RESUMEN
Knee osteoarthritis (OA) progression can be monitored by measuring changes in the subchondral bone structure such as area and shape from MR images as an imaging biomarker. However, measurements of these minute changes are highly dependent on the accurate segmentation of bone tissue from MR images and it is challenging task due to the complex tissue structure and inadequate image contrast/brightness. In this paper, a fully automated method for segmenting subchondral bone from knee MR images is proposed. Here, the contrast of knee MR images is enhanced using a gray-level S-curve transformation followed by automatic seed point detection using a three-dimensional multi-edge overlapping technique. Successively, bone regions are initially extracted using distance-regularized level-set evolution followed by identification and correction of leakages along the bone boundary regions using a boundary displacement technique. The performance of the developed technique is evaluated against ground truths by measuring sensitivity, specificity, dice similarity coefficient (DSC), average surface distance (AvgD) and root mean square surface distance (RMSD). An average sensitivity (91.14%), specificity (99.12%) and DSC (90.28%) with 95% confidence interval (CI) in the range 89.74-92.54%, 98.93-99.31% and 88.68-91.88% respectively is achieved for the femur bone segmentation in 8 datasets. For tibia bone, average sensitivity (90.69%), specificity (99.65%) and DSC (91.35%) with 95% CI in the range 88.59-92.79%, 99.50-99.80% and 88.68-91.88% respectively is achieved. AvgD and RMSD values for femur are 1.43 ± 0.23 (mm) and 2.10 ± 0.35 (mm) respectively while for tibia, the values are 0.95 ± 0.28 (mm) and 1.30 ± 0.42 (mm) respectively that demonstrates acceptable error between proposed method and ground truths. In conclusion, results obtained in this work demonstrate substantially significant performance with consistency and robustness that led the proposed method to be applicable for large scale and longitudinal knee OA studies in clinical settings.
Asunto(s)
Imagenología Tridimensional/métodos , Rodilla/diagnóstico por imagen , Imagen por Resonancia Magnética/métodos , Algoritmos , Humanos , Osteoartritis de la Rodilla/diagnóstico por imagenRESUMEN
RATIONALE AND OBJECTIVES: Quantitative assessment of knee articular cartilage (AC) morphology using magnetic resonance (MR) imaging requires an accurate segmentation and 3D reconstruction. However, automatic AC segmentation and 3D reconstruction from hydrogen-based MR images alone is challenging because of inhomogeneous intensities, shape irregularity, and low contrast existing in the cartilage region. Thus, the objective of this research was to provide an insight into morphologic assessment of AC using multilevel data processing of multinuclear ((23)Na and (1)H) MR knee images. MATERIALS AND METHODS: A dual-tuned ((23)Na and (1)H) radio-frequency coil with 1.5-T MR scanner is used to scan four human subjects using two separate MR pulse sequences for the respective sodium and proton imaging of the knee. Postprocessing is performed using customized routines written in MATLAB. MR data were fused to improve contrast of the cartilage region that is further used for automatic segmentation. Marching cubes algorithm is applied on the segmented AC slices for 3D volume rendering and volume is then calculated using the divergence theorem. RESULTS: Fusion of multinuclear MR images results in an improved contrast (factor >3) in the cartilage region. Sensitivity (80.21%) and specificity (99.64%) analysis performed by comparing manually segmented AC shows a good performance of the automated AC segmentation. The average cartilage volume (23.19 ± 1.38 cm(3); coefficient of variation [COV] -0.059) measured from 3D AC models of four data sets shows a marked improvement over average cartilage volume (23.24 cm(3); COV -0.19) reported earlier. CONCLUSIONS: This study confirms the use of multinuclear MR data for cartilage morphology (volume) assessment that can be used in clinical settings.
