB-approved, and HIPAA-compliant study. Patients with an injured spleen were excluded. Using a semiautomatic segmentation program, two readers computed spleen volumes from CT. Spleen volume distribution in male and female trauma and control cohorts were compared nonparametrically. Spleen volume plotted against height, weight, and age were analyzed by linear regression. The number of females and males are, respectively, 35 and 32 in trauma subjects and 69 and 32 among controls. Female trauma patients (49.6 years) were older than males (39.8 years) (p = 0.02). Distributions of spleen volume were not normal, skewed above their means, requiring a nonparametric comparison. Spleen volumes in trauma patients were smaller than those in controls with medians of 230 vs 294 mL in males(p

International audience; Background Mechanical and hemodynamic factors are among the determinants of patient-device interaction and early-term and long-term outcomes in left ventricular assist device (LVAD) recipients. Material and methods We are currently developing computer simulation tools aimed at (1) analyze the intrathoracic and intracavitary positioning of LVADs after implantation and establish correlation with clinical outcomes; (2) assist surgeons in the choice of device and of left ventricular coring site for optimized intrathoracic placement and function; and (3) facilitate the planning of less-invasive LVAD implantation. A virtual representation of LVAD (mesh device component) was created through cone-beam computed tomography and semiautomatic segmentation. A modular framework software (CamiTK, Grenoble, France) was used to create a three-dimensional representation of patients' computed tomography (CT) scan and incorporate the mesh device component for virtual implantation. Results Device reconstruction was included into a dedicated software with the purposes of virtual implantation, based on the preoperative CT scan of surgical candidates. Conclusions We present herein the first digital reconstruction of the novel HeartMate 3 LVAD. Virtual implantation on the basis of preoperative CT scan is feasible within a user-friendly interactive software. Future studies will be focused on correlation with clinical variables. © 2016 Elsevier Inc.

International audience; Purpose: To propose a postprocessing technique that measures tumor surface with insufficient ablative margins (r 5 mm) on magnetic resonance (MR) imaging to predict local tumor progression (LTP) following radiofrequency (RF) ablation.Materials and Methods: A diagnostic method is proposed based on measurement of tumor surface with a margin r 5 mm on MR imaging. The postprocessing technique includes fully automatic registration of pre-and post–RF ablation MR imaging, a semiautomatic segmentation of pre–RF ablation tumor and post–RF ablation volume, and a subsequent calculation of the three-dimensional exposed tumor surface area. The ability to use this surface margin r 5 mm to predict local recurrence at 2 years was then tested on 16 patients with cirrhosis who were treated by RF ablation with a margin r 5 mm in 2012: eight with LTP matched according to tumor size and number and α-fetoprotein level versus eight without local recurrence. Results: The error of estimated tumor surface with a margin r 5 mm was less than 12%.Results of a log-rank test showed that patients with a tumor surface area 4 425 mm 2 had a 2-year LTP rate of 77.5%, compared with 25% for patients with a tumor surface area r 425 mm 2 (P ¼ .018).Conclusions: This proof-of-concept study proposes an accurate and reliable postprocessing technique to estimate tumor surface with insufficient ablative margins, and underscores the potential usefulness of tumor surface with a margin r 5 mm to stratify patients with HCC treated by RF ablation according to their risk of LTP.

Purpose Accurate segmentation of lung nodules is crucial in the development of imaging biomarkers for predicting malignancy of the nodules. Manual segmentation is time consuming and affected by inter-observer variability. We evaluated the robustness and accuracy of a publically available semiautomatic segmentation algorithm that is implemented in the 3D Slicer Chest Imaging Platform (CIP) and compared it with the performance of manual segmentation. Methods CT images of 354 manually segmented nodules were downloaded from the LIDC database. Four radiologists performed the manual segmentation and assessed various nodule characteristics. The semiautomatic CIP segmentation was initialized using the centroid of the manual segmentations, thereby generating four contours for each nodule. The robustness of both segmentation methods was assessed using the region of uncertainty (δ) and Dice similarity index (DSI). The robustness of the segmentation methods was compared using the Wilcoxon-signed rank test (pWilcoxon

Semiautomatic segmentation methods using High Resolution Computed Tomography (HRCT) or Magnetic Resonance Imaging give accurate and reproducible volumetric measurements in various intracranial diseases. In this prospective study, for the first time in literature, with the help of a new semiautomatic segmentation technique and coronal HRCT, we correlated the volumes and cross-sectional areas of the nasal cavity with those obtained by clinical acoustic rhinometry in 14 patients with chronic sinusitis. The measurements obtained by both techniques showed statistically significant correlations between volumes in the anterior and middle parts, but statistically poor correlations between the volumes in the posterior part of the nasal cavity. Coronal HRCT and our new microcomputer applicable semiautomatic segmentation software proved compatible with daily clinical practice. Based on the promising results of our study, we recommend the use of this technique in the validation studies of acoustic rhinometry and in complicated cases as a complementary examination in the evaluation of nasal cavity.

