Optimized quality of histologic images allows the use of neural network scanning in diagnosis of fungal infection of abnormal nails
Analytical and Quantitative Cytology and Histology
M E BoonLambrecht P Kok
Abstract
The neural network scanning (NNS) system, formerly known as Papnet, is capable of selecting fungi in cervical smears. The objective of this study was to investigate whether the optimized quality of histologic images created using a combination of coagulant fixation and microwave histoprocessing allows the application of this computer-assisted microscopy in the diagnostic process. In a prospective study, 117 abnormal nails clinically suspect for fungal disease werefixed in a coagulant fixative, BoonFix, processed in a microwave histoprocessor to obtain optimal paraffin sections and stained with the periodic acid-Schiff (PAS) method. The stained paraffin sections were randomly numbered and screened by two independent pathologists for diagnosis of fungal hyphae and spores. The same sections were subsequently scanned by a neural network, and a maximum of 128 digital images produced by the system were screened and diagnosed by pathologists. Using light microscopy as the gold standard for diagnosis of fungi, the usefulness of NNS was then assessed. The fungi and spores were clearly demonstrated in the paraffin sections, and the NNS system detected and recorded them efficiently. The hyphae and spores could be identified in these pixil...Continue Reading