Multimodal multiphoton imaging for label-free monitoring of early gastric cancer

Background Early gastric cancer is associated with a much better prognosis than advanced disease, and strategies to improve prognosis is strictly dependent on earlier detection and accurate diagnosis. Therefore, a label-free, non-invasive imaging technique that allows the precise identification of morphologic changes in early gastric cancer would be of considerable clinical interest. Methods In this study, multiphoton microscopy (MPM) using two-photon excited fluorescence combined with second-harmonic generation was used for the identification of early gastric cancer. Results This microscope was able to directly reveal improved cellular detail and stromal changes during the development of early gastric cancer. Furthermore, two features were quantified from MPM images to assess the cell change in size and stromal collagen change as gastric lesion developed from normal to early cancer. Conclusions These results clearly show that multiphoton microscopy can be used to examine early gastric cancer at the cellular level without the need for exogenous contrast agents. This study would be helpful for early diagnosis and treatment of gastric cancer, and may provide the groundwork for further exploration into the application of multiphoton microscopy in clinical practice.Ope

A nomogram based on collagen signature for predicting the immunoscore in colorectal cancer

ObjectivesThe Immunoscore can categorize patients into high- and low-risk groups for prognostication in colorectal cancer (CRC). Collagen plays an important role in immunomodulatory functions in the tumor microenvironment (TME). However, the correlation between collagen and the Immunoscore in the TME is unclear. This study aimed to construct a collagen signature to illuminate the relationship between collagen structure and Immunoscore.MethodsA total of 327 consecutive patients with stage I-III stage CRC were included in a training cohort. The fully quantitative collagen features were extracted at the tumor center and invasive margin of the specimens using multiphoton imaging. LASSO regression was applied to construct the collagen signature. The association of the collagen signature with Immunoscore was assessed. A collagen nomogram was developed by incorporating the collagen signature and clinicopathological predictors after multivariable logistic regression. The performance of the collagen nomogram was evaluated via calibration, discrimination, and clinical usefulness and then tested in an independent validation cohort. The prognostic values of the collagen nomogram were assessed using Cox regression and the Kaplan−Meier method.ResultsThe collagen signature was constructed based on 16 collagen features, which included 6 collagen features from the tumor center and 10 collagen features from the invasive margin. Patients with a high collagen signature were more likely to show a low Immunoscore (Lo IS) in both cohorts (P<0.001). A collagen nomogram integrating the collagen signature and clinicopathological predictors was developed. The collagen nomogram yielded satisfactory discrimination and calibration, with an AUC of 0.925 (95% CI: 0.895-0.956) in the training cohort and 0.911 (95% CI: 0.872-0.949) in the validation cohort. Decision curve analysis confirmed that the collagen nomogram was clinically useful. Furthermore, the collagen nomogram-predicted subgroup was significantly associated with prognosis. Moreover, patients with a low-probability Lo IS, rather than a high-probability Lo IS, could benefit from chemotherapy in high-risk stage II and stage III CRC patients.ConclusionsThe collagen signature is significantly associated with the Immunoscore in the TME, and the collagen nomogram has the potential to individualize the prediction of the Immunoscore and identify CRC patients who could benefit from adjuvant chemotherapy

Improving liver fibrosis diagnosis based on forward and backward second harmonic generation signals

10.1063/1.4913907Applied Physics Letters106

Improving liver fibrosis diagnosis based on forward and backward second harmonic generation signals

The correlation of forward second harmonic generation (SHG) signal and backward SHG signal in different liver fibrosis stages was investigated. We found that three features, including the collagen percentage for forward SHG, the collagen percentage for backward SHG, and the average intensity ratio of two kinds of SHG signals, can quantitatively stage liver fibrosis in thioacetamide-induced rat model. We demonstrated that the combination of all three features by using a support vector machine classification algorithm can provide a more accurate prediction than each feature alone in fibrosis diagnosis

Label-free imaging of basement membranes differentiates normal, precancerous, and cancerous colonic tissues by second-harmonic generation microscopy.

Since changes in the basement membranes are the critical indicators for differentiating normal, precancerous, and cancerous colonic tissues, direct visualization of these warning signs is essential for the early diagnosis and treatment of colonic cancer. Here, we present that second harmonic generation (SHG) microscopy can probe the changes of basement membranes in different colonic cancer stages. Our results also show the capability of using the quantitative analyses of images for quantifying these changes in different cancer stages. These results suggest that SHG microscopy has the potential in label-freely imaging the changes of basement membranes for effectively distinguishing between normal, precancerous, and cancerous colonic tissues. To our knowledge, this is the first demonstration of the dynamics of basement membrane changes in different colonic cancer stages using entirely intrinsic source of contrast

Editorial: recent advances in fibrosis assessment for metabolic dysfunction-associated fatty liver disease - authors' reply

Editorial: Recent advances in fibrosis assessment for metabolic dysfunction-associated fatty liver disease - authors' reply. Lette