Purpose. To evaluate whether 3T clinical MRI with a small-animal coil and gradient-echo (GE) sequence could be used to characterize long-term left ventricular remodelling (LVR) following nonreperfused myocardial infarction (MI) using semi-automatic segmentation software (SASS) in a rat model.Materials and Methods. 5 healthy rats were used to validate left ventricular mass (LVM) measured by MRI with postmortem values. 5 sham and 7 infarcted rats were scanned at 2 and 4 weeks after surgery to allow for functional and structural analysis of the heart. Measurements included ejection fraction (EF), end-diastolic volume (EDV), end-systolic volume (ESV), and LVM. Changes in different regions of the heart were quantified using wall thickness analyses.Results. LVM validation in healthy rats demonstrated high correlation between MR and postmortem values. Functional assessment at 4 weeks after MI revealed considerable reduction in EF, increases in ESV, EDV, and LVM, and contractile dysfunction in infarcted and noninfarcted regions.Conclusion. Clinical 3T MRI with a small animal coil and GE sequence generated images in a rat heart with adequate signal-to-noise ratio (SNR) for successful semiautomatic segmentation to accurately and rapidly evaluate long-term LVR after MI.

Metachromatic leukodystrophy is a lysosomal storage disorder leading to progressive demyelination of brain white matter. This is sensitively detected using magnetic resonance imaging. The volume of demyelination, the "demyelination load," could serve as a useful parameter for assessing both the natural course of the disease and treatment effects. The aim of this study was to develop and validate a semiautomated approach for determining the demyelination load to achieve reliable and time-efficient segmentation results.The demyelination load was determined in 77 magnetic resonance imaging data sets from 35 patients both manually and semiautomatically. For manual segmentation, regarded as the gold standard, the software ITK-Snap was used. For semiautomatic segmentation, a new algorithm called Clusterize was developed and implemented in MATLAB, consisting of automatic iterative region growing followed by the interactive selection of clusters. Results were compared in terms of the obtained volumes, spatial overlap, and time taken to conduct the segmentation.Performance of the semiautomatic algorithm was excellent, with the volumes generated by the new algorithm showing good agreement with the ones generated by the gold standard (93.4 ± 45.5 vs 96.1 ± 49.0 mL, P = NS) with high spatial overlap (Dice's similarity coefficient = 0.7861 ± 0.0697). The semiautomatic algorithm was significantly faster than the gold standard (8.2 vs 27.0 min, P.001). Intrarater and interrater reliability determined high reproducibility of the method.The demyelination load in metachromatic leukodystrophy can be determined in a time-efficient manner using a semiautomatic algorithm, showing high agreement with the current gold standard.

Purpose To demonstrate that manual prostate segmentation in transrectal ultrasound images can be replaced with semiautomatic segmentation. Methods and Materials Semiautomatic segmentation using a tapered ellipsoid model was applied to transrectal ultrasound images. Region-based volumetric evaluation was performed between original and physician-reviewed semiautomatic contours. For dosimetric assessment, treatment plans generated on semiautomatic contours were overlaid on physician-reviewed semiautomatic contours and dose parameters were computed. To establish a threshold for the acceptable amount of dosimetric degradation below which the adoption of semiautomatic planning is unacceptable, the range of variability in dosimetric quality attributed to manual variability was obtained and compared with that of semiautomatic contours. Results An average volume error (1—Dice similarity coefficient) of less than 7% between semiautomatic and manual volumes (140 cases) was obtained. The difference between the mean V100 of plans created for semiautomatic contours then overlaid on physician-reviewed semiautomatic contours and the original V100 values, that is, before overlaying on the physician-reviewed contours (41 cases) was lower than 5%. An average total duration of 2–4 min, which includes algorithm initialization, 11.67 ± 3.57 s algorithm time, and contour modification is required per case. This algorithm is being used at the British Columbia Cancer Agency and to this date has been applied for the treatment of more than 600 patients. Conclusions In terms of volumetric and dosimetric accuracy, the proposed algorithm is a suitable replacement for manual segmentation in the context of our planning technique. The benefits are shorter segmentation times; greater consistency; less reliance on user experience; and smooth, symmetric contours.

Magnetic resonance imaging with arterial spin labeling (ASL) is a noninvasive approach to measure organ perfusion. The purpose of this study was to evaluate the reproducibility of ASL kidney perfusion measurements with semiautomatic segmentation, which allows separate quantification of cortical and medullary perfusion. The right kidneys of 14 healthy volunteers were examined 6 times on 2 occasions (3 times at each occasion). There was a 10-minute pause between each examination and a 14-day interval between the 2 occasions. Cortical, medullary, and whole kidney parenchymal perfusion was determined with customized semiautomatic segmentation software. Coefficient of variances (CVs) and intraclass correlations (ICCs) were calculated. Mean whole, cortical, and medullary kidney perfusion was 307.26 ± 25.65, 337.10 ± 34.83, and 279.61 ± 26.73 mL/min/100 g, respectively. On session 1, mean perfusion for the whole kidney, cortex, and medulla was 307.08 ± 26.91, 336.79 ± 36.54, and 279.60 ± 27.81 mL/min/100 g, respectively, and on session 2, 307.45 ± 24.65, 337.41 ± 33.48, and 279.61 ± 25.94 mL/min/100 g, respectively (P > 0.05; R2 = 0.60/0.59/0.54). For whole, cortical, and medullary kidney perfusion, the total ICC/CV were 0.97/3.43 ± 0.86%, 0.97/4.19 ± 1.33%, and 0.96/4.12 ± 1.36%, respectively. Measurements did not differ significantly and showed a very good correlation (P > 0.05; R2 = 0.75/0.76/0.65). ASL kidney measurements combined with operator-independent semiautomatic segmentation revealed high correlation and low variance of cortical, medullary, and whole kidney perfusion.