Radiological-pathological correlation of mass lesions in the liver

The Role of Pathological Examination of the Liver in Medicolegal Autopsy: A Tertiary Care Center Study From North India

BACKGROUND

The pathological examination of a medicolegal autopsy is a great learning opportunity for a pathologist as well as for a forensic expert, where the cause of death remains unknown. Liver disease epidemiology differs from one geographic area to another.

MATERIAL AND METHODS

This was a prospective observational study with 100 medicolegal autopsy cases over a one-year period conducted in the Department of Forensic Medicine and Toxicology (FMT) and Pathology. Representative tissue from the liver was collected in 10% neutral buffered formalin and sent for histopathological examination.

RESULTS

The mean age of the cases was 41.98 ± 15.39 years, and ages ranged from 20 to 90 years with male preponderance. The most common histopathology and gross findings noted were mild to moderate chronic hepatitis (CH) (54%) and fatty change (36%), respectively. There was a significant association (p ≤ 0.05) between histopathology and gross findings, cause, and manner of death.

CONCLUSION

Gross and histopathological examination of the liver in a medicolegal autopsy has a significant role in ascertaining the cause and manner of death.

Characteristics suggestive of focal Fatty sparing from liver malignancy on ultrasound in liver screening

OBJECTIVE

The objective of this study was to determine whether there are ultrasound characteristics that can be used to differentiate focal fatty sparing (FFS) from hepatocellular carcinoma and other liver malignancies in liver screening.

METHODS

Data of patients with FFS found at ultrasound were reviewed, 136 patients with FFS were included, and 112 patients with hepatocellular carcinoma and 65 patients with liver metastatic tumor (173 tumors) were selected as control group. Ultrasound and color Doppler characteristics of FFS and liver malignancies were studied. Some characteristics drawn from this study were used as reference to validate the liver malignancies and FFS, and sensitivity, specificity, and positive and negative predictive values were calculated.

RESULTS

Hyperechogenicity, isoechogenicity, heterogeneous echotexture, posterior acoustic shadowing, halo, hypervasculature presented exclusively in liver malignancies, posterior acoustic enhancement presented predominantly in liver malignancies, irregularly shaped morphology presented exclusively in FFS, arterial velocity, and maximal size of liver malignancies were significantly higher than those of FFS (P < 0.001). Halo presented in 109 of 285 liver malignancies (38.2%), but was absent in FFS (P < 0.001). The overall sensitivity, specificity, and positive and negative predictive values were 94.38%, 90.44%, and 95.39% and 88.49%, respectively.

CONCLUSIONS

Combination of hyperechogenicity, isoechogenicity, heterogeneous echotexture, posterior acoustic shadowing, posterior acoustic enhancement, halo appearance, and hypervascularity with high-speed artery has high sensitivity, specificity, and positive and negative predictive values for distinguishing liver malignancy and FFS.

Extraction of lesion-partitioned features and retrieval of contrast-enhanced liver images

The most critical step in grayscale medical image retrieval systems is feature extraction. Understanding the interrelatedness between the characteristics of lesion images and corresponding imaging features is crucial for image training, as well as for features extraction. A feature-extraction algorithm is developed based on different imaging properties of lesions and on the discrepancy in density between the lesions and their surrounding normal liver tissues in triple-phase contrast-enhanced computed tomographic (CT) scans. The algorithm includes mainly two processes: (1) distance transformation, which is used to divide the lesion into distinct regions and represents the spatial structure distribution and (2) representation using bag of visual words (BoW) based on regions. The evaluation of this system based on the proposed feature extraction algorithm shows excellent retrieval results for three types of liver lesions visible on triple-phase scans CT images. The results of the proposed feature extraction algorithm show that although single-phase scans achieve the average precision of 81.9%, 80.8%, and 70.2%, dual- and triple-phase scans achieve 86.3% and 88.0%.

Automated retrieval of CT images of liver lesions on the basis of image similarity: method and preliminary results

PURPOSE

To develop a system to facilitate the retrieval of radiologic images that contain similar-appearing lesions and to perform a preliminary evaluation of this system with a database of computed tomographic (CT) images of the liver and an external standard of image similarity.

MATERIALS AND METHODS

Institutional review board approval was obtained for retrospective analysis of deidentified patient images. Thereafter, 30 portal venous phase CT images of the liver exhibiting one of three types of liver lesions (13 cysts, seven hemangiomas, 10 metastases) were selected. A radiologist used a controlled lexicon and a tool developed for complete and standardized description of lesions to identify and annotate each lesion with semantic features. In addition, this software automatically computed image features on the basis of image texture and boundary sharpness. Semantic and computer-generated features were weighted and combined into a feature vector representing each image. An independent reference standard was created for pairwise image similarity. This was used in a leave-one-out cross-validation to train weights that optimized the rankings of images in the database in terms of similarity to query images. Performance was evaluated by using precision-recall curves and normalized discounted cumulative gain (NDCG), a common measure for the usefulness of information retrieval.

RESULTS

When used individually, groups of semantic, texture, and boundary features resulted in various levels of performance in retrieving relevant lesions. However, combining all features produced the best overall results. Mean precision was greater than 90% at all values of recall, and mean, best, and worst case retrieval accuracy was greater than 95%, 100%, and greater than 78%, respectively, with NDCG.

CONCLUSION

Preliminary assessment of this approach shows excellent retrieval results for three types of liver lesions visible on portal venous CT images, warranting continued development and validation in a larger and more comprehensive database.