Claude Kauffmann

Reliability of a quantification imaging system using magnetic resonance images to measure cartilage thickness and volume in human normal and osteoarthritic knees

OBJECTIVE The aim of this study was to evaluate the reliability of a software tool that assesses knee cartilage volumes using magnetic resonance (MR) images. The objectives were to assess measurement reliability by: (1) determining the differences between readings of the same image made by the same reader 2 weeks apart (test-retest reliability), (2) determining the differences between the readings of the same image made by different readers (between-reader agreement), and (3) determining the differences between the cartilage volume readings obtained from two MR images of the same knee image acquired a few hours apart (patient positioning reliability). METHODS Forty-eight MR examinations of the knee from normal subjects, patients with different stages of symptomatic knee osteoarthritis (OA), and a subset of duplicate images were independently and blindly quantified by three readers using the imaging system. The following cartilage areas were analyzed to compute volumes: global cartilage, medial and lateral compartments, and medial and lateral femoral condyles. RESULTS Between-reader agreement of measurements was excellent, as shown by intra-class correlation (ICC) coefficients ranging from 0.958 to 0.997 for global cartilage (P<0.0001), 0.974 to 0.998 for the compartments (P<0.0001), and 0.943 to 0.999 for the condyles(P<0.0001). Test-retest reliability of within-reader data was also excellent, with Pearson correlation coefficients ranging from 0.978 to 0.999 (P<0.0001). Patient positioning reliability was also excellent, with Pearson correlation coefficients ranging from 0.978 to 0.999 (P<0.0001). CONCLUSIONS The results of this study establish the reliability of this MR imaging system. Test-retest reliability, between-reader agreement, and patient positioning reliability were all extremely high. This study represents a first step in the overall validation of an imaging system designed to follow progression of human knee OA.

Computer-aided method for quantification of cartilage thickness and volume changes using MRI: validation study using a synthetic model

The primary objective of this study was to develop a computer-aided method for the quantification of three-dimensional (3-D) cartilage changes over time in knees with osteoarthritis (OA). We introduced a local coordinate system (LCS) for the femoral and tibial cartilage boundaries that provides a standardized representation of cartilage geometry, thickness, and volume. The LCS can be registered in different data sets from the same patient so that results can be directly compared. Cartilage boundaries are segmented from 3-D magnetic resonance (MR) slices with a semi-automated method and transformed into offset-maps , defined by the LCS. Volumes and thickness are computed from these offset-maps. Further anatomical labeling allows focal volumes to be evaluated in predefined subregions. The accuracy of the automated behavior of the method was assessed, without any human intervention, using realistic, synthetic 3-D MR images of a human knee. The error in thickness evaluation is lower than 0.12 mm for the tibia and femur. Cartilage volumes in anatomical subregions show a coefficient of variation ranging from 0.11% to 0.32%. This method improves noninvasive 3-D analysis of cartilage thickness and volume and is well suited for in vivo follow-up clinical studies of OA knees.

Noninvasive quantitation of human liver steatosis using magnetic resonance and bioassay methods

The purpose was to evaluate the ability of three magnetic resonance (MR) techniques to detect liver steatosis and to determine which noninvasive technique (MR, bioassays) or combination of techniques is optimal for the quantification of hepatic fat using histopathology as a reference. Twenty patients with histopathologically proven steatosis and 24 control subjects underwent single-voxel proton MR spectroscopy (MRS; 3 voxels), dual-echo in phase/out of phase MR imaging (DEI) and diffusion-weighted MR imaging (DWI) examinations of the liver. Blood or urine bioassays were also performed for steatosis patients. Both MRS and DEI data allowed to detect steatosis with a high sensitivity (0.95 for MRS; 1 for DEI) and specificity (1 for MRS; 0.875 for DEI) but not DWI. Strong correlations were found between fat fraction (FF) measured by MRS, DEI and histopathology segmentation as well as with low density lipoprotein (LDL) and cholesterol concentrations. A Bland-Altman analysis showed a good agreement between the FF measured by MRS and DEI. Partial correlation analyses failed to improve the correlation with segmentation FF when MRS or DEI data were combined with bioassay results. Therefore, FF from MRS or DEI appear to be the best parameters to both detect steatosis and accurately quantify fat liver noninvasively.

Seeded ND medical image segmentation by cellular automaton on GPU.

