Consolidation Tumor Ratio Combined With Pathological Features Could Predict Status of Lymph Nodes of Early-Stage Lung Adenocarcinoma

IntroductionStage IA lung adenocarcinoma manifested as part-solid nodules (PSNs), has attracted immense attention owing to its unique characteristics and the definition of its invasiveness remains unclear. We sought to develop a nomogram for predicting the status of lymph nodes of this kind of nodules.MethodsA total of 2,504 patients between September 2018 to October 2020 with part-solid nodules in our center were reviewed. Their histopathological features were extracted from paraffin sections, whereas frozen sections were reviewed to confirm the consistency of frozen sections and paraffin sections. Univariate and multivariate logistic regression analyses and Akaike information criterion (AIC) variable selection were performed to assess the risk factors of lymph node metastasis and construct the nomogram. The nomogram was subjected to bootstrap internal validation and external validation. The concordance index (C-index) was applied to evaluate the predictive accuracy and discriminative ability.ResultsWe enrolled 215 and 161 eligible patients in the training cohort and validation cohort, respectively. The sensitivity between frozen and paraffin sections on the presence of micropapillary/solid subtype was 78.4%. Multivariable analysis demonstrated that MVI, the presence of micropapillary/solid subtype, and CTR >0.61 were independently associated with lymph node metastasis (p < 0.01). Five risk factors were integrated into the nomogram. The nomogram demonstrated good accuracy in estimating the risk of lymph node metastasis, with a C-index of 0.945 (95% CI: 0.916–0.974) in the training cohort and a C-index of 0.975 (95% CI: 0.954–0.995) in the validation cohort. The model’s calibration was excellent in both cohorts.ConclusionThe nomogram established showed excellent discrimination and calibration and could predict the status of lymph nodes for patients with ≤3 cm PSNs. Also, this prediction model has the prediction potential before the end of surgery.

Neuropathological interpretation of stimulated Raman histology images of brain and spine tumors: part B

Intraoperative histopathological examinations are routinely performed to provide neurosurgeons with information about the entity of tumor tissue. Here, we quantified the neuropathological interpretability of stimulated Raman histology (SRH) acquired using a Raman laser imaging system in a routine clinical setting without any specialized training or prior experience. Stimulated Raman scattering microscopy was performed on 117 samples of pathological tissue from 73 cases of brain and spine tumor surgeries. A board-certified neuropathologist — novice in the interpretation of SRH — assessed image quality by scoring subjective tumor infiltration and stated a diagnosis based on the SRH images. The diagnostic accuracy was determined by comparison to frozen hematoxylin–eosin (H&E)-stained sections and the ground truth defined as the definitive neuropathological diagnosis. The overall SRH imaging quality was rated high with the detection of tumor cells classified as inconclusive in only 4.2% of all images. The accuracy of neuropathological diagnosis based on SRH images was 87.7% and was non-inferior to the current standard of fast frozen H&E-stained sections (87.3 vs. 88.9%, p = 0.783). We found a substantial diagnostic correlation between SRH-based neuropathological diagnosis and H&E-stained frozen sections (κ = 0.8). The interpretability of intraoperative SRH imaging was demonstrated to be equivalent to the current standard method of H&E-stained frozen sections. Further research using this label-free innovative alternative vs. conventional staining is required to determine to which extent SRH-based intraoperative decision-making can be streamlined in order to facilitate the advancement of surgical neurooncology.

Ex vivo Fluorescence Confocal Microscopy: Chances and Changes in the Analysis of Breast Tissue

Background: Rapid histologic diagnosis of frozen sections is essential for a variety of surgical procedures. Frozen sections however, require specialized lab equipment, are prone to freezing artifacts and are not applicable to all types of tissue. Adipose tissue is especially difficult to process in frozen sections. Although these limitations are well known, no alternative method for microscopic tissue analysis that might replace frozen sections could be established. Our objective was to evaluate whether tissue imaging based on ex vivo fluorescent confocal microscopy (FCM) is applicable for rapid microscopic assessment of breast tumors specimens with abundant adipose tissue.Methods: We evaluated 17 tissue samples from mastectomy specimens, rich in adipose tissue, submitted to the department of pathology at the Medical University of Vienna. We conducted our study on the FCM VivaScope® 2500M-G4 (Mavig GmbH, Munich, Germany; Caliber I.D.; Rochester NY, USA).Results: When comparing FCM to frozen sections, we found a very similar overall processing time for FCM images and frozen sections respectively. Image quality was mostly superior to frozen sections (especially for adipose tissue and nuclear detail) but inferior to H&E stained FFPE sections. Limitations of the technology were uneven coloring, invisibility of ink applied for marking tissue margins and distortion artifacts if too much pressure is applied to the tissue. Conclusion: FCM has the potential to expand the application and usefulness of rapid tissue analysis as speed is comparable and quality exceeds that of frozen sections especially in tissues rich in adipose cells such as breast specimen.

Re-Evaluate the Value of Frozen Sections in Diagnoses of Breast Malignancies that Failed to be Diagnosed by Core Needle Biopsy: A Chinese Retrospective Analysis of Clinical Practice

Objective: The value of frozen sections in diagnoses of breast malignancies that failed to be diagnosed by core needle biopsy (CNB) is indeterminate. To re-evaluate and improve the utility of frozen section on this kind of breast malignancy, we conducted a retrospective data analysis and constructed a prediction model.Method: We reviewed data of breast cancer patients that failed to be diagnosed by CNB (CNB-undiagnosable) in Fudan University Shanghai Cancer Center (FUSCC) from May 1, 2006 to December 31, 2019. Clinical characteristics of patients were collected. the correlation between clinical features and false negative rate (FNR) of frozen sections was explored with logistic regression analysis, after which a nomogram was constructed to predict the probability of false negative.Result: The diagnostic sensitivity of frozen section on CNB-undiagnosable breast cancer was 67.18%, and the FNR was 32.82%. In multivariate analysis, papillary lesion (OR, 4.251; 95% CI, 2.804-6.492; P<0.0001) and sclerosing adenosis (OR, 3.727; 95% CI, 1.897-7.376; P= 0.0001) on CNB were risk factors of false negative, while clustered microcalcifications on mammography (OR, 0.345; 95% CI, 0.216-0.543; P < 0.0001) and ultrasonic BI-RADS category 4C-5 (OR, 0.250; 95% CI, 0.081-0.777; P = 0.0157) were favorable factors of true positive. The false negative rate of frozen section could be controlled at about 10% by the prediction of nomogram. Conclusion: Frozen sections are valuable in the diagnosis of CNB-undiagnosable breast cancers. It is recommended to implement the intraoperative frozen sections for high-risk breast lesions with a low probability of false negative indicated by prediction, so as to minimize the occurrence of unnecessary re-operation.