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OBJECTIVE: The aim of this study is to evaluate the clinicopathological features and prognostic significance of HER2 low, fibrotic focus (FF), and tumor-infiltrating lymphocytes (TILs) in patients with HER2-negative breast cancer. METHODS: We retrospectively reviewed the data of 293 patients with HER2-negative, stage I-II, invasive breast cancer of non-specific types. The HER2-negative cases were classified into HER2 low and HER2 0. Digital analysis of hematoxylin-eosin stained whole slide images was used to evaluate the FF expression. TILs were also evaluated using the Whole Slide Image. Furthermore, the association between HER2 low, FF, and TILs as well as their prognostic significance were analyzed. RESULTS: The study cohort included 178 cases (60.8%) with HER2 low and 115 cases (39.2%) with HER2 0. Older age, lower Nottingham histological grade (NHG), estrogen receptor (ER) positivity, progesterone receptor (PR) positivity, and hormone receptor (HR) positivity were all associated with HER2 low. FF was correlated with older age, intermediate and low NHG, vascular invasion, HR positivity, HER2 low status, high Ki67 expression, and low TILs. Univariate survival analysis showed that FF was significantly associated with shorter progression-free survival (PFS). Stratified analysis indicated that in the HR-negative and HR-positive groups, HER2 status and TILs did not affect PFS. DFS was longer in patients without FF compared to those with FF in the HR-positive (hazard ratio [HR] = 0.313) and HER2 low (HR = 0.272) groups. DFS was also significantly longer in patients without FF compared to those with FF in the HR-negative (HR = 0.069) and HER2 0 groups (HR = 0.129). CONCLUSION: The results indicated that the HER2 low status and the TILs expression did not impact prognosis. However, patients with FF exhibited distinct biological characteristics and prognostic significance, particularly in the HR-negative and HER2 0 groups. This provides a rationale for accurate diagnosis and treatment of HER2-negative breast cancer.
Subject(s)
Breast Neoplasms , Humans , Female , Prognosis , Retrospective Studies , Receptor, ErbB-2/metabolism , Lymphocytes, Tumor-Infiltrating , Disease-Free SurvivalABSTRACT
BACKGROUND AND AIMS: Evaluation of the programmed cell death ligand-1 (PD-L1) combined positive score (CPS) is vital to predict the efficacy of the immunotherapy in triple-negative breast cancer (TNBC), but pathologists show substantial variability in the consistency and accuracy of the interpretation. It is of great importance to establish an objective and effective method which is highly repeatable. METHODS: We proposed a model in a deep learning-based framework, which at the patch level incorporated cell analysis and tissue region analysis, followed by the whole-slide level fusion of patch results. Three rounds of ring studies (RSs) were conducted. Twenty-one pathologists of different levels from four institutions evaluated the PD-L1 CPS in TNBC specimens as continuous scores by visual assessment and our artificial intelligence (AI)-assisted method. RESULTS: In the visual assessment, the interpretation results of PD-L1 (Dako 22C3) CPS by different levels of pathologists have significant differences and showed weak consistency. Using AI-assisted interpretation, there were no significant differences between all pathologists (P = 0.43), and the intraclass correlation coefficient (ICC) value was increased from 0.618 [95% confidence interval (CI) = 0.524-0.719] to 0.931 (95% CI = 0.902-0.955). The accuracy of interpretation result is further improved to 0.919 (95% CI = 0.886-0.947). Acceptance of AI results by junior pathologists was the highest among all levels, and 80% of the AI results were accepted overall. CONCLUSION: With the help of the AI-assisted diagnostic method, different levels of pathologists achieved excellent consistency and repeatability in the interpretation of PD-L1 (Dako 22C3) CPS. Our AI-assisted diagnostic approach was proved to strengthen the consistency and repeatability in clinical practice.
