Pulmonary cryptococcosis (PC), a serious fungal lung infection caused by Cryptococcus species, has become a growing public health concern (Howard-Jones et al., 2022). Although over 30 species exist, Cryptococcus neoformans and Cryptococcus gattii constitute the primary pathogenic species. Notably, Cryptococcus neoformans is ranked highest in the fungal priority pathogens list recently released by the World Health Organization (Zhao et al., 2023; World Health Organization, 2023). Cryptococcosis is primarily acquired via respiratory aspiration (Chen et al., 2022). Following pulmonary invasion, alveolar macrophages play a pivotal role in innate immunity by recognizing, phagocytosing, and eliminating cryptococci through diverse mechanisms (Wang Y. et al., 2022). Multinucleated giant cells, formed by the macrophage fusion at infection sites, phagocytose and sequester pathogens to limit their dissemination into surrounding tissues. These immune responses frequently induce granulomatous lesions that typically manifest as nodules on radiological imaging in PC. Despite the widespread clinical implementation of high-resolution computed tomography, distinguishing PC from pulmonary malignancies and tuberculosis remains challenging due to overlapping radiological features (Qu et al., 2020; Xin et al., 2022). Consequently, a definitive diagnosis typically requires histopathological confirmation through percutaneous lung biopsy, bronchial biopsy, or open thoracic surgery.

However, the diagnostic performance of histopathological methods for pulmonary fungal diseases still lacks sufficient clinical evidence. Pathologists are often uncertain when selecting diagnostic strategies due to the lack of consensus on optimal approaches. There are significant differences in the choice of diagnostic methods among pathology centers, with most hospital pathology departments using combined staining approaches [e.g., Grocott methenamine silver [GMS] combined with periodic acid-Schiff (PAS) and/or alcian blue (AB)]. Nevertheless, these methods exhibit marked performance variability in clinical practice. Both PAS and AB stain tissue components with colors similar to fungal elements, a feature that interferes with cryptococcal identification and reduces diagnostic accuracy. Critically, pulmonary granulomatous lesions have diverse etiologies, including non-infectious granulomatosis, tuberculosis, and other fungal pathogens (Rosen, 2022). False-negative staining results may prompt clinicians to consider alternative diagnoses, which could prolong the diagnostic process and delay antifungal therapy.

Our previous study showed that GMS staining is the most sensitive method for detecting pulmonary Cryptococcus (Wang S. et al., 2022). To further elucidate the superiority and diagnostic sufficiency of GMS staining for PC, we conducted a multicenter study involving 790 confirmed cases from six tertiary hospitals. In this study, digital pathology was employed for the first time to detect Cryptococcus quantitatively. We multidimensionally compared the sensitivity and accuracy of GMS, PAS, and AB staining methods in diagnosing PC, providing evidence-based scientific support for precise clinicopathologic diagnostic criteria.

Special staining remains the gold standard for identifying fungal diseases in histopathology because it highlights key morphological features essential for pathogen identification. However, clinical practice lacks consensus regarding the selection of fungal diagnostic methods, with pathology departments adopting different staining techniques based on their institutional experience. To address this lack of standardization, we conducted a multicenter validation study analyzing 790 PC cases from six tertiary hospitals.

The statistical results demonstrated 100% sensitivity for GMS staining across all centers, outperforming PAS (89.0–98.5%) and AB (68.3–87.5%) staining. Overall, GMS achieved perfect diagnostic sensitivity (790/790), while PAS detected 93.7% (740/790) of cases, and AB detected 75.4% (321/426). Statistical analysis confirmed that GMS had significantly higher sensitivity than both PAS (p < 0.001) and AB (p < 0.001). The diagnostic accuracy of the GMS single method was already excellent and did not differ from that of combined staining approaches. Moreover, digital tissue image analysis in 68 representative cases revealed that GMS-stained sections had significantly higher cryptococcal counts per section compared to PAS- and AB-stained sections, further supporting the superior sensitivity of GMS (median: 13,026 vs. 7,408 vs. 697, p < 0.001 for GMS vs. PAS and GMS vs. AB).

The GMS staining originated from Gomori’s (1946) histochemical method for detecting glycogen and mucin, which Grocott (1955) later optimized into a specialized fungal identification technique. Similarly, the PAS technique was introduced by McManus for visualizing mucin (McManus, 1946). Both techniques depend on oxidizing agents (chromic or periodic acid) to produce binding sites for silver ions or Schiff reagents via aldehyde formation. Chromic acid in GMS converts hydroxyl groups (-OH) to aldehyde groups (-CHO) and then to carboxyl groups (-COOH). Fungal cell walls, rich in polysaccharides, primarily stop at the aldehyde group stage. Non-fungal tissues, which contain fewer polysaccharides, oxidize fully to carboxyl groups. These carboxyl groups cannot bind silver ions, making GMS highly specific for fungi. In contrast, PAS can stain a wide range of tissue components including glycogen, mucins, and collagen fibers, because periodic acid only oxidizes vicinal diols to aldehydes. However, the overlapping chromatic profiles between fungi and other PAS-positive structures create diagnostic challenges, as colorimetric interference complicates morphological discrimination. Our data indicate that GMS exhibits higher sensitivity than PAS, which is primarily attributed to the superior oxidizing capacity of chromic acid. Although chromic acid and periodic acid differ in their reaction endpoints with ethylene glycol hydroxyl groups, the former’s strong oxidizing ability generates a greater number of aldehyde groups. This enhanced oxidation efficiency significantly boosts GMS sensitivity, making it more effective for detection.