PurposeWe present a GPU-based framework to perform organ segmentation in N-dimensional (ND) medical image datasets by computation of weighted distances using the Ford–Bellman algorithm (FBA). Our GPU implementation of FBA gives an alternative and optimized solution to other graph-based segmentation techniques.MethodsGiven a number of K labelled-seeds, the segmentation algorithm evolves and segments the ND image in K objects. Each region is guaranteed to be connected to seeds with the same label. The method uses a Cellular Automata (CA) to compute multiple shortest-path-trees based on the FBA. The segmentation result is obtained by K-cuts of the graph in order to separate it in K sets. A quantitative evaluation of the method was performed by measuring renal volumes of 20 patients based on magnetic resonance angiography (MRA) acquisitions. Inter-observer reproducibility, accuracy and validity were calculated and associated computing times were recorded. In a second step, the computational performances were evaluated with different graphics hardware and compared to a CPU implementation of the method using Dijkstra’s algorithm.ResultsThe ICC for inter-observer reproducibility of renal volume measurements was 0.998 (0.997–0.999) for two radiologists and the absolute mean difference between the two readers was lower than 1.2% of averaged renal volumes. The validity analysis shows an excellent agreement of our method with the results provided by a supervised segmentation method, used as reference.ConclusionsThe formulation of the FBA in the form of a CA is simple, efficient and straightforward, and can be implemented in low cost vendor-independent graphics hardware. The method can efficiently be applied to perform organ segmentation and quantitative evaluation in clinical routine.

Analysis of pressure distribution at the body-seat interface in able-bodied and paraplegic subjects using a deformable active contour algorithm

In this paper, a semi-automatic method for segmenting pressure distribution image-based data at the body-seat interface is presented. The purpose of this work was to estimate the surface and the load supported by the ischial tuberosity (IT) region. The proposed method involves three steps: (1) detecting the IT region using a pressure-distribution image gradient; (2) estimating the contour of the IT region by an iterative active contour algorithm and finally (3) estimating the percentage of the surface and the weight-bearing of the IT region in a group of able-bodied (AB) and spinal-cord injury (SCI) subjects. It was found in this study that the weight bearing on the IT for the spinal-cord injured group is distributed on half the surface in comparison with the AB group or the powered wheelchair users groups. The findings of this study provide insights concerning pressure distribution in sitting for the paraplegic and able-bodied.

Measurements and detection of abdominal aortic aneurysm growth: Accuracy and reproducibility of a segmentation software

PURPOSE To validate the reproducibility and accuracy of a software dedicated to measure abdominal aortic aneurysm (AAA) diameter, volume and growth over time. MATERIALS AND METHODS A software enabling AAA segmentation, diameter and volume measurement on computed tomography angiography (CTA) was tested. Validation was conducted in 28 patients with an AAA having 2 consecutive CTA examinations. The segmentation was performed twice by a senior radiologist and once by 3 medical students on all 56 CTAs. Intra and inter-observer reproducibility of D-max and volumes values were calculated by intraclass correlation coefficient (ICC). Systematic errors were evaluated by Bland-Altman analysis. Differences in D-max and volume growth were compared with paired Students t-tests. RESULTS Mean D-max and volume were 49.6±6.2mm and 117.2±36.2ml for baseline and 53.6±7.9mm and 139.6±56.3ml for follow-up studies. Volume growth (17.3%) was higher than D-max progression (8.0%) between baseline and follow-up examinations (p<.0001). For the senior radiologist, intra-observer ICC of D-max and volume measurements were respectively estimated at 0.997 (≥0.991) and 1.000 (≥0.999). Overall inter-observer ICC of D-max and volume measurements were respectively estimated at 0.995 (0.990-0.997) and 0.999 (>0.999). Bland-Altman analysis showed excellent inter-reader agreement with a repeatability coefficient <3mm for D-max, <7% for relative D-max growth, <6ml for volume and <6% for relative volume growth. CONCLUSION Software AAA volume measurements were more sensitive than AAA D-max to detect AAA growth while providing an equivalent and high reproducibility.

Clinical validation of a software for quantitative follow-up of abdominal aortic aneurysm maximal diameter and growth by CT angiography

PURPOSE To compare the reproducibility and accuracy of abdominal aortic aneurysm (AAA) maximal diameter (D-max) measurements using segmentation software, with manual measurement on double-oblique MPR as a reference standard. MATERIALS AND METHODS The local Ethics Committee approved this study and waived informed consent. Forty patients (33 men, 7 women; mean age, 72 years, range, 49-86 years) had previously undergone two CT angiography (CTA) studies within 16 ± 8 months for follow-up of AAA ≥ 35 mm without previous treatment. The 80 studies were segmented twice using the software to calculate reproducibility of automatic D-max calculation on 3D models. Three radiologists reviewed the 80 studies and manually measured D-max on double-oblique MPR projections. Intra-observer and inter-observer reproducibility were calculated by intraclass correlation coefficient (ICC). Systematic errors were evaluated by linear regression and Bland-Altman analyses. Differences in D-max growth were analyzed with a paired Students t-test. RESULTS The ICC for intra-observer reproducibility of D-max measurement was 0.992 (≥ 0.987) for the software and 0.985 (≥ 0.974) and 0.969 (≥ 0.948) for two radiologists. Inter-observer reproducibility was 0.979 (0.954-0.984) for the three radiologists. Mean absolute difference between semi-automated and manual D-max measurements was estimated at 1.1 ± 0.9 mm and never exceeded 5mm. CONCLUSION Semi-automated software measurement of AAA D-max is reproducible, accurate, and requires minimal operator intervention.