Subject(s)
Artificial Intelligence , B7-H1 Antigen , Triple Negative Breast Neoplasms , Humans , Triple Negative Breast Neoplasms/diagnosis , Triple Negative Breast Neoplasms/pathology , B7-H1 Antigen/analysis , B7-H1 Antigen/metabolism , Female , Biomarkers, Tumor/analysis , Deep Learning , Immunohistochemistry/methods , Image Interpretation, Computer-Assisted/methodsABSTRACT
Exposure to fine particulate matter (PM2.5) during pregnancy has been inversely associated with neonatal neurological development. However, the associations of exposure to specific PM2.5 constituents with neonatal neurological development remain unclear. We investigated these associations and examined the mediating role of meconium metabolites in a Chinese birth cohort consisting of 294 mother-infant pairs. Our results revealed that exposure to PM2.5 and its specific constituents (i.e., organic matter, black carbon, sulfate, nitrate, and ammonium) in the second trimester, but not in the first or third trimester, was inversely associated with the total neonatal behavioral neurological assessment (NBNA) scores. The PM2.5 constituent mixture in the second trimester was also inversely associated with NBNA scores, and sulfate was identified as the largest contributor. Furthermore, meconium metabolome analysis identified four metabolites, namely, threonine, lysine, leucine, and saccharopine, that were associated with both PM2.5 constituents and NBNA scores. Threonine was identified as an important mediator, accounting for a considerable proportion (14.53-15.33%) of the observed inverse associations. Our findings suggest that maternal exposure to PM2.5 and specific constituents may adversely affect neonatal behavioral development, in which meconium metabolites may play a mediating role.
Subject(s)
Maternal Exposure , Meconium , Particulate Matter , Humans , Female , Meconium/chemistry , Pregnancy , Cohort Studies , Infant, Newborn , Adult , Air PollutantsABSTRACT
The new human epidermal growth factor receptor (HER)2-targeting antibody-drug conjugate offers the opportunity to treat patients with HER2-low breast cancer. Distinguishing HER2 immunohistochemical (IHC) scores of 0 and 1+ is not only critical but also challenging owing to HER2 heterogeneity and variability of observers. In this study, we aimed to increase the interpretation accuracy and consistency of HER2 IHC 0 and 1+ evaluation through assistance from an artificial intelligence (AI) algorithm. In addition, we examined the value of our AI algorithm in evaluating HER2 IHC scores in tumors with heterogeneity. AI-assisted interpretation consisted of AI algorithms and an augmenting reality module with a microscope. Fifteen pathologists (5 junior, 5 midlevel, and 5 senior) participated in this multi-institutional 2-round ring study that included 246 infiltrating duct carcinoma cases that were not otherwise specified. In round 1, pathologists analyzed 246 HER2 IHC slides by microscope without AI assistance. After a 2-week washout period, the pathologists read the same slides with AI algorithm assistance and rendered the definitive results by adjusting to the AI algorithm. The accuracy of interpretation accuracy with AI assistance (0.93 vs 0.80), thereby the evaluation precision of HER2 0 and the recall of HER2 1+. In addition, the AI algorithm improved the total consistency (intraclass correlation coefficient = 0.542-0.812), especially in HER2 1+ cases. In cases with heterogeneity, accuracy improved significantly (0.68 to 0.89) and to a similar level as in cases without heterogeneity (accuracy, 0.97). Both accuracy and consistency improved more for junior pathologists than those for the midlevel and senior pathologists. To the best of our knowledge, this is the first study to show that the accuracy and consistency of HER2 IHC 0 and 1+ evaluation and the accuracy of HER2 IHC evaluation in breast cancers with heterogeneity can be significantly improved using AI-assisted interpretation.
Subject(s)
Breast Neoplasms , Carcinoma, Ductal , Humans , Female , Breast Neoplasms/pathology , Artificial Intelligence , Receptor, ErbB-2/genetics , Algorithms , OncogenesABSTRACT
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.