AB staining (pH 2.5) uses a copper-phthalocyanine dye with polycationic side chains, which was first used by Steedman to visualize acidic mucins (Steedman, 1950). This dye binds to the polyanions of carbohydrates, forming blue insoluble complexes. AB stain reacts with multiple tissue components, including cryptococcal capsular polysaccharides, acidic mucins, and connective tissue proteoglycans. When used for fungal staining, it can produce interfering noise that complicates diagnosis. Our data showed that the sensitivity of AB staining for Cryptococcus detection was only 75.4%. This limited performance is primarily due to two key biological factors: Firstly, some strains of Cryptococcus naturally lack complete capsules. Secondly, during the processing of tissue specimens, organic solvents can damage the cryptococcal capsules, causing shrinkage or lysis (El-Zammar and Katzenstein, 2007).

Our observations revealed that Cryptococcus organisms exhibit two distinct spatial distributions. IC are completely phagocytosed by macrophages or multinucleated giant cells, while EC remain unphagocytosed, clustered, and surrounded by large, clear halos. Following GMS staining, both IC and EC exhibited strong staining. Fungal elements were distinctly stained in rich brown-black hues, sharply contrasting with the green counterstain. This optimized optical differentiation enhances the visual quality of tissue sections, enabling rapid screening of positive organisms even at low magnification.

Our data also showed that only 5.9% (4/68) of IC and 41.2% (28/68) of EC exhibited strong positivity with PAS staining, while only 2.9% (2/68) of IC and 51.5% (35/68) of EC exhibited strong positivity with AB staining. These strong positivity rates were statistically lower than those of GMS staining (100%, 68/68, p < 0.001 for all comparisons). The weaker staining intensities observed in PAS and AB staining are closely associated with the structural disruption of fungal cell walls and capsules. Cryptococcal infections begin with the inhalation of aerosolized spores or desiccated yeast cells. Upon reaching the lungs, fungal cells synthesize and thicken their polysaccharide capsules (Bojarczuk et al., 2016; Maxson et al., 2007). Alveolar macrophages, the primary force of defense in the lungs, recognize cryptococci through surface pattern recognition receptors and phagocytose them (Leopold Wager et al., 2016). Following internalization, reactive oxygen species and reactive nitrogen species produced within macrophages cause oxidative damage to cryptococci (Nelson et al., 2020; Leopold Wager and Wormley, 2015), while lysosomal enzymes further degrade the fungal cells (Mansour et al., 2014). These processes demonstrate the capacity of macrophages to disrupt both the cell walls and capsules of IC. Similar structural damage was observed in cryptococci within multinucleated giant cells, which may be due to damage caused by macrophages prior to fusion or to the direct antimicrobial activity of these giant cells themselves. However, the direct killing ability of multinucleated giant cells remains controversial (Ahmadzadeh et al., 2022), and their specific molecular mechanisms require further exploration in our subsequent studies. Although cryptococci are disrupted in the extracellular environment, intracellular conditions result in more effective killing and pronounced disruption of their polysaccharide structures. This leads to the loss of PAS and AB staining targets and a reduction in staining intensities. Consistently, our data showed significantly lower staining intensities for IC compared to EC in both PAS and AB staining (p < 0.001). In contrast, GMS maintains a sharp staining effect due to its high sensitivity.

Necrotic changes were identified in 14 (20.6%) of the 68 PC cases. GMS staining demonstrated strong positivity in both necrotic cores and adjacent peri-necrotic margins. In contrast, PAS and AB staining intensities were significantly higher in the peri-necrotic margins than in the necrotic cores (p < 0.05 for both comparisons), with elevated false-negative rates observed in the latter. In regions of tissue necrosis, Cryptococcus organisms underwent degradation and subsequent cell death, accompanied by progressive disintegration and eventual disappearance of their capsules and cell walls. This process led to a reduction in fungal polysaccharide content and structural fragmentation of the polysaccharide components. Consequently, these pathological changes manifested as significantly diminished staining intensities or even complete negativity in both PAS and AB. Given these findings, PAS and AB staining should be used with particular caution in necrotic cases, especially when biopsy tissue samples are limited. In contrast, the GMS staining method demonstrated high sensitivity and efficacy in detecting microscopic fungal cell wall remnants, showing notable stability and reliability. Despite this advantage, the cryptococcal density in necrotic cores was lower than that in peri-necrotic margins, likely due to the disappearance of cell walls following extensive organisms’ death in the necrotic cores. This finding suggests that pathologists should prioritize examining peri-necrotic margins when cryptococci are not identified in necrotic cores.

GMS staining is superior to PAS and AB for diagnosing pulmonary cryptococcosis, as it exhibits higher sensitivity and enhanced visualization of cryptococci, particularly in intracellular compartments, necrotic foci, and colonies with low structural polysaccharide content. GMS is recommended for accurate pathological diagnosis.