Near-Infrared II Hyperspectral Imaging Improves the Accuracy of Pathological Sampling of Multiple Cancer Types.

Pathological histology is the "gold standard" for clinical diagnosis of cancer. Incomplete or excessive sampling of the formalin-fixed excised cancer specimen will result in inaccurate histologic assessment or excessive workload. Conventionally, pathologists perform specimen sampling relying on naked-eye observation, which is subjective and limited by human perception. Precise identification of cancer tissue, size, and margin is challenging, especially for lesions with inconspicuous tumors. To overcome the limits of human eye perception (visible: 400-700 nm) and improve the sampling efficiency, in this study, we propose using a second near-infrared window (NIR-II: 900-1700 nm) hyperspectral imaging (HSI) system to assist specimen sampling on the strength of the verified deep anatomical penetration and low scattering characteristics of the NIR-II optical window. We used selected NIR-II HSI narrow bands to synthesize color images for human eye observation and also applied a machine learning-based algorithm on the complete NIR-II HSI data for automatic tissue classification to assist pathologists in specimen sampling. A total of 92 tumor samples were collected, including 7 types. Sixty-two (62/92) samples were used as the validation set. Five experienced pathologists marked the contour of the cancer tissue on conventional color images by using different methods, and compared it with the "gold standard," showing that NIR-II HSI-assisted methods had significant improvements in determining cancer tissue compared with conventional methods (conventional color image with or without X-ray). The proposed system can be easily integrated into the current workflow, with high imaging efficiency and no ionizing radiation. It may also find applications in intraoperative detection of residual lesions and identification of different tissues.

Improving Ki67 assessment concordance by the use of an artificial intelligence-empowered microscope: a multi-institutional ring study.

AIMS: The nuclear proliferation biomarker Ki67 plays potential prognostic and predictive roles in breast cancer treatment. However, the lack of interpathologist consistency in Ki67 assessment limits the clinical use of Ki67. The aim of this article was to report a solution utilising an artificial intelligence (AI)-empowered microscope to improve Ki67 scoring concordance. METHODS AND RESULTS: We developed an AI-empowered microscope in which the conventional microscope was equipped with AI algorithms, and AI results were provided to pathologists in real time through augmented reality. We recruited 30 pathologists with various experience levels from five institutes to assess the Ki67 labelling index on 100 Ki67-stained slides from invasive breast cancer patients. In the first round, pathologists conducted visual assessment on a conventional microscope; in the second round, they were assisted with reference cards; and in the third round, they were assisted with an AI-empowered microscope. Experienced pathologists had better reproducibility and accuracy [intraclass correlation coefficient (ICC) = 0.864, mean error = 8.25%] than inexperienced pathologists (ICC = 0.807, mean error = 11.0%) in visual assessment. Moreover, with reference cards, inexperienced pathologists (ICC = 0.836, mean error = 10.7%) and experienced pathologists (ICC = 0.875, mean error = 7.56%) improved their reproducibility and accuracy. Finally, both experienced pathologists (ICC = 0.937, mean error = 4.36%) and inexperienced pathologists (ICC = 0.923, mean error = 4.71%) improved the reproducibility and accuracy significantly with the AI-empowered microscope. CONCLUSION: The AI-empowered microscope allows seamless integration of the AI solution into the clinical workflow, and helps pathologists to obtain higher consistency and accuracy for Ki67 assessment.

Concordance of assessments of four PD-L1 immunohistochemical assays in esophageal squamous cell carcinoma (ESCC).

OBJECTIVE: Given real-world limitations in programmed death-ligand 1 (PD-L1) testing, concordance studies between PD-L1 assays are needed. We undertook comparisons of PD-L1 assays (DAKO22C3, Ventana SP263, Ventana SP142, E1L3N) among observers in esophageal squamous cell carcinoma (ESCC) to provide information on the analytical and clinical comparability of four PD-L1 IHC assays. METHODS: Paraffin embedded samples of 50 cases of esophageal squamous cell carcinoma were obtained, satined with all four PD-L1 assays. PD-L1 was evaluated by 68 pathologists from 19 different hospitals. PD-L1 expression was assessed for combined positive score (CPS). RESULTS: The expression sensitivity of SP263 was the highest in ESCC, followed by 22C3, E1L3N and SP142. Taking CPS 10 as the critical value, inter-observer concordance for CPS scores among 68 physicians was assessed for the 22C3, SP263, SP142, and E1L3N assays, yielding values of 0.777, 0.790, 0.758, and 0.782, respectively. In the comparison between assays, the overall CPS scores concordance rates between 22C3 and SP263, SP142, and E1L3N were 0.896, 0.833, and 0.853, respectively. 22C3 and SP263 have high concordance, with OPA of 0.896, while E1L3N and SP142 have the highest concordance, with OPA of 0.908. CONCLUSION: In ESCC, the concordance of PD-L1 evaluation among observers is good, and the immune cell score is still an important factor affecting the concordance of interpretation among observers. Cases near the specific threshold are still the difficult problem of interpretation. SP263 had the highest CPS score of the four assays. SP263 cannot identify all 22C3 positive cases, but had good concordance with 22C3.E1L3N and SP142 showed high concordance.

Relationship between HER2 expression and tumor interstitial angiogenesis in primary gastric cancer and its effect on prognosis.

