Development of Functional Requirements for Ex Vivo Pathology Applications of In Vivo Microscopy Systems: A Proposal From the In Vivo Microscopy Committee of the College of American Pathologists

Ultra-fast confocal fluorescence microscopy for neck lymph node imaging in head and neck cancer

OBJECTIVES

We evaluated ultra-fast confocal fluorescence microscopy (UFCM) as a new modality for pathology practice in head and neck cancer (HNC). This was assessed through an ex vivo study to estimate the accuracy, specificity, and sensitivity of interpretation of UFCM images by pathologists for the detection of metastatic lymph nodes in HNC patients undergoing sentinel lymph node biopsy or selective or complete neck dissection.

MATERIALS AND METHODS

44 patients with 32 cN0 and 12 cN+ HNC were included. The macroscopically non-invaded fresh bisected lymph nodes were stained with acridine orange and imaged with Histolog® Scanner (UFCM). Two pathologists interpreted independently the UFCM images postoperatively and gave a consensus diagnosis in case of disagreement. The gold standard was the diagnosis based on hematoxylin-eosin-saffron (HES) sections.

RESULTS

201 lymph nodes were imaged by UFCM. Thirty nodes (15 %) were invaded on final histology: 3 with micrometastases and 27 with macrometastases. The concordance rate between the pathologists on the UFCM images was 192/201 = 95.5 % and the Cohen kappa coefficient was 0.80. The accuracy of UFCM was 95.5 % (95 %CI: 91.7 %-97.9 %) with a high specificity at 98.8 % (95 %CI: 95.8 %-99.9 %) but an insufficient sensitivity at 76.7 % (95 %CI: 57.7 %-90.1 %). The three micrometastases and four of the 27 macrometastases were missed on UFCM images.

CONCLUSION

The UFCM is providing promising detection values with a very good specificity and moderate sensitivity carrying room for improvement.

Breast tissue imaging atlas using ultra-fast confocal microscopy to identify cancer lesions

New generation ultra-fast fluorescence confocal microscopy (UFCM) allows to image histological architecture of fresh breast tissue and may be used for ex vivo intraoperative analysis for margin status. The criteria to identify breast tumoral and non-tumoral tissues in UFCM images are still objects of investigation. The objective of the study was to create an atlas of ex vivo UFCM images of breast tissues and breast carcinomas based on the first extensive collection of large field-of-view UFCM breast images. One hundred sixty patients who underwent conserving surgery for breast cancer were included. Their fresh surgical specimens were sliced, stained with acridine orange, and imaged at high resolution with large-field-of-view UFCM. The resulting images were digitally false colored to resemble frozen sections. Each UFCM image was correlated with the corresponding definitive histology. Representative images of normal tissue, inflammation, benign lesions, invasive carcinoma (IC), and ductal carcinoma in situ (DCIS) were collected. A total of 320 large-field images were recorded from 58 IC of no special type, 44 invasive lobular carcinomas, 1 invasive mucinous carcinoma, 47 DCIS, 2 lobular carcinomas in situ, and 8 specimens without cancer. Representative images of the main components of the normal breast and the main types of ICs and DCIS were annotated to establish an UFCM atlas. UFCM enables the imaging of the fresh breast tissue sections. Main morphological criteria defined in traditional histopathology such as tissue architecture and cell features can be applied to describe UFCM images content. The generated atlas of the main normal or tumoral tissue features will support the adoption of this optical technology for the intraoperative examination of breast specimens in clinical practice as it can be used to train physicians on UFCM images and develop artificial intelligence algorithms. Further studies are needed to document rare breast lesions.

Deep learning-enabled realistic virtual histology with ultraviolet photoacoustic remote sensing microscopy

The goal of oncologic surgeries is complete tumor resection, yet positive margins are frequently found postoperatively using gold standard H&E-stained histology methods. Frozen section analysis is sometimes performed for rapid intraoperative margin evaluation, albeit with known inaccuracies. Here, we introduce a label-free histological imaging method based on an ultraviolet photoacoustic remote sensing and scattering microscope, combined with unsupervised deep learning using a cycle-consistent generative adversarial network for realistic virtual staining. Unstained tissues are scanned at rates of up to 7 mins/cm2, at resolution equivalent to 400x digital histopathology. Quantitative validation suggests strong concordance with conventional histology in benign and malignant prostate and breast tissues. In diagnostic utility studies we demonstrate a mean sensitivity and specificity of 0.96 and 0.91 in breast specimens, and respectively 0.87 and 0.94 in prostate specimens. We also find virtual stain quality is preferred (P = 0.03) compared to frozen section analysis in a blinded survey of pathologists.

Optical coherence tomography holds promise to transform the diagnostic anatomic pathology gross evaluation process

SIGNIFICANCE

Real-time histology can close a variety of gaps in tissue diagnostics. Currently, gross pathology analysis of excised tissue is dependent upon visual inspection and palpation to identify regions of interest for histopathological processing. Such analysis is limited by the variable correlation between macroscopic and microscopic findings. The current standard of care is costly, burdensome, and inefficient.

AIM

We are the first to address this gap by introducing optical coherence tomography (OCT) to be integrated in real-time during the pathology grossing process.

APPROACH

This is achieved by our high-resolution, ultrahigh-speed, large field-of-view OCT device designed for this clinical application.

