Optimized quality of histologic images allows the use of neural network scanning in diagnosis of fungal infection of abnormal nails.
OBJECTIVE
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.


METHODS
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.


RESULTS
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 pixilated images with relative ease. Of the 117 examined cases, 50 were positive and 47 negative by both methods. In the 20 remaining cases, NNS did not present images of fungi that were present in the histologic sections. In practice, this implies that only 67 out of 117 cases (57%) must be screened by light microscopy. NNS recorded not only fungi and spores in the 128 digital images but also artifacts, such as round, deeply PAS-positive granules of talcum powder, which by light microscopy might be mistaken for fungal spores.


CONCLUSIONS
NNS proves applicable for the selection of spores and fungi if the histologic sections are of sufficiently high quality. As a result, the number of slides to be screened by light microscopy can be reduced substantially. In a throughput diagnostic laboratory handling a large number of such cases this technology can be highly valuable.
Boon
Mathilde E
ME
Leiden Cytology and Pathology Laboratory, Leiden, The Netherlands. M.E.Boon@lcpl.nl
Berger
Thomas H D
TH
Middag-Broekman
Anneke J H F F
AJ
Kok
Lambrecht P
LP
D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D016477:Artifacts; D002648:Child; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D016571:Neural Networks, Computer; D014009:Onychomycosis / Q000175:diagnosis*; D016612:Paraffin Embedding; D010503:Periodic Acid-Schiff Reaction; D011786:Quality Control; D013172:Spores, Fungal / Q000648:ultrastructure