INTRODUCTION: Her2-positive gastric cancer is a unique subtype of disease, requiring different diagnosis and treatment strategies and methods. Neoplasms are significantly correlated with the occurrence, invasion and metastasis of tumors. The purpose of this study was to explore the correlation between HER2 amplification and tumor interstitial angiogenesis in patients with gastric cancer. METHODS: The data of 1121 patients with gastric cancer were retrospectively analyzed, and the amplification of HER2 was detected by immunohistochemistry (IHC) and FISH. CD34 IHC was used to label MVD. We analyzed the factors affecting HER2 amplification, the difference in MVD under different HER2 states, the factors related to 5-year survival rate of patients, and predicted the independent factors affecting 5-year survival rate of gastric cancer patients. RESULTS: We found 115 cases with HER2 positive rate of 10.26 %. HER2 amplification was more likely in gastric cancer patients with more than 5.2 cm tumor diameter, Lauren intestinal type, tubular adenocarcinoma, and the depth of infiltration at stage T2, (P < 0.05). Gender, age, tumor location, number of lymph node metastasis, distant metastasis, clinical stage, nerve invasion and vascular tumor thrombi were not the factors affecting HER2 amplification of gastric cancer (P > 0.05). MVD count of HER2-positive gastric cancer was significantly higher than that of HER2-negative gastric cancer, (P < 0.05). The 5-year overall survival rate of 1121 patients with gastric cancer was 51.92 %. HER2 amplification, high MVD count, large tumor size, tubular adenocarcinoma, Lauren intestinal type, deep tumor infiltration, numerous lymph node metastases and late clinical stage are all associated with low 5-year survival rate, indicating poor prognosis in gastric cancer patients, (P < 0.05). The 5-year survival rate of gastric cancer patients was not correlated with gender, age, tumor location, distant metastasis, nerve invasion and vascular cancer plug, (P > 0.05). Multivariate analysis showed that Lauren classification, Infiltrating depth, Nodal status, Clinical stage, HER2 expression, MVD count were independent factors affecting the prognosis of gastric cancer patients, (P < 0.05). CONCLUSION: HER2 overexpression was not only closely related to gastric cancer neovascularization, but also an independent predictor of prognosis of gastric cancer. In clinical treatment, anti-HER2 targeted therapy and anti-angiogenesis drugs can be adopted to achieve effective treatment.

The beneficial role of Asian-based RecurIndex test in the prognostic prediction in Chinese male breast cancer patients.

RecurIndex, a multigene profiling assay, can predict the risk of local recurrence and distant metastasis in female breast cancer (FBC), but its role in male breast cancer (MBC) remains unclear. In this study, the clinicopathological data of 43 consecutive MBC patients undergoing surgeries between 2009 and 2018 were retrospectively analysed. Their paraffin-embedded tissue sections were examined by RecurIndex test which comprised 2 models: recurrence index for local recurrence (RI-LR) and recurrence index for distant recurrence (RI-DR). Of 43 patients, there were 26 low-risk and 17 high-risk patients assessed by RI-LR, while 17 low-risk and 26 high-risk patients by RI-DR. For RI-LR, tumor N stage showed statistically significant (P < 0.001) between low- and high-risk patients; for RI-DR, differences were pronounced in tumor grade (P = 0.033), T stage (P = 0.043) and N stage (P = 0.003). In terms of clinical outcomes, the overall survival (OS) of low- and high-risk patients stratified by RI-LR showed no statistically significant differences (P = 0.460), while high-risk patients identified by RI-DR had a significantly worse distant recurrence-free survival (DRFS) (P = 0.035), progression-free survival (PFS) (P = 0.019) and OS (P = 0.044) than low-risk patients. Overall, RI-DR can effectively predict the DRFS, PFS and OS of MBC patients and identify those at low risk of recurrence, which may serve as a potential prognostic tool for MBC.

Can AI-assisted microscope facilitate breast HER2 interpretation? A multi-institutional ring study.

The level of human epidermal growth factor receptor-2 (HER2) protein and gene expression in breast cancer is an essential factor in judging the prognosis of breast cancer patients. Several investigations have shown high intraobserver and interobserver variability in the evaluation of HER2 staining by visual examination. In this study, we aim to propose an artificial intelligence (AI)-assisted microscope to improve the HER2 assessment accuracy and reliability. Our AI-assisted microscope was equipped with a conventional microscope with a cell-level classification-based HER2 scoring algorithm and an augmented reality module to enable pathologists to obtain AI results in real time. We organized a three-round ring study of 50 infiltrating duct carcinoma not otherwise specified (NOS) cases without neoadjuvant treatment, and recruited 33 pathologists from 6 hospitals. In the first ring study (RS1), the pathologists read 50 HER2 whole-slide images (WSIs) through an online system. After a 2-week washout period, they read the HER2 slides using a conventional microscope in RS2. After another 2-week washout period, the pathologists used our AI microscope for assisted interpretation in RS3. The consistency and accuracy of HER2 assessment by the AI-assisted microscope were significantly improved (p < 0.001) over those obtained using a conventional microscope and online WSI. Specifically, our AI-assisted microscope improved the precision of immunohistochemistry (IHC) 3 + and 2 + scoring while ensuring the recall of fluorescent in situ hybridization (FISH)-positive results in IHC 2 + . Also, the average acceptance rate of AI for all pathologists was 0.90, demonstrating that the pathologists agreed with most AI scoring results.