DOI: 10.5061/dryad.pk0p2ngwn
title: Data from: Open-top Bessel beam two-photon light sheet microscopy for three-dimensional pathology

description: Nondestructive pathology based on three-dimensional (3D) optical
 microscopy holds promise as a complement to traditional destructive
 hematoxylin and eosin (H&E) stained slide-based pathology by
 providing cellular information in high throughput manner. However,
 conventional techniques provided superficial information only due to
 shallow imaging depths. Herein, we developed open-top two-photon light
 sheet microscopy (OT-TP-LSM) for intraoperative 3D pathology. An extended
 depth of field two-photon excitation light sheet was generated by scanning
 a nondiffractive Bessel beam, and selective planar imaging was conducted
 with cameras at 400 frames/s max during the lateral translation of tissue
 specimens. Intrinsic second harmonic generation was collected for
 additional extracellular matrix (ECM) visualization. OT-TP-LSM was tested
 in various human cancer specimens including skin, pancreas, and prostate.
 High imaging depths were achieved owing to long excitation wavelengths and
 long wavelength fluorophores. 3D visualization of both cells and ECM
 enhanced the ability of cancer detection. Furthermore, an unsupervised
 deep learning network was employed for the style transfer of OT-TP-LSM
 images to virtual H&E images. The virtual H&E images
 exhibited comparable histological characteristics to real ones. OT-TP-LSM
 may have the potential for histopathological examination in surgical and
 biopsy applications by rapidly providing 3D information.
description: # Open-top Bessel beam two-photon light sheet microscopy for
 three-dimensional pathology
 [https://doi.org/10.5061/dryad.pk0p2ngwn](https://doi.org/10.5061/dryad.pk0p2ngwn) This dataset contains images and code that support the study entitled "Open-top Bessel beam two-photon light sheet microscopy for three-dimensional pathology" published in eLife ([https://doi.org/10.7554/eLife.92614.2)](https://doi.org/10.7554/eLife.92614.2\)) ## Description of the data and file structure This dataset contains OT-TP-LSM and H&E image datasets from skin (cancer), pancreas (normal, premalignant, cancer), prostate (benign, cancer). In addition, the pancreatic OT-TP-LSM and H&E images used to train cycle-consistent generational adversarial networks (CycleGAN) for virtual H&E are included. **Image dataset of two basal cell carcinoma (BCC) skin cancer used in Figure 2 are represented in this database:** SkinCancer_.zip and SkinCancer_H_E.zip **Image dataset of normal and intraductal papillary mucinous neoplasm (IPMN) pancreas used in Figure 3 are represented in this database:** Pancreas_nomral_.zip and Pancreas_nomral_H_E.zip Pancreas_IPMN_.zip and Pancreas_IPMN_H_E.zip **Image dataset of pancreatic cancer used in Figure 4 are represented in this database:** Pancreas_cancer_.zip and Pancreas_cancer_H_E.zip **Image dataset of benign and cancer prostate used in Figure 5 are represented in this database:** Prostate_benign_.zip and Prostate_benign_H_E.zip Prostate_cancer_.zip and Prostate_cancer_H_E.zip **Image dataset to train CycleGAN for virtual H&E used in Figure 6 are represented in this database:** CycleGAN_training_dataset.7z **The following abbreviations are used in the naming of images of the dataset:** SHG = second harmonic generation BCC = basal cell carcinoma H_E = hematoxylin & eosin PI: propidium iodide CycleGAN: cycle-consistent generative adversarial network **Description of sub-folders in database files** "Fluorescence" in SkinCancer_.zip = cell structure images after staining proflavine "Fluorescence" in Pancreas_nomral_.zip, Pancreas_IPMN_.zip, Pancreas_cancer_.zip, Prostate_benign_.zip and Prostate_cancer_.zip = cell structure images after PI staining "SHG" in all database = collagen fibers images within the extracellular matrix "Second strips" in Prostate_cancer_.zip = Strip images connected laterally to the original strip images "trainA_pancreas" in CycleGAN_training_dataset.7z = pancreas images after PI staining "trainB_pancreas" in CycleGAN_training_dataset.7z = H&E images of pancreas ## Sharing/Access information All data in this dataset was generated for, and underlies the conclusion of the following study: * [https://doi.org/10.7554/eLife.92614.2](https://doi.org/10.7554/eLife.92614.2) ## Code/Software Code for 3D reconstruction image processing (Matlab) and virtual hematoxylin and eosin (H&E) is available on Github ([https://github.com/Won-Yeong-Park/OT-TPLSM)](https://github.com/Won-Yeong-Park/OT-TPLSM\))