Identifying the neck margin status of ductal adenocarcinoma in the pancreatic head by multiphoton microscopy

Towards next-generation diagnostic pathology: AI-empowered label-free multiphoton microscopy

Diagnostic pathology, historically dependent on visual scrutiny by experts, is essential for disease detection. Advances in digital pathology and developments in computer vision technology have led to the application of artificial intelligence (AI) in this field. Despite these advancements, the variability in pathologists' subjective interpretations of diagnostic criteria can lead to inconsistent outcomes. To meet the need for precision in cancer therapies, there is an increasing demand for accurate pathological diagnoses. Consequently, traditional diagnostic pathology is evolving towards "next-generation diagnostic pathology", prioritizing on the development of a multi-dimensional, intelligent diagnostic approach. Using nonlinear optical effects arising from the interaction of light with biological tissues, multiphoton microscopy (MPM) enables high-resolution label-free imaging of multiple intrinsic components across various human pathological tissues. AI-empowered MPM further improves the accuracy and efficiency of diagnosis, holding promise for providing auxiliary pathology diagnostic methods based on multiphoton diagnostic criteria. In this review, we systematically outline the applications of MPM in pathological diagnosis across various human diseases, and summarize common multiphoton diagnostic features. Moreover, we examine the significant role of AI in enhancing multiphoton pathological diagnosis, including aspects such as image preprocessing, refined differential diagnosis, and the prognostication of outcomes. We also discuss the challenges and perspectives faced by the integration of MPM and AI, encompassing equipment, datasets, analytical models, and integration into the existing clinical pathways. Finally, the review explores the synergy between AI and label-free MPM to forge novel diagnostic frameworks, aiming to accelerate the adoption and implementation of intelligent multiphoton pathology systems in clinical settings.

Label-free imaging diagnosis and collagen-optical evaluation of endometrioid adenocarcinoma with multiphoton microscopy

The assessment of tumor grade and pathological stage plays a pivotal role in determining the treatment strategy and predicting the prognosis of endometrial cancer. In this study, we employed multiphoton microscopy (MPM) to establish distinctive optical pathological signatures specific to endometrioid adenocarcinoma (EAC), while also assessing the diagnostic sensitivity, specificity, and accuracy of MPM for this particular malignancy. The MPM technique exhibits robust capability in discriminating between benign hyperplasia and various grades of cancer tissue, with statistically significant differences observed in nucleocytoplasmic ratio and second harmonic generation/two-photon excited fluorescence intensity. Moreover, by utilizing semi-automated image analysis, we identified notable disparities in six collagen signatures between benign and malignant endometrial stroma. Our study demonstrates that MPM can differentiate between benign endometrial hyperplasia and EAC without labels, while also quantitatively assessing changes in the tumor microenvironment by analyzing collagen signatures in the endometrial stromal tissue.

In vivo label-free optical signatures of chemotherapy response in human pancreatic ductal adenocarcinoma patient-derived xenografts

Pancreatic cancer is a devastating disease often detected at later stages, necessitating swift and effective chemotherapy treatment. However, chemoresistance is common and its mechanisms are poorly understood. Here, label-free multi-modal nonlinear optical microscopy was applied to study microstructural and functional features of pancreatic tumors in vivo to monitor inter- and intra-tumor heterogeneity and treatment response. Patient-derived xenografts with human pancreatic ductal adenocarcinoma were implanted into mice and characterized over five weeks of intraperitoneal chemotherapy (FIRINOX or Gem/NabP) with known responsiveness/resistance. Resistant and responsive tumors exhibited a similar initial metabolic response, but by week 5 the resistant tumor deviated significantly from the responsive tumor, indicating that a representative response may take up to five weeks to appear. This biphasic metabolic response in a chemoresistant tumor reveals the possibility of intra-tumor spatiotemporal heterogeneity of drug responsiveness. These results, though limited by small sample size, suggest the possibility for further work characterizing chemoresistance mechanisms using nonlinear optical microscopy.

