Vocal cord movement: can it be accurately graded?

INTRODUCTION: Flexible nasendoscopy (FNE) is the principal assessment method for vocal cord movement. Because the procedure is inherently subjective it may not be possible for clinicians to grade the degree of vocal cord movement reliably. The aim of this study was to assess the accuracy and consistency of grading vocal cord movement as viewed via FNE. METHODS: Thirty FNE videos, without sound or clinical information, were assessed by six consultant head and neck surgeons. The surgeons were asked to assess and grade right and left vocal cord movement independently, based on a five-category scale. This process was repeated three times on separate occasions. Agreement and reliability were assessed. RESULTS: Mean overall observed inter-rater agreement was 67.7% (sd 1.9) with the five-category scale, increasing to 91.4% (sd 1.9) when a three-category scale was derived. Mean overall observed intra-rater agreement was 78.3% (sd 9.7) for five categories, increasing to 93.1% (sd 3.3) for three categories. Discriminating vocal cord motion was less reliable using the five-category scale (k = 0.52) than with the three-category scale (k = 0.68). CONCLUSIONS: This study demonstrates quantitatively that it is challenging to accurately and consistently grade subtle differences in vocal cord movement, as proven by the reduced agreement and reliability when using a five-point scale instead of a three-point scale. The study highlights the need for an objective measure to help in the assessment of vocal cord movement.

Validation of a Magnetic Resonance Imaging-based Auto-contouring Software Tool for Gross Tumour Delineation in Head and Neck Cancer Radiotherapy Planning.

AIMS: To carry out statistical validation of a newly developed magnetic resonance imaging (MRI) auto-contouring software tool for gross tumour volume (GTV) delineation in head and neck tumours to assist in radiotherapy planning. MATERIALS AND METHODS: Axial MRI baseline scans were obtained for 10 oropharyngeal and laryngeal cancer patients. GTV was present on 102 axial slices and auto-contoured using the modified fuzzy c-means clustering integrated with the level set method (FCLSM). Peer-reviewed (C-gold) manual contours were used as the reference standard to validate auto-contoured GTVs (C-auto) and mean manual contours (C-manual) from two expert clinicians (C1 and C2). Multiple geometric metrics, including the Dice similarity coefficient (DSC), were used for quantitative validation. A DSC≥0.7 was deemed acceptable. Inter- and intra-variabilities among the manual contours were also validated. The two-dimensional contours were then reconstructed in three dimensions for GTV volume calculation, comparison and three-dimensional visualisation. RESULTS: The mean DSC between C-gold and C-auto was 0.79. The mean DSC between C-gold and C-manual was 0.79 and that between C1 and C2 was 0.80. The average time for GTV auto-contouring per patient was 8 min (range 6-13 min; mean 45 s per axial slice) compared with 15 min (range 6-23 min; mean 88 s per axial slice) for C1. The average volume concordance between C-gold and C-auto volumes was 86.51% compared with 74.16% between C-gold and C-manual. The average volume concordance between C1 and C2 volumes was 86.82%. CONCLUSIONS: This newly designed MRI-based auto-contouring software tool shows initial acceptable results in GTV delineation of oropharyngeal and laryngeal tumours using FCLSM. This auto-contouring software tool may help reduce inter- and intra-variability and can assist clinical oncologists with time-consuming, complex radiotherapy planning.

LV wall segmentation using the variational level set method (LSM) with additional shape constraint for oedema quantification.

In this paper an automatic algorithm for the left ventricle (LV) wall segmentation and oedema quantification from T2-weighted cardiac magnetic resonance (CMR) images is presented. The extent of myocardial oedema delineates the ischaemic area-at-risk (AAR) after myocardial infarction (MI). Since AAR can be used to estimate the amount of salvageable myocardial post-MI, oedema imaging has potential clinical utility in the management of acute MI patients. This paper presents a new scheme based on the variational level set method (LSM) with additional shape constraint for the segmentation of T2-weighted CMR image. In our approach, shape information of the myocardial wall is utilized to introduce a shape feature of the myocardial wall into the variational level set formulation. The performance of the method is tested using real CMR images (12 patients) and the results of the automatic system are compared to manual segmentation. The mean perpendicular distances between the automatic and manual LV wall boundaries are in the range of 1-2 mm. Bland-Altman analysis on LV wall area indicates there is no consistent bias as a function of LV wall area, with a mean bias of -121 mm(2) between individual investigator one (IV1) and LSM, and -122 mm(2) between individual investigator two (IV2) and LSM when compared to two investigators. Furthermore, the oedema quantification demonstrates good correlation when compared to an expert with an average error of 9.3% for 69 slices of short axis CMR image from 12 patients.

CMRI based 3D left ventricle motion analysis on patients with acute myocardial infarction.

3D Quantitative measurement of left ventricle (LV) motion on patients with acute myocardial infarction has been recognized as essential for effective LV function diagnosis. This paper presents a method to quantify 3D LV motion obtained from conventional CINE MRI using image analysis based on mathematical modeling. Level set method is employed for segmentation, and a 3D LV geometry was reconstructed by co-registering different views of MRI images. A mathematical model of LV geometry was then constructed to quantitatively describe the LV wall inward motion. The results using real data show that the method is able to quantify the LV inward motion, and can clearly represent the changed motion pattern with the follow-up data. Furthermore, the LV motion analysis for 8 patients with acute myocardial infarction (MI) show that high inward motion occurs mainly in the basal region of LV while a negative relation is found between LV ejection fraction (EF) improvement after acute MI and solely basal region inward motion, which could be helpful for diagnosis and LV EF recovery prediction.

Automatic cardiac LV boundary detection and tracking using hybrid fuzzy temporal and fuzzy multiscale edge detection.

This paper describes a new fully automatic fuzzy multiresolution-based algorithm for cardiac left ventricular (LV) epicardial and endocardial boundary detection and tracking on a sequence of short axis (SA) echocardiographic images of a complete cardiac cycle. This is a necessary step for automatic quantification of cardiac function using echo images. The proposed method is a "center-based" approach in which epicardial and endocardial boundary edge points are searched for on radial lines emanating from the LV center point. The central point of the LV cavity is estimated using a fuzzy-based technique in which the "uncertain" spatial, morphological, and intensity information of the image are represented as fuzzy sets and then combined by fuzzy operators. Edge-detection stage uses multiscale spatial and temporal information in a fuzzy multiresolution framework to identify a single moving edge point for each one of the epicardial and endocardial boundaries over the M radii in the N frames of a complete cardiac cycle. The raw extracted edge points are then processed in the wavelet domain to reduce the effects of noise from the boundaries and papillary muscles from the endocardial boundary extraction process. Finally, a uniform cubic B-spline approximation method is used to define the closed LV boundaries. Experiments with simulated and real echocardiographic images are presented.