AN APPLICATION OF IMAGE PROCESSING TECHNIQUES IN COMPUTED TOMOGRAPHY IMAGE ANALYSIS

An estimate of the thickness of subcutaneous adipose tissue at differing positions around the body was required in a study examining body composition. To eliminate human error associated with the manual placement of markers for measurements and to facilitate the collection of data from a large number of animals and image slices, automation of the process was desirable. The open-source and free image analysis program ImageJ was used. A macro procedure was created that provided the required functionality. The macro performs a number of basic image processing procedures. These include an initial process designed to remove the scanning table from the image and to center the animal in the image. This is followed by placement of a vertical line segment from the mid point of the upper border of the image to the image center. Measurements are made between automatically detected outer and inner boundaries of subcutaneous adipose tissue along this line segment. This process was repeated as the image was rotated (with the line position remaining unchanged) so that measurements around the complete circumference were obtained. Additionally, an image was created showing all detected boundary points so that sites of measurement could be checked by visual inspection. This paper provides a detailed account of this macro, illustrates the effect of its components on the image, and the applicability of standard image processing techniques to veterinary imaging.     

MEASUREMENT OF BODY COMPOSITION IN CATS USING COMPUTED TOMOGRAPHY AND DUAL ENERGY X‐RAY ABSORPTIOMETRY

Dual energy X‐ray absorptiometry (DEXA) is a reference method for assessing body composition but is seldom `accessible in veterinary settings. Computed tomography (CT) can provide similar body composition estimates and we propose that it can be used in body composition studies in animals. We compared CT and DEXA data from 73 healthy adult neutered domestic cats. Three approaches for measuring adipose tissue percentage from full‐body CT scans were explored. By examining the frequency distribution of voxels by Hounsfield unit (HU) value, it is possible to calculate a fat index (Fat%) that is in close agreement with the fat percentages obtained from DEXA scans. Fat% values obtained by the best of the methods had a mean difference of 0.96% (95% confidence interval 0.33–1.59%) from the DEXA results. Fat% obtained by the other two methods were characterized by good correlation but poor agreement and in one of the methods, the difference between the values from the two modalities was proportional to their mean. By using CT, it is possible to obtain body composition estimates that are in close agreement with those available using DEXA. While the significance of individual Fat% measurements obtained from CT can be difficult to interpret and to compare between centers, CT can contribute to research studies concerned either with nutrition or with obesity‐related disorders.     

FDG PET/CT IMAGING IN CANINE CANCER PATIENTS

2‐Deoxy‐2‐[¹⁸F]fluoro‐d ‐glucose positron emission tomography/computed tomography (FDG PET/CT) is becoming increasingly available as an imaging modality in veterinary medicine. The purpose of this study was to report semiquantitative standard uptake values (SUV) of malignant and nonmalignant tissues and organs in canine cancer patients. FDG PET/CT was performed in 14 dogs including, nine mesenchymal tumors, four carcinomas, and one incompletely excised mast cell tumor. A generally higher FDG uptake was observed in carcinomas relative to sarcomas. Maximum SUV of carcinomas ranged from 7.6 to 27.0, and for sarcomas from 2.0 to 10.6. The FDG SUV of several organs and tissues, including regional brain uptake is reported, to serve as a reference for future FDG PET studies in canine cancer patients. Several potential pitfalls have been recognized in interpretation of FDG PET images of human patients, a number of these were also observed in this study.     

DETERMINATION OF FISH GENDER USING FRACTAL ANALYSIS OF ULTRASOUND IMAGES

The gender of cod Gadus morhua can be determined by considering the complexity in their gonadal ultrasonographic appearance. The fractal dimension ( D _B) can be used to describe this feature in images. B-mode gonadal ultrasound images in 32 cod, where gender was known, were collected. Fractal analysis was performed on these images and D _B was determined using the box counting method. A receiver–operating curve (ROC) was drawn for D _B as a test for male fish. Using a range of D _B values, the maximum accuracy for this test was calculated and compared with the accuracy for identifying male fish by subjective analysis alone. The mean (and standard deviation) of the fractal dimension D _B for male fish was 1.554 (0.073) while for female fish it was 1.468 (0.061); the difference was statistically significant ( P =0.001). The area under the ROC curve was 0.84 indicating the value of fractal analysis in gender determination in cod. Maximum accuracy (0.84) for D _B as a test for male fish was obtained using the threshold value D _B=1.5058 compared with an accuracy of 0.78 for subjective image evaluation. The use of two thresholds, D _B<1.4475 (females) and D _B>1.5054 (males) gives an 80% certainty in the classification result. Fractal analysis is useful for gender determination in cod. This or a similar form of analysis may have wide application in veterinary imaging as a tool for quantification of complexity in images.     