Fatty liver deposition and sparing: a pictorial review

ObjectiveFatty liver deposition is a very common finding, but it has many atypical patterns of distribution that can represent diagnostic pitfalls. The purpose of this pictorial essay is to review different patterns of fatty liver deposition and sparing.MethodsWe searched our archive retrospectively, reviewed the literature, and identified six patterns of liver steatosis.ResultsSteatosis may be diffuse, geographic, focal, subcapsular, multifocal or perivascular.ConclusionsPrevious knowledge of atypical patterns of steatosis distribution may prevent misdiagnosis of infiltrative disease or focal liver lesions. When an unusual form of fatty liver deposition is suspected on ultrasound or computed tomography, magnetic resonance imaging may be used to confirm the diagnosis.

Hemorphin 7 Reflects Hemoglobin Proteolysis in Abdominal Aortic Aneurysm

Objective—In human abdominal aortic aneurysm, the accumulation of blood-derived cells and proteases within the mural thrombus plays a pivotal role in the evolution toward vessel wall rupture. We sought to identify peptides released from abdominal aortic aneurysm specimens, characterized by an intraluminal thrombus. Methods and Results—Intraluminal thrombus samples were analyzed by differential proteomics, using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry. A 1309-Da peptide was detected in larger amounts in the newly formed luminal thrombus layer relative to older layers. It was identified as being LVVYPWTQRF (known as LVV-Hemorphin 7), a peptide generated from hemoglobin by cathepsin D. By immunohistochemical analysis, we showed that Hemorphin 7 (H7) colocalizes with cathepsin D and cathepsin G in the luminal layer of the intraluminal thrombus. In vitro, cathepsin G was able to generate H7 peptides at pH 7.4, whereas cathepsin D was only active in acidic conditions. Finally, H7 peptides were shown to be increased 3- to 4-fold in sera of abdominal aortic aneurysm patients relative to controls, and their levels were positively correlated with the volume of the thrombus. Conclusion—Our results suggest that circulating H7 peptides may reflect proteolysis of hemoglobin in the aneurysmal intraluminal thrombus and may be used as a biological marker of pathological vascular remodeling.

Source of Errors and Accuracy of a Two-Dimensional/Three-Dimensional Fusion Road Map for Endovascular Aneurysm Repair of Abdominal Aortic Aneurysm

PURPOSE To evaluate the accuracy and source of errors using a two-dimensional (2D)/three-dimensional (3D) fusion road map for endovascular aneurysm repair (EVAR) of abdominal aortic aneurysm. MATERIALS AND METHODS A rigid 2D/3D road map was tested in 16 patients undergoing EVAR. After 3D/3D manual registration of preoperative multidetector computed tomography (CT) and cone beam CT, abdominal aortic aneurysm outlines were overlaid on live fluoroscopy/digital subtraction angiography (DSA). Patient motion was evaluated using bone landmarks. The misregistration of renal and internal iliac arteries were estimated by 3 readers along head-feet and right-left coordinates (z-axis and x-axis, respectively) before and after bone and DSA corrections centered on the lowest renal artery. Iliac deformation was evaluated by comparing centerlines before and during intervention. A score of clinical added value was estimated as high (z-axis < 3 mm), good (3 mm ≤ z-axis ≤ 5 mm), and low (z-axis > 5 mm). Interobserver reproducibility was calculated by the intraclass correlation coefficient. RESULTS The lowest renal artery misregistration was estimated at x-axis = 10.6 mm ± 11.1 and z-axis = 7.4 mm ± 5.3 before correction and at x-axis = 3.5 mm ± 2.5 and z-axis = 4.6 mm ± 3.7 after bone correction (P = .08), and at 0 after DSA correction (P < .001). After DSA correction, residual misregistration on the contralateral renal artery was estimated at x-axis = 2.4 mm ± 2.0 and z-axis = 2.2 mm ± 2.0. Score of clinical added value was low (n = 11), good (n= 0), and high (n= 5) before correction and low (n = 5), good (n = 4), and high (n = 7) after bone correction. Interobserver intraclass correlation coefficient for misregistration measurements was estimated at 0.99. Patient motion before stent graft delivery was estimated at x-axis = 8 mm ± 5.8 and z-axis = 3.0 mm ± 2.7. The internal iliac artery misregistration measurements were estimated at x-axis = 6.1 mm ± 3.5 and z-axis = 5.6 mm ± 4.0, and iliac centerline deformation was estimated at 38.3 mm ± 15.6. CONCLUSIONS Rigid registration is feasible and fairly accurate. Only a partial reduction of vascular misregistration was observed after bone correction; minimal DSA acquisition is still required.