Subject(s)
Artificial Intelligence , Biomarkers, Tumor/analysis , Breast Neoplasms/diagnosis , Image Interpretation, Computer-Assisted/methods , Ki-67 Antigen/analysis , Microscopy/methods , Female , Humans , Image Interpretation, Computer-Assisted/instrumentation , Microscopy/instrumentation , Observer Variation , Pathology, Clinical/instrumentation , Pathology, Clinical/methods , Reproducibility of Results , Retrospective StudiesABSTRACT
OBJECTIVE: To study the pharmacokinetics and brain/plasma concentration ratio of nortriptyline at multiple doses in mice which were pre-treated with physiological saline, piperine and verapamil. METHODS: A total of 216 male Kun Ming mice [(25±3) g] were equally divided into 4 groups randomly. Each group was intragastrically administered physiological saline (B), piperine (170 µg/ kg), piperine (5 mg/kg) and verapamil (5 mg/kg) for 8 days. On the 8th day, 1 h after giving the above drugs, each mice was intraperitoneally injected nortriptyline (13 mg/kg). The mice were sacrificed by picking off eyeballs at the time intervals of 5, 15, 30 min, and 1, 2, 4, 6, 8 and 12 h, and the cerebra were collected and weighted. Nortriptyline in mouse plasma and brain was determined by HPLC-MS/MS. The pharmacokinetic properties of the plasma, brain and brain/plasma were calculated. RESULTS: The AUC0-12 h of brain/plasma concentration ratio in the 170 µg/kg piperine group was significantly lower than that in the other groups (P<0.05), while the AUC0-12 h of brain/plasma concentration ratios in the 5 mg/kg piperine group and the verapamil group were not significantly different from those of untreated mice. CONCLUSION: Piperine (170 µg/kg) may induce P-glycoprotein expression in the blood-brain barrier, while piperines at 5 mg/kg has no influence on P-glycoprotein expression in the bloodbrain barrier.
Subject(s)
Alkaloids/chemistry , Benzodioxoles/chemistry , Blood-Brain Barrier , Brain/drug effects , Nortriptyline/pharmacokinetics , Piperidines/chemistry , Polyunsaturated Alkamides/chemistry , ATP Binding Cassette Transporter, Subfamily B , Animals , Chromatography, High Pressure Liquid , Male , Mice , Tandem Mass Spectrometry , VerapamilABSTRACT
We endeavor on a rarely explored task named thermal infrared video denoising. Perception in the thermal infrared significantly enhances the capabilities of machine vision. Nonetheless, noise in imaging systems is one of the factors that hampers the large-scale application of equipment. Existing thermal infrared denoising methods, primarily focusing on the image level, inadequately utilize time-domain information and insufficiently conduct investigation of system-level mixed noise, presenting the inferior ability in the video-recorded era; while video denoising methods, commonly applied to RGB cameras, exhibit uncertain effectiveness owing to substantial dissimilarities in the noise models and modalities between RGB and thermal infrared images. In sight of this, we initially revisit the imaging mechanism, while concurrently introducing a physics-inspired noise generator based on the sources and characteristics of system noise. Subsequently, a thermal infrared video denoising dataset consisting of 518 real-world videos is constructed. Lastly, we propose a denoising model called multi-domain infrared video denoising network, capable of concentrating features from the time, space, and frequency domains to restore high-fidelity videos. Extensive experiments demonstrate that the proposed method achieves state-of-the-art denoising quality and can be successfully applied to commercial cameras and downstream vision tasks, providing a new avenue for clear videography in the thermal infrared world. The dataset and code will be available.
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BACKGROUND: To investigate clinical characteristics, treatment, outcomes, and prognostic risk factors of metachronous bilateral breast carcinoma (MBBC) and provide a theoretical basis for clinical management of MBBC. METHODS: This was a retrospective study. From January 1, 2010 to March 31, 2022, a total of 23,010 patients with breast cancer underwent surgical treatment at the Breast Center of the Fourth Hospital of Hebei Medical University, including 386 patients with MBBC. Propensity score matching (PSM) was performed on MBBC patients and unilateral breast cancer (UBC) patients in a 1:1 ratio, and 210 UBC patients and 210 MBBC patients were finally matched. Clinical medical records of all patients were collected, including age of onset, family history of breast cancer, tumor size, lymph node status, TNM stage, mode of surgery, menstruation, pathological type, immunohistochemical (IHC) typing, treatment, disease-free survival (DFS), and overall survival (OS). RESULTS: The result showed that age of onset of the second primary cancer (SPC) was significantly older than that of the first primary cancer (FPC) (P = 0.024). Baseline data from MPPC patients showed that the tumor size of FPC was significantly larger than that of SPC (P = 0.043), and the proportion of PR ( +) in FPC is significantly higher than that in SPC (P = 0.045). Among MBBC patients with FPC for estrogen receptor (ER) or progesterone receptor (PR) ( +) and Her-2 (-), clinical characteristics and treatment results showed that the proportion of PR ( +) in the drug-resistant group was significantly lower than that in the non-drug-resistant group. The 2-year OS rate of SPC in the drug-resistant group was significantly shorter than those of the non-drug-resistant group (78.9% vs 100%, P < 0.05). The result of PSM-based comparison between MBBC patients and UBC patients showed significantly lower proportion of MBBC patients with SPC received chemotherapy compared to UBC patients (P = 0.026), and there was no significant difference in OS and DFS between SPC course of MBBC patients and UBC patients (P > 0.05). The univariate analysis showed that high TNM stage was a risk factor for death and disease progression in MBBC patients, with the risk of death in stage III MBBC patients being about 5 times higher than that in stage I MBBC patients (HR = 4.97, 95%CI = 1.42-17.31, P = 0.012), and the risk of disease recurrence being about 3.5 times higher than that in stage I MBBC patients (HR = 3.55, 95%CI = 1.07-11.81, P = 0.039). CONCLUSION: In summary, this study presented clinical characteristics, treatment options, and outcomes of MBBC patients and patients with MBBC who were resistant to endocrine therapy have a worse SPC survival prognosis. The course of SPC in MBBC patients was similar to that of UBC in terms of prognosis and survival, which suggested that SPC can be treated according to UBC treatment regimen. High TNM stage was a prognostic risk factor for SPC patients.