RESULTS

We demonstrate the feasibility of imaging tissue sections from multiple human organs (breast, prostate, lung, and pancreas) in a clinical gross pathology setting without interrupting standard workflows.

CONCLUSIONS

OCT-based real-time histology evaluation holds promise for addressing a gap that has been present for >100 years.

The Critical Role of Breast Specimen Gross Evaluation for Optimal Personalized Cancer Care

Gross examination is the foundation for the pathologic evaluation of all surgical specimens. The rapid identification of cancers is essential for intraoperative assessment and preservation of biomolecules for molecular assays. Key components of the gross examination include the accurate identification of the lesions of interest, correlation with clinical and radiologic findings, assessment of lesion number and size, relationship to surgical margins, documenting the extent of disease spread to the skin and chest wall, and the identification of axillary lymph nodes. Although the importance of gross evaluation is undeniable, current challenges include the difficulty of teaching grossing well and its possible perceived undervaluation compared with microscopic and molecular studies. In the future, new rapid imaging techniques without the need for tissue processing may provide an ideal melding of gross and microscopic pathologic evaluation.

Ex vivo Fusion Confocal Microscopy of Colorectal Polyps: A Fast Turnaround Time of Pathological Diagnosis

BACKGROUND

Colorectal cancer screening programs have accomplished a mortality reduction from the disease but have created bottlenecks in endoscopy units and pathology departments. We aimed to explore the feasibility of ex vivo fusion confocal microscopy (FuCM) to improve the histopathology diagnostic efficiency and reduce laboratory workload.

METHODS

Consecutive fresh polyps removed at colonoscopy were scanned using ex vivo FuCM, then went through histopathologic workout and hematoxylin and eosin (H&E) diagnosis. Two pathologists blinded to H&E diagnosis made a diagnosis based on FuCM scanned images.

RESULTS

Thirty-six fresh polyps from 22 patients were diagnosed with FuCM and H&E. Diagnostic agreement between H&E and FuCM was 97.2% (kappa = 0.96) for pathologist #1 and 91.7% (kappa = 0.87) for pathologist #2. Diagnostic performance concordance between FuCM and H&E to discern adenomatous from nonadenomatous polyps was 100% (kappa = 1) for pathologist #1 and 97.2% (kappa = 0.94) for pathologist #2. Global interobserver agreement was 94.44% (kappa = 0.91) and kappa = 0.94 to distinguish adenomatous from nonadenomatous polyps.

CONCLUSIONS

Ex vivo FuCM shows an excellent correlation with standard H&E for the diagnosis of colorectal polyps. The clinical direct benefit for patients, pathologists, and endoscopists allows adapting personalized surveillance protocols after colonoscopy and a workload decrease in pathology departments.

Comparison of Real-Time Fluorescence Confocal Digital Microscopy With Hematoxylin-Eosin-Stained Sections of Core-Needle Biopsy Specimens

IMPORTANCE

Strategies to procure high-quality core-needle biopsy (CNB) specimens are critical for making basic tissue diagnoses and for ancillary testing.

OBJECTIVES

To investigate acquisition of fluorescence confocal microscopy (FCM) images of interventional radiology (IR)-guided CNB in real time in the radiology suite and to compare the accuracy of FCM diagnoses with those of hematoxylin-eosin (H&E)-stained CNB sections.

DESIGN, SETTING, AND PARTICIPANTS

In this diagnostic study, FCM imaging of IR-guided CNBs was performed in the radiology suite at a major cancer center for patients with an imaging abnormality from August 1, 2016, to April 30, 2019. The time taken to acquire FCM images and the quality of FCM images based on percentage of interpretable tissue with optimal resolution was recorded. The FCM images were read by 2 pathologists and categorized as nondiagnostic, benign/atypical, or suspicious/malignant; these diagnoses were compared with those made using H&E-stained tissue sections. Cases with discrepant diagnosis were reassessed by the pathologists together for a consensus diagnosis. Data were analyzed from June 3 to July 19, 2019.

INTERVENTIONS

Each IR-guided CNB was stained with 0.6mM acridine orange, subjected to FCM imaging, and then processed to generate H&E-stained sections.

MAIN OUTCOMES AND MEASURES

Mean time taken for acquisition of FCM images, quality of FCM images based on interpretable percentage of the image, and accuracy of diagnostic categorization based on FCM images compared with H&E-stained sections.

RESULTS

A total of 105 patients (57 male [54.3%]; mean [SD] age, 63 [13] years) underwent IR-guided CNBs in a mean (SD) of 7 (2) minutes each. The FCM images showed at least 20% of the tissue with optimal quality in 101 CNB specimens (96.2%). The FCM images were accurately interpreted by the 2 pathologists in 100 of 105 cases (95.2%) (2 false-positive and 3 false-negative) and 90 of 105 cases (85.7%) (6 false-positive and 9 false-negative). A reassessment of 14 discordant diagnoses resulted in consensus diagnoses that were accurate in 101 of 105 cases (96.2%) (1 false-positive and 3 false-negative).

CONCLUSIONS AND RELEVANCE

The ease of acquisition of FCM images of acceptable quality and the high accuracy of the diagnoses suggest that FCM may be useful for rapid evaluation of IR-guided CNBs. This approach warrants further investigation.