Multiphoton microscopy in surgical oncology- a systematic review and guide for clinical translatability

BACKGROUND

Multiphoton microscopy (MPM) facilitates three-dimensional, high-resolution functional imaging of unlabeled tissues in vivo and ex vivo. This systematic review discusses the diagnostic value, advantages and challenges in the practical use of MPM in surgical oncology.

METHOD AND FINDINGS

A Medline search was conducted in April 2019. Fifty-three original research papers investigating MPM compared to standard histology in human patients with solid tumors were identified. A qualitative synopsis and meta-analysis of 14 blinded studies was performed. Risk of bias and applicability were evaluated. MPM can image fresh, frozen or fixed tissues up to a depth 1000 μm in the z-plane. Best results including functional imaging and virtual histochemistry are obtained by in vivo imaging or scanning fresh tissue immediately after excision. Two-photon excited fluorescence by natural fluorophores of the cytoplasm and second harmonic generation signals by fluorophores of the extracellular matrix can be scanned simultaneously, providing high resolution optical histochemistry comparable to standard histology. Functional parameters like fluorescence lifetime imaging or optical redox ratio provide additional objective information. A major concern is inability to visualize the nucleus. However, in a subpopulation analysis of 440 specimens, MPM yielded a sensitivity of 94%, specificity of 96% and accuracy of 95% for the detection of malignant tissue.

CONCLUSION

MPM is a promising emerging technique in surgical oncology. Ex vivo imaging has high sensitivity, specificity and accuracy for the detection of tumor cells. For broad clinical application in vivo, technical challenges need to be resolved.

Assessment of human pancreas cancer tissue and precursor lesions via a fluorophore with inherent PDAC selectivity

The current five-year survival rate of <5% for pancreatic ductal adenocarcinoma (PDAC) is compounded by late diagnosis, a lack of PDAC-specific intraoperative guidance to ensure complete resection, and the ineffectiveness of current therapies. Previously, utilizing compound 1, a fluorophore with inherent PDAC selectivity, PDAC was visualized both in vivo and ex vivo in a murine model. In the current study, human PDAC tissue is targeted. Compound 1 selectively stains ducts of the adenocarcinoma versus the surrounding stroma, enabling the imaging of PDAC in frozen tissue sections with high contrast. To enhance the potential of 1 for intraoperative applications, the ex vivo staining protocol was optimized for rapid margin assessment, with a final staining time of ~15 min. To measure diagnostic performance, the area under a receiver operating characteristic (ROC) curve was measured for the identification of ductal adenocarcinoma vs. stroma. The bright fluorescence contrast enabled quantitative determination of PDAC (or precancerous PanIN lesions) versus healthy pancreas tissue in human tissue array samples.

Characterization of Pancreatic Cancer Tissue Using Multiphoton Excitation Fluorescence and Polarization-Sensitive Harmonic Generation Microscopy

Thin tissue sections of normal and tumorous pancreatic tissues stained with hematoxylin and eosin were investigated using multiphoton excitation fluorescence (MPF), second harmonic generation (SHG), and third harmonic generation (THG) microscopies. The cytoplasm, connective tissue, collagen and extracellular structures are visualized with MPF due to the eosin stain, whereas collagen is imaged with endogenous SHG contrast that does not require staining. Cellular structures, including membranous interfaces and nuclear components, are seen with THG due to the aggregation of hematoxylin dye. Changes in the collagen ultrastructure in pancreatic cancer were investigated by a polarization-sensitive SHG microscopy technique, polarization-in, polarization-out (PIPO) SHG. This involves measuring the orientation of the linear polarization of the SHG signal as a function of the linear polarization orientation of the incident laser radiation. From the PIPO SHG data, the second-order non-linear optical susceptibility ratio, χ(2) zzz '/χ(2) zxx ', was obtained that serves as a structural parameter for characterizing the tissue. Furthermore, by assuming C6 symmetry, an additional second-order non-linear optical susceptibility ratio, χ(2) xyz '/χ(2) zxx ', was obtained, which is a measure of the chirality of the collagen fibers. Statistically-significant differences in the χ(2) zzz '/χ(2) zxx ' values were found between tumor and normal pancreatic tissues in periductal, lobular, and parenchymal regions, whereas statistically-significant differences in the full width at half maximum (FWHM) of χ(2) xyz '/χ(2) zxx ' occurrence histograms were found between tumor and normal pancreatic tissues in periductal and parenchymal regions. Additionally, the PIPO SHG data were used to determine the degree of linear polarization (DOLP) of the SHG signal, which indicates the relative linear depolarization of the signal. Statistically-significant differences in DOLP values were found between tumor and normal pancreatic tissues in periductal and parenchymal regions. Hence, the differences observed in the χ(2) zzz '/χ(2) zxx ' values, the FWHM of χ(2) xyz '/χ(2) zxx ' values and the DOLP values could potentially be used to aid pathologists in diagnosing pancreatic cancer.

