Objectives: To test a double histology reading system based on digitalized imaging for cancer diagnosis.
Material and methods: Pathology images of cancer diagnosis material were produced in real time by a digital imaging system integrated into the laboratory data processing system. Over a 30-day period, second readings were performed using the digitalized images. Cases with second readings were classified according to the aspect on the digitalized images as malignant tumor with histological type, malignant tumor with no other precision, and doubtful malignancy.
Results: During the study period, 204 cases of cancer were diagnosed, including 178 with digitalized imaging (87%). Among the digitalized cases, 119 (67%) were classified as malignant tumor with histological type, 53 (30%) as malignant tumor with no other precision, and 6 (3%) as doubtful malignancy. The histology material of these latter cases were reviewed and corresponded to malignant tumors. Approximately 2 hours per week were devoted to the second readings.
Conclusion: A integrated digitalized imaging system can participate in quality control of cancer diagnosis by allowing rapid efficacious second readings.