Sinography in the Investigation of Draining Tracts in Small Animals: Retrospective Review of 25 Cases

The signalment, history, clinical signs, radiographic findings, and surgical findings of 25 consecutive animals that had sinography were reviewed to assess the contribution made by sinography to diagnosing and surgically managing draining tracts in small animals. There were 23 dogs and 2 cats; a variety of breeds and both sexes were represented (18 males, 7 females). Before referral the mean duration of clinical signs was 9.8 months (range, 0.5 to 33 months) and a mean of 2.0 surgical procedures (range, 1 to 5) had been performed. Sinuses occurred in a variety of locations, most commonly the neck (10), head (6), and paws (5). The most common cause was foreign body (15). Survey radiographs showed abnormalities in 21 of 26 (78%) instances, including soft-tissue swelling (11), chronic-appearing periosteal reaction on adjacent bones (5), possible foreign body (4), and gas in soft tissues (2). Sinography (or fistulography) enabled definite diagnosis of the cause of the sinus (or fistula) in 15 of 26 (58%) instances and demonstrated 13 of 15 foreign bodies (sensitivity 87%; specificity 100%). Tracts caused by an esophageal perforation and otitis media were also correctly shown by fistulography. In 11 animals, sinography indicated that the position or extent of the lesion was different to that expected on the basis of clinical signs and survey radiographs.     

CHARACTERIZATION OF CANINE SUPERFICIAL TUMORS USING GRAY-SCALE B MODE, COLOR FLOW MAPPING, AND SPECTRAL DOPPLER ULTRASONOGRAPHY—A MULTIVARIATE STUDY

Superficial tumors are not routinely evaluated by two- or three-dimensional diagnostic imaging methods as part of the staging of canine cancer patients, although superficial tumors are readily imaged by ultrasound. The objectives of this study were to characterize the ultrasonographic patterns of superficial tumors and to evaluate whether ultrasound can help discriminate between benign and malignant tumors in dogs. Superficial tumors (n=132) in 86 dogs were evaluated by B mode, color flow mapping, and spectral Doppler ultrasonography. Size, echogenicity, tumor border definition, invasiveness, acoustic transmission, presence and distribution of vascular flow to and within the tumor, as well as perfusion indices were measured. The tumors were classified as lipomas, benign tumors, atypical mammary tumors, and malignant tumors. Multivariate statistics using discriminant analysis was used to determine which parameters may be used to predict the status of the tumor. Tumor echogenicity, border shape, acoustic shadowing, total number of vessels to the tumor and the total flow amount are the parameters that in combination resulted in the lowest classification error (24%), meaning that on average three out of four tumors were correctly classified using these parameters. All the lipomas and atypical mammary tumors were classified correctly by ultrasonography. The results of this study show that ultrasonography has an important role in the evaluation of canine superficial tumors, particularly in the evaluation of tissue homogeneity and tumor vascularity.     

QUANTITATIVE COMPUTED TOMOGRAPHY EVALUATION OF PULMONARY DISEASE

Objective assessment of pulmonary disease from computed tomography (CT) examinations is desirable but difficult. When such assessments can be made, it is important that they are related to some part of the pathophysiologic process present. Herein we propose that automated volume histogram analysis can yield data that allow differentiation of normal from abnormal lung, and that the magnitude of disease will have an association with objective CT indices. Data from pulmonary CT images from 34 foxes (six uninfected controls and 28 infected with Angiostrongylus vasorum , subdivided by age and infective dose) were available. Lung tissue was segmented from surrounding tissue using an automated segmentation method. A volume histogram showing voxel frequency for each CT number in the range −1024 to −250 HU was created from the entire image stack from each fox. Using these data, the inter-quartile range and the CT number at the 95th percentile were determined. The results showed that segmentation could be readily achieved but that areas of severely diseased lung were excluded. Based on two-way analysis of variance for both the inter-quartile range and the CT number at the 95th percentile, both quantities were significantly affected by the infection status of the animal and were related to worm burden ( P <0.001). The study shows that this form of analysis is readily achieved and provides quantitative data that can be used to assess disease severity, progression, and response to treatment.