H&E Style Translation Using CycleGAN for Deep Ultraviolet-Excitation Fluorescence Images of Pancreatic Endoscopic Ultrasound-Fine Needle Aspiration/Biopsy Toward Slide-Free Rapid Pathology

Abstract

Endoscopic ultrasound-guided fine-needle aspiration/biopsy (EUS-FNA/B) is critical for determining treatment strategies for patients with pancreatic cancer. However, conventional pathological examination using hematoxylin and eosin (H&E) staining is time-consuming. Microscopy with ultraviolet surface excitation (MUSE) enables rapid pathological diagnosis without requiring slide preparation. This study explores the potential of combining MUSE imaging with a cycle-consistent generative adversarial network (CycleGAN), an image generation algorithm capable of learning translations without paired images, to enhance diagnostic workflows for pancreatic EUS-FNA/B. Thirty-five pancreatic specimens were stained with Terbium/Hoechst 33342, and deep ultraviolet (DUV) fluorescence images were captured by exciting the tissue surface. These fluorescence images, along with H&E-stained formalin-fixed, paraffin-embedded (FFPE) sections from the same specimens, were divided into 256 × 256-pixel segments for CycleGAN training. The algorithm was employed to translate pseudo-H&E images from MUSE test images. The pseudo-H&E images generated by the CycleGAN showed improved inter-pathologist agreement among three pathologists compared with the original MUSE images. We established a technique to perform MUSE imaging on small pancreatic samples obtained through EUS-FNA/B and confirmed that H&E-style translation using CycleGAN simplified interpretation for pathologists. Integrating MUSE imaging with CycleGAN has the potential to offer a rapid, cost-effective, and accurate diagnostic tool.

Keywords: cycle-consistent generative adversarial network (CycleGAN); endoscopic ultrasound-guided fine-needle aspiration/biopsy (EUS-FNA/B); microscopy with ultraviolet surface excitation (MUSE); pancreatic cancer; rapid pathological diagnosis.

Fig. 1.

A schematic view representing the protocol for fluorescence staining and MUSE imaging of pancreatic EUS-FNA/B samples. In total, 247 MUSE images at 5,472 × 3,648 pixels acquired from 35 cases were used in this study. For CycleGAN training datasets, 35 H&E WSIs were obtained from FFPE thin-sectioned specimens of the corresponding EUS-FNA/B samples following MUSE imaging. CycleGAN, cycle-consistent generative adversarial network; DUV, deep ultraviolet; EUS-FNA/B, endoscopic ultrasound-guided fine-needle aspiration/biopsy; FFPE, formalin fixed paraffin embedded; H&E, hematoxylin and eosin; MUSE, microscopy with ultraviolet surface excitation; Tb, terbium; WSI, whole slide image.

Fig. 2.

H&E style translation by the CycleGAN model. (A) Five-fold cross validation for H&E-style image translation using CycleGAN. For each patient, the MUSE images were randomly assigned to five folds; one fold was used as test data, and the remaining four folds served as training data. All MUSE images were utilized as test data and translated into pseudo-H&E images. (B) A bidirectional translation model was trained on 256 × 256-pixel patches extracted from MUSE images and FFPE H&E images. Bars = 10 μm. (C) The transfer model translated MUSE test images into H&E style using a sliding window process. CycleGAN, cycle-consistent generative adversarial network; FFPE, formalin fixed paraffin embedded; H&E, hematoxylin and eosin; MUSE, microscopy with ultraviolet surface excitation.

Fig. 3.

Representative MUSE and corresponding FFPE H&E images of pancreatic EUS-FNA/B. MUSE images (A, B) and corresponding H&E image (C) of normal pancreatic acinar cells. MUSE images (D, E) and corresponding H&E image (F) of pancreatic invasive ductal adenocarcinoma. Enlarged views of the regions outlined by red squares in the images (A, D) are shown to the right as the images (B, E), respectively. Bars = 200 μm (A, D) and 50 μm (B, C, E, F). EUS-FNA/B, endoscopic ultrasound-guided fine-needle aspiration/biopsy; FFPE, formalin fixed paraffin embedded; H&E, hematoxylin and eosin; MUSE, microscopy with ultraviolet surface excitation.

Fig. 4.

Representative MUSE images (A, B) and pseudo-H&E images (C, D) of normal pancreatic duct epithelia obtained by EUS-FNA/B. Enlarged views of the regions outlined by red squares in the images (A, C) are shown to the right as the images (B, D), respectively. Bars = 200 μm (A, C) and 50 μm (B, D). EUS-FNA/B, endoscopic ultrasound-guided fine-needle aspiration/biopsy; H&E, hematoxylin and eosin; MUSE, microscopy with ultraviolet surface excitation.

Fig. 5.

Representative MUSE images (A, B) and pseudo-H&E images (C, D) of pancreatic invasive ductal adenocarcinoma obtained by EUS-FNA/B. Enlarged views of the regions outlined by red squares in the images (A, C) are shown to the right as the images (B, D), respectively. Bars = 200 μm (A, C) and 50 μm (B, D). EUS-FNA/B, endoscopic ultrasound-guided fine-needle aspiration/biopsy; H&E, hematoxylin and eosin; MUSE, microscopy with ultraviolet surface excitation.