Aaron D. Ward

MRI-Based 3D Shape Analysis of Thigh Muscles : Patients with Chronic Obstructive Pulmonary Disease Versus Healthy Adults

RATIONALE AND OBJECTIVEnBecause lower limb muscles differ in architecture and function, the systemic effects of chronic obstructive pulmonary disease (COPD) and related disuse may result in regional abnormalities. The purpose of this study was to investigate the differences between patients with COPD and healthy controls in three-dimensional shape and size measurements of individual thigh muscles.nnnMATERIALS AND METHODSnTwenty patients with COPD and 20 healthy adults (aged 55-79 years) underwent magnetic resonance imaging of the thighs. After manual segmentation of individual knee extensor and flexor muscles, the three-dimensional shape of each muscle was obtained using specialized software. Eight shape descriptors were computed both globally (for the whole muscle) and regionally (for portions of the muscle). A two-tailed t test with a modified Bonferroni correction was used to compare group differences.nnnRESULTSnCompared to the thigh muscles of healthy subjects, vastus intermedius and semimembranosus showed the most shape abnormalities in the COPD group (P < .01). Greater regional shape anomalies in the COPD group were found in the middle to proximal regions of all knee extensor muscles and the middle region of the semimembranosus muscle, compared to those of the control group (P < .01). In the COPD group, more shape abnormalities were found in the knee extensors than in the knee flexors (P < .01).nnnCONCLUSIONSnA non-uniform distribution of atrophy and size changes was found across knee extensors and flexors in patients with COPD. Further research is required to investigate the underlying mechanisms of regional morphologic abnormalities of the thigh muscles and the increased susceptibility of the knee extensors to atrophy-related anatomic anomalies in COPD.

QUANTIFICATION AND VISUALIZATION OF LOCALIZED AND INTUITIVE SHAPE VARIABILITY USING A NOVEL MEDIAL-BASED SHAPE REPRESENTATION

Quantification and visualization of anatomical shape variability in different populations is essential for diagnosis and tracking progression of diseases. We present a new 3D medial-based shape representation method capable of analysis and visualization of 3D anatomy and demonstrate its ability to quantify and highlight shape variability in an intuitive manner. 3D shapes are represented via orientations and elongations of one or more medial sheets, along with thickness values encoding the distances to the shape surface. Two parameters traverse each medial sheet and are mapped to orientation, elongation, and thickness values; we call this map a medial patch. Shape variability is decomposed intuitively into bend, stretch, or bulge deformations, via operators acting on the components of the medial patch. In a simple manner, the location, extent, type, and amplitude of the deformation operators can be specified to capture local and global intuitive shape variability. We demonstrate the capabilities and intuitiveness of this approach through synthetic 3D shape deformations, as well as deformations that capture the 3D shape of an anatomical structure. We demonstrate the ability to highlight regions containing specific types of intuitive changes in anatomy.

3D Bicipital Groove Shape Analysis and Relationship to Tendopathy

The bicipital groove of the proximal humerus is formed by the medial and lateral tuberosities and serves to retain the long biceps tendon in its proper place as the arm moves. Bicipital root and proximal tendon disorders are an important symptom generator in the shoulder. The accuracy of the diagnosis of many shoulder disorders visually without quantitative shape analysis is limited, motivating a clinical need for some ancillary method to assess the proximal biceps. In previous studies, measurements of bicipital groove shape were 2-dimensional (2D), taken from a single axial slice. Because of significant variations in groove shape from one axial slice to another in a single patient, such approaches risk overlooking shape features important to long biceps tendon pathology. In this paper, we present a study of the relationship between bicipital groove shape and long biceps tendon pathology using a novel 3-dimensional (3D) shape descriptor for the bicipital groove. In addition to providing quantitative measures of the shape of the groove and its relation to tendopathy, the new descriptor allows for intuitive, descriptive visualization of the shape of the groove.

Statistical shape modeling using MDL incorporating shape, appearance, and expert knowledge

We propose a highly automated approach to the point correspondence problem for anatomical shapes in medical images. Manual landmarking is performed on a small subset of the shapes in the study, and a machine learning approach is used to elucidate the characteristic shape and appearance features at each landmark. A classifier trained using these features defines a cost function that drives key landmarks to anatomically meaningful locations after MDL-based correspondence establishment. Results are shown for artificial examples as well as real data.

Extraction of the plane of minimal cross-sectional area of the corpus callosum using template-driven segmentation

Changes in corpus callosum (CC) size are typically quantified in clinical studies by measuring the CC cross-sectional area on a midsagittal plane. We propose an alternative measurement plane based on the role of the CC as a bottleneck structure in determining the rate of interhemispheric neural transmission. We designate this plane as the Minimum Corpus Callosum Area Plane (MCCAP), which captures the cross section of the CC that best represents an upper bound on interhemispheric transmission. Our MCCAP extraction method uses a nested optimization framework, segmenting the CC as it appears on each candidate plane, using registration-based segmentation. We demonstrate the robust convergence and high accuracy of our method for magnetic resonance images and present preliminary clinical results showing higher sensitivity to disease-induced atrophy.

Learning Fourier descriptors for computer-aided diagnosis of the supraspinatus.

RATIONALE AND OBJECTIVESnSupraspinatus muscle disorders are frequent and debilitating, resulting in pain and a limited range of shoulder motion. The gold standard for diagnosis involves an invasive surgical procedure. As part of a proposed clinical workflow for noninvasive computer-aided diagnosis (CAD) of the condition of the supraspinatus, we present a method to classify three-dimensional shapes of the muscle into relevant pathology groups, based on magnetic resonance (MR) images.nnnMATERIALS AND METHODSnWe obtained MR images of the shoulder from 72 patients, separated into five pathology groups. The imaging protocol ensures that the supraspinatus is consistently oriented relative to the MR imaging plane for each scan. Next, we compute the Fourier coefficients of two-dimensional contours lying on parallel imaging planes and integrate the corresponding frequency components across all contours. To classify the shapes, we learn the Fourier coefficients that best distinguish the different classes.nnnRESULTSnWe show that our method leads to significant improvement when compared to previous work. We are able to distinguish between normal shapes and shapes that possess a pathology with an accuracy of almost 100%. Moreover, we can differentiate between the different pathology groups with an average accuracy of 86%.nnnCONCLUSIONnWe confirm that analyzing the three-dimensional shape of the muscle has potential as a form of diagnosis reinforcement to assess the condition of the supraspinatus. Moreover, our proposed descriptor based on Fourier coefficients is able to distinguish the different pathology groups with accuracies higher than those obtained by previous work, indicating its potential application to support a system for CAD of the supraspinatus.

3D shape description of the bicipital groove of the proximal humerus

Bicipital root and proximal tendon disorders are an important symptom generator in the shoulder. The accuracy of the diagnosis of many shoulder disorders visually without quantitative shape analysis is limited, motivating a clinical need for some ancillary method to access the proximal biceps. Because of the known inter-relationship of the bicipital groove (BG) with several types of disorders, we propose an approach to the 3D shape description of the BG that captures information relevant to disorders of the shoulder (e.g. width, depth, angles of walls, presence of spurs). Our approach is medial-axis based and captures intuitive aspects of shape such as thickness, bending, and elongation. Our proposed method overcomes the well-known problem of boundary sensitivity in the medial representation as it is applied to representation and analysis of BG shape. We give preliminary quantitative results indicating that this representation does capture shape variation within our experimental data, providing motivation to explore more sophisticated statistical analysis based on this representation in future work. We also provide a method for semi-automatic segmentation of the BG from computed tomography (CT) scans of the shoulder; an important precursor step to BG shape analysis.