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Certain sub-groups, including men and obese individuals, are more susceptible to ozone (O3) exposure, but the underlying molecular mechanisms remain unclear. In this study, the male mice were divided into two dietary groups: one fed a high-fat diet (HFD), mimicking obesity conditions, and the other fed a normal diet (ND), then exposed to 0.5 ppm and 2 ppm O3 for 4 h per day over two days. The HFD mice exhibited significantly higher body weight and serum lipid biochemical indicators compared to the ND mice. Obese mice also exhibited more severe pulmonary inflammation and oxidative stress. Using a multi-omics approach including proteomics, metabolomics, and lipidomics, we observed that O3 exposure induced significant pulmonary molecular changes in both obese and normal mice, primarily arachidonic acid metabolism and lipid metabolism. Different molecular biomarker responses to acute O3 exposure were also observed between two dietary groups, with immune-related proteins impacted in obese mice and PPAR pathway-related proteins affected in normal mice. Furthermore, although not statistically significant, O3 exposure tended to aggravate HFD-induced disturbances in lung glycerophospholipid metabolism. Overall, this study provides valuable molecular insights into the responses of lung to O3 exposure and highlights the potential impact of O3 on obesity-induced metabolic changes.
Subject(s)
Multiomics , Ozone , Humans , Mice , Male , Animals , Mice, Obese , Lung , Obesity/metabolism , Ozone/pharmacologyABSTRACT
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.
Subject(s)
Esophageal Neoplasms , Esophageal Squamous Cell Carcinoma , Lung Neoplasms , Humans , Immunohistochemistry , B7-H1 Antigen , Pathologists , Biomarkers, Tumor/metabolism , Lung Neoplasms/pathologyABSTRACT
The demand for cone-beam computed tomography (CBCT) imaging in clinics, particularly in dentistry, is rapidly increasing. Preoperative surgical planning is crucial to achieving desired treatment outcomes for imaging-guided surgical navigation. However, the lack of surface texture hinders effective communication between clinicians and patients, and the accuracy of superimposing a textured surface onto CBCT volume is limited by dissimilarity and registration based on facial features. To address these issues, this study presents a CBCT imaging system integrated with a monocular camera for reconstructing the texture surface by mapping it onto a 3D surface model created from CBCT images. The proposed method utilizes a geometric calibration tool for accurate mapping of the camera-visible surface with the mosaic texture. Additionally, a novel approach using 3D-2D feature mapping and surface parameterization technology is proposed for texture surface reconstruction. Experimental results, obtained from both real and simulation data, validate the effectiveness of the proposed approach with an error reduction to 0.32 mm and automated generation of integrated images. These findings demonstrate the robustness and high accuracy of our approach, improving the performance of texture mapping in CBCT imaging.
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Background: The emergence of HER2 antibody-drug conjugates provides new treatment decisions for breast cancer patients, especially those with HER2-low expression. In order to explore the biological characteristics of breast cancer with HER2-low expression, the HER2-low category in primary breast cancer and residual tumor after neoadjuvant therapy was investigated to reflect the evolution of HER2 expression. Methods: HER2 was assessed according to the latest ASCO/CAP guidelines. The cut-off value for staining of HER2-positive cells was >10%. HER2-negative cases were divided into HER2-low (IHC=1+/2+