The Effect of a Full Bladder on Proportions of Diagnostic Ultrasound Studies in Children with Suspected Appendicitis.

OBJECTIVES: We examined the effect of a full bladder on proportions of diagnostic ultrasound (US) studies in children with suspected appendicitis. We also examined the effect of a full bladder on proportions of fully visualized ovaries on US in children with suspected appendicitis. METHODS: We conducted a retrospective health record review of children aged 2-17 years presenting to a tertiary pediatric emergency department (ED) with suspected appendicitis who had an ultrasound performed. We compared proportions of diagnostic US studies in children with full and sub-optimally filled bladders. We also compared proportions of ovarian visualization in females with full and sub-optimally filled bladders. RESULTS: 678 children were included in our final analysis. The proportion of diagnostic US studies did not vary significantly between groups with a full (132/283, 47%, 95% confidence interval [CI] 38%-56%) or sub-optimally filled bladder (205/395, 52%, 95% CI 47%-57%)(p=0.17). Rates of ovarian visualization were higher in females with a full bladder (196/205, 96%, 95% CI 93%-99%) compared to those with a sub-optimally filled bladder (180/223, 81%, 95% CI 76%-86%) (p<0.01). CONCLUSIONS: Administrators and clinical decision makers should consider removing routine bladder filling practice from current pediatric appendicitis protocols in males and in pre-pubertal females where ovarian pathology is not suspected. Selective bladder filling prior to US should be performed in females when ovarian pathology is suspected.

Outcomes of children with suspected appendicitis and incompletely visualized appendix on ultrasound.

OBJECTIVES: The objective was to review the clinical outcomes of children with suspected appendicitis after an ultrasound (US) examination fails to fully visualize the appendix, the diagnostic characteristics of US in children with suspected appendicitis, and the predictive value of secondary signs of appendicitis when the appendix is not fully visualized. METHODS: This was a retrospective health record review of children aged 3 to 17 years presenting to a tertiary pediatric emergency department (ED) with suspected appendicitis. Descriptive statistics and diagnostic test characteristics are reported. RESULTS: Overall, 968 children had US. The appendix was fully visualized in 442 cases (45.7%), and 526 (54.3%) children had incompletely visualized appendices. The disposition of those with incompletely visualized appendices were as follows: 59.1% were discharged home, 10.5% went directly to the operating room, and 30.4% were admitted to the hospital for further observation. Of those discharged home based on clinical findings after incompletely visualized appendices, fewer than 0.3% ended up having appendicitis. Ultimately 15.6% of children with incompletely visualized appendices had pathology-confirmed appendicitis. The sensitivity and specificity of US for children with fully visualized appendices were 99.5% (95% confidence interval [CI] = 96.7% to 100%) and 81.3% (95% CI = 75.2% to 86.2%), respectively. The sensitivity and specificity for the presence of any secondary sign in diagnosing appendicitis were 40.2% (95% CI = 29.6% to 51.7%) and 90.6% (95% CI = 87.5% to 93.2%), respectively. CONCLUSIONS: Children with incompletely visualized appendices on US can be safely discharged home based on clinical findings with an acceptable rate of missed appendicitis. Children with nonreassuring clinical examinations following incompletely visualized appendices on US may benefit from further imaging studies prior to appendectomy, to reduce the rate of negative appendectomy. While the presence of secondary signs of inflammation can be used to rule in appendicitis, statistical strength to rule out appendicitis in the absence of secondary signs is insufficient.

Pediatric metanephric adenoma: case report and review of the literature.

Metanephric adenomas are rare benign renal neoplasms, uncommonly seen in the pediatric population. They are typically detected incidentally on imaging studies performed for unrelated clinical presentations. Preoperatively, the imaging appearance of this tumor overlaps with the appearance of more common and more aggressive renal neoplasms such as Wilms' tumor or renal cell carcinoma. We present a case of a pathologically proven metanephric adenoma, monitored preoperatively for approximately 5 years, prior to definitive nephrectomy. As the majority of solid renal masses are resected soon after they are detected, to the best of our knowledge, this case is the first to demonstrate the natural in vivo progression of a pathologically proven metanephric adenoma.

Automatic segmentation of the ribs, the vertebral column, and the spinal canal in pediatric computed tomographic images.

We propose methods to perform automatic identification of the rib structure, the vertebral column, and the spinal canal in computed tomographic (CT) images of pediatric patients. The segmentation processes for the rib structure and the vertebral column are initiated using multilevel thresholding and the results are refined using morphological image processing techniques with features based on radiological and anatomical prior knowledge. The Hough transform for the detection of circles is applied to a cropped edge map that includes the thoracic vertebral structure. The centers of the detected circles are used to derive the information required for the opening-by-reconstruction algorithm used to segment the spinal canal. The methods were tested on 39 CT exams of 13 patients; the results of segmentation of the vertebral column and the spinal canal were assessed quantitatively and qualitatively by comparing with segmentation performed independently by a radiologist. Using 13 CT exams of six patients, including a total of 458 slices with the vertebra from different sections of the vertebral column, the average Hausdorff distance was determined to be 3.2 mm with a standard deviation (SD) of 2.4 mm; the average mean distance to the closest point (MDCP) was 0.7 mm with SD = 0.6 mm. Quantitative analysis was also performed for the segmented spinal canal with three CT exams of three patients, including 21 slices with the spinal canal from different sections of the vertebral column; the average Hausdorff distance was 1.6 mm with SD = 0.5 mm, and the average MDCP was 0.6 mm with SD = 0.1 mm.