Asunto(s)
Cartílago Articular/anatomía & histología , Cartílago Articular/metabolismo , Articulación de la Rodilla/anatomía & histología , Articulación de la Rodilla/metabolismo , Imagen por Resonancia Magnética/métodos , Espectroscopía de Protones por Resonancia Magnética/métodos , Sodio/metabolismo , Femenino , Humanos , Aumento de la Imagen/métodos , Masculino , Radiofármacos/farmacocinética , Reproducibilidad de los Resultados , Sensibilidad y Especificidad , Isótopos de Sodio/farmacocinéticaRESUMEN
Early detection of knee osteoarthritis (OA) is of great interest to orthopaedic surgeons, rheumatologists, radiologists, and researchers because it would allow physicians to provide patients with treatments and advice to slow the onset or progression of the disease. Early detection can be achieved by identifying early changes in selected features of degenerative articular cartilage (AC) using non-invasive imaging modalities. Magnetic resonance imaging (MRI) is becoming the standard for assessment of OA. The aim of this paper was to review the influence of MRI on the selection, detection, and measurement of AC features associated with early OA. Our review of the literature indicates that the changes associated with early OA are in cartilage thickness, cartilage volume, cartilage water content, and proteoglycan content that can be accurately, consistently, and non-invasively measured using MRI. Choosing an MR pulse sequence that provides the capability to assess cartilage physiology and morphology in a single acquisition and advanced multi-nuclei MRI is desirable. The results of the review indicate that using an ultra-high magnetic strength, MR imager does not affect early OA detection. In conclusion, MRI is currently the most suitable modality for early detection of knee OA, and future research should focus on the quantitative evaluation of early OA features using advances in MR hardware, software, and data processing with sophisticated image/pattern recognition techniques.
Asunto(s)
Cartílago Articular/patología , Imagen por Resonancia Magnética/métodos , Osteoartritis de la Rodilla/patología , Progresión de la Enfermedad , Humanos , Procesamiento de Imagen Asistido por Computador , Articulación de la Rodilla/patología , Índice de Severidad de la EnfermedadRESUMEN
The onset of osteoarthritis (OA), a most common knee joint disease, can be characterized by the degeneration of articular cartilage (AC). Degenerative changes in AC have been assessed by the morphological and physiological measurements using non-invasive modality such as Magnetic Resonance Imaging (MRI) to obtain MRI images of the knee. However, visualization and quantification of AC from MR images is difficult due to the low visibility contrast of AC compared to surrounding tissues, low and varying signal intensities in cartilage region and variable intensities in different slices of single dataset. In this work, we present a method to fuse multinuclear ((23)Na and (1)H) MR images acquired in the same plane without changing the position of the human knee as well as the Radio Frequency (RF) coil. This work is performed towards our hypothesis that fusion of sodium and proton images will provide an enhanced image that can be used for an accurate assessment of cartilage morphology. Our result shows that merging of sodium knee MR image with proton knee MR image resulting in enhanced contrast information in the cartilage region and resolves low visibility and varying intensities issue with 2D/3D proton MR. We conclude that the proposed method can further be utilized for the accurate assessment of cartilage morphology.
Asunto(s)
Cartílago Articular/patología , Articulación de la Rodilla/patología , Rodilla/patología , Imagen por Resonancia Magnética , Osteoartritis de la Rodilla/patología , Medios de Contraste , Humanos , Aumento de la Imagen/métodos , Osteoartritis de la Rodilla/diagnóstico , Protones , Ondas de Radio , Vasos Retinianos/patología , Sodio/químicaRESUMEN
Osteoarthritis is a common joint disorder that is most prevalent in the knee joint. Knee osteoarthritis (OA) can be characterized by the gradual loss of articular cartilage (AC). Formation of lesion, fissures and cracks on the cartilage surface has been associated with degenerative AC and can be measured by morphological assessment. In addition, loss of proteoglycan from extracellular matrix of the AC can be measured at early stage of cartilage degradation by physiological assessment. In this case, a biochemical phenomenon of cartilage is used to assess the changes at early degeneration of AC. In this paper, a method to measure local sodium concentration in AC due to proteoglycan has been investigated. A clinical 1.5-T magnetic resonance imaging (MRI) with multinuclear spectroscopic facility is used to acquire sodium images and quantify local sodium content of AC. An optimised 3D gradient-echo sequence with low echo time has been used for MR scan. The estimated sodium concentration in AC region from four different data sets is found to be ~225±19mmol/l, which matches the values that has been reported for the normal AC. This study shows that sodium images acquired at clinical 1.5-T MRI system can generate an adequate quantitative data that enable the estimation of sodium concentration in AC. We conclude that this method is potentially suitable for non-invasive physiological (sodium content) measurement of articular cartilage.