Surgical pathology in sub-Saharan Africa--volunteering in Malawi

The breadth of material found in surgical pathology services in African countries differs from the common spectrum of "the West". We report our experience of a voluntary work in the pathology departments of Blantyre and Lilongwe, Malawi. During a 6-week period, 405 cases (378 histology and 27 cytology cases) were processed. The vast majority showed significant pathological findings (n = 369; 91.1 %): 175 cases (47.4 %) were non-tumoral conditions with predominance of inflammatory lesions, e.g., schistosomiasis (n = 11) and tuberculosis (n = 11). There were 39 (10.6 %) benign tumors or tumor-like lesions. Intraepithelial neoplasia of the cervix uteri dominated among premalignant conditions (n = 15; 4.1 %). The large group of malignancies (n = 140; 37.9 %) comprised 11 pediatric tumors (e.g., rhabdomyosarcoma, small blue round cell tumors) and 129 adult tumors. Among women (n = 76), squamous cell carcinomas (SCCs) of the cervix uteri predominated (n = 25; 32.9 %), followed by breast carcinomas (n = 12; 15.8 %) and esophageal SCC (n = 9; 11.8 %). Males (n = 53) most often showed SCC of the esophagus (n = 9; 17.0 %) and of the urinary bladder (n = 7; 13.2 %). Lymphomas (n = 7) and Kaposi's sarcomas (n = 6) were less frequent. Differences compared to the western world include the character of the conditions in general, the spectrum of inflammatory lesions, and the young age of adult tumor patients (median 45 years; range 18-87 years). Providing pathology service in a low-resource country may be handicapped by lack of personnel, inadequate material resources, or insufficient infrastructure. Rotating volunteers offer a bridge for capacity building of both personnel and the local medical service; in addition, the volunteer's horizons are broadened professionally and personally.

Pathology hinting as the combination of automatic segmentation with a statistical shape model

With improvements in acquisition speed and quality, the amount of medical image data to be screened by clinicians is starting to become challenging in the daily clinical practice. To quickly visualize and find abnormalities in medical images, we propose a new method combining segmentation algorithms with statistical shape models. A statistical shape model built from a healthy population will have a close fit in healthy regions. The model will however not fit to morphological abnormalities often present in the areas of pathologies. Using the residual fitting error of the statistical shape model, pathologies can be visualized very quickly. This idea is applied to finding drusen in the retinal pigment epithelium (RPE) of optical coherence tomography (OCT) volumes. A segmentation technique able to accurately segment drusen in patients with age-related macular degeneration (AMD) is applied. The segmentation is then analyzed with a statistical shape model to visualize potentially pathological areas. An extensive evaluation is performed to validate the segmentation algorithm, as well as the quality and sensitivity of the hinting system. Most of the drusen with a height of 85.5 microm were detected, and all drusen at least 93.6 microm high were detected.