Landmarking and segmentation of computed tomographic images of pediatric patients with neuroblastoma.

OBJECTIVES: Segmentation and landmarking of computed tomographic (CT) images of pediatric patients are important and useful in computer-aided diagnosis, treatment planning, and objective analysis of normal as well as pathological regions. Identification and segmentation of organs and tissues in the presence of tumors is difficult. Automatic segmentation of the primary tumor mass in neuroblastoma could facilitate reproducible and objective analysis of the tumor's tissue composition, shape, and volume. However, due to the heterogeneous tissue composition of the neuroblastic tumor, ranging from low-attenuation necrosis to high-attenuation calcification, segmentation of the tumor mass is a challenging problem. In this context, we explore methods for identification and segmentation of several abdominal and thoracic landmarks to assist in the segmentation of neuroblastic tumors in pediatric CT images. MATERIALS AND METHODS: Methods are proposed to identify and segment automatically peripheral artifacts and tissues, the rib structure, the vertebral column, the spinal canal, the diaphragm, and the pelvic surface. The results of segmentation of the vertebral column, the spinal canal, the diaphragm and the pelvic girdle are quantitatively evaluated by comparing with the results of independent manual segmentation performed by a radiologist. RESULTS AND CONCLUSION: The use of the landmarks and removal of several tissues and organs assisted in limiting the scope of the tumor segmentation process to the abdomen, and resulted in the reduction of the false-positive error rates by 22.4%, on the average, over ten CT exams of four patients, and improved the result of segmentation of neuroblastic tumors.

Automatic delineation of the diaphragm in computed tomographic images.

Segmentation of the internal organs in medical images is a difficult task. By incorporating a priori information regarding specific organs of interest, results of segmentation may be improved. Landmarking (i.e., identifying stable structures to aid in gaining more knowledge concerning contiguous structures) is a promising segmentation method. Specifically, segmentation of the diaphragm may help in limiting the scope of segmentation methods to the abdominal cavity; the diaphragm may also serve as a stable landmark for identifying internal organs, such as the liver, the spleen, and the heart. A method to delineate the diaphragm is proposed in the present work. The method is based upon segmentation of the lungs, identification of the lower surface of the lungs as an initial representation of the diaphragm, and the application of least-squares modeling and deformable contour models to obtain the final segmentation of the diaphragm. The proposed procedure was applied to nine X-ray computed tomographic (CT) exams of four pediatric patients with neuroblastoma. The results were evaluated against the boundaries of the diaphragm as identified independently by a radiologist. Good agreement was observed between the results of segmentation and the reference contours drawn by the radiologist, with an average mean distance to the closest point of 5.85 mm over a total of 73 CT slices including the diaphragm.

Landmarking of computed tomographic images to assist in segmentation of abdominal tumors caused by neuroblastoma.

Segmentation of the primary tumor mass in neuroblastoma could aid radiologists by facilitating reproducible and objective quantification of the tumor's tissue composition and size. However, due to the heterogeneous nature of the tissue components of the neuroblastic tumor, ranging from low-attenuation necrosis to high-attenuation calcification, some of which possess strong similarities with adjacent nontumoral tissues in computed tomographic (CT) images, segmentation of the tumor is a difficult problem. In this context, landmarking methods are proposed to assist in the segmentation of neuroblastic tumors. Methods are proposed to identify and segment automatically the rib structure, the vertebral column, the spinal canal, the diaphragm, and the pelvic girdle. The use of the landmarks assisted in limiting the scope of the tumor segmentation process to the abdomen, and resulted in the reduction of the false-positive error rates by 26.9%, on the average, over 10 CT exams, and improved the result of segmentation of neuroblastic tumors.

Three-dimensional segmentation of the tumor in computed tomographic images of neuroblastoma.

Segmentation of the tumor in neuroblastoma is complicated by the fact that the mass is almost always heterogeneous in nature; furthermore, viable tumor, necrosis, and normal tissue are often intermixed. Tumor definition and diagnosis require the analysis of the spatial distribution and Hounsfield unit (HU) values of voxels in computed tomography (CT) images, coupled with a knowledge of normal anatomy. Segmentation and analysis of the tissue composition of the tumor can assist in quantitative assessment of the response to therapy and in the planning of the delayed surgery for resection of the tumor. We propose methods to achieve 3-dimensional segmentation of the neuroblastic tumor. In our scheme, some of the normal structures expected in abdominal CT images are delineated and removed from further consideration; the remaining parts of the image volume are then examined for tumor mass. Mathematical morphology, fuzzy connectivity, and other image processing tools are deployed for this purpose. Expert knowledge provided by a radiologist in the form of the expected structures and their shapes, HU values, and radiological characteristics are incorporated into the segmentation algorithm. In this preliminary study, the methods were tested with 10 CT exams of four cases from the Alberta Children's Hospital. False-negative error rates of less than 12% were obtained in eight of 10 exams; however, seven of the exams had false-positive error rates of more than 20% with respect to manual segmentation of the tumor by a radiologist.