Real-time Brain Tumor imaging with endogenous fluorophores: a diagnosis proof-of-concept study on fresh human samples

The primary line of therapy for high-grade brain tumor is surgical resection, however, identifying tumor margins in vivo remains a major challenge. Despite the progress in computer-assisted imaging techniques, biopsy analysis remains the standard diagnostic tool when it comes to delineating tumor margins. Our group aims to answer this challenge by exploiting optical imaging of endogenous fluorescence in order to provide a reliable and reproducible diagnosis close to neuropathology. In this study, we first establish the ability of two-photon microscopy (TPM) to discriminate normal brain tissue from glioblastomas and brain metastasis using the endogenous fluorescence response of fresh human brain sample. Two-photon fluorescence images were compared to gold standard neuropathology. "Blind" diagnosis realized by a neuropathologist on a group of TPM images show a good sensitivity, 100%, and specificity, 50% to discriminate non tumoral brain tissue versus glioblastoma or brain metastasis. Quantitative analysis on spectral and fluorescence lifetime measurements resulted in building a scoring system to discriminate brain tissue samples.

Development of predictive prognostic nomogram for NECs of rectum on population-based exploration

AIM

We aim to investigate the clinical characteristics of the rectal NECs and the prognosis-related factors and construct a nomogram for prognosis prediction.

METHODS

The data of 41 patients and 1028 patients with rectal NEC were retrieved respectively from our institution and SEER database. OS or PFS were defined as the major study outcome. Variables were compared by Chi2 test, t-test when appropriate. Kaplan-Meier analysis with log-rank test was used for survival analysis and the cox regression analysis were applied. The nomogram integrating risk factors for predicting OS was constructed by R to achieve superior discriminatory ability. Predictive utility of the nomogram was determined by concordance index (C-index) and calibration curve.

RESULTS

In the univariate and multivariate analysis, tumor differentiation, N stage, M stage and resection of primary site were identified as independent prognostic indicators. The linear regression relationship was found between the value of Ki-67 index and the duration of OS (P<0.05). Furthermore, the independent prognostic factors were added to formulate prognostic nomogram. The constructed nomogram showed good performance according to the C-index.

CONCLUSIONS

Contrary to WHO classification guideline, we found that the rectal NEC disease are heterogeneous and should be divided as different categories according to the pathological differentiation. Besides, the nomogram formulated in this study showed excellent discriminative capability to predict OS for those patients. More advanced predictive model for this disease is required to assist risk stratification via the formulated nomogram.

Label-free classification of hepatocellular-carcinoma grading using second harmonic generation microscopy

The clear and accurate understanding of the degree of hepatocellular-carcinoma (HCC) differentiation plays a key role in the determination of the patient prognosis and development of a treatment plan by the clinician. However, label-free and automated classification of the HCC grading is challenging. Here, we demonstrate second-harmonic generation (SHG) microscopy for label-free classification of HCC grading in paraffin-embedded specimens. A total of 217 images from 113 patients were obtained using SHG microscopy, and the SHG signals from the collagen within the tumor were analyzed using feature extraction and selection, the Mann-Whitney test, and the receiver operating characteristic curves. The results exhibit good correlation between the software analysis and the diagnosis by experienced pathologists. Combining the image features and clinical information, an adaptive quantification algorithm is generated for automatically determining the HCC grade. The results suggest that SHG microscopy might be a promising automated diagnostic method for clinical use, without requiring time for tissue processing and staining.