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[Histopathological Diagnosis of Invasive Fungal Infections in Formalin-Fixed and Paraffin-Embedded Tissues in Conjunction with Molecular Methods].

The main objective of this study was to evaluate the relationship between histopathology, polymerase chain reaction (PCR), and in situ hybridization (ISH) for the identification of causative fungi in formalin-fixed and paraffin-embedded (FFPE) tissue specimens. Since pathogenic fungi in tissue specimens can be difficult to identify morphologically, PCR and ISH have been usually employed as auxiliary procedures. However, little comparison has been made on the sensitivity and specificity of PCR and ISH using FFPE specimens. Therefore, to compare and clarify the reproducibility and usefulness of PCR and ISH as auxiliary procedures for histological identification, we performed histopathological review, PCR assays, and ISH to identify pathogenic fungi in 59 FFPE tissue specimens obtained from 49 autopsies. The following are the main findings for this retrospective review: i) even for cases classified as "mold not otherwise specified" (MNOS), two cases could be identified as Aspergillus species by molecular methods; ii) all cases classified as non-zygomycetes mold (NZM) were Aspergillus species and were not identified by molecular methods as other fungi; iii) all 3 cases classified as zygomycetes mold (ZM) could be identified by molecular methods as Mucorales; iv) except for 1 case identified by molecular methods as Trichosporon spp., 5 cases were originally identified as dimorphic yeast (DY). As a measure of nucleic acid integrity, PCR and ISH successfully detected human and fungal nucleic acids in approximately 60% of the specimens. Detection of Aspergillus DNA by nested PCR assay and by ISH against the A. fumigatus ALP gene were similarly sensitive and significant (p<0.01). Thus, our findings demonstrated the potential risk of error in the classification of fungi based on pathological diagnosis. Combining molecular methods such as ISH and PCR on FFPE specimens with pathological diagnosis should improve diagnostic accuracy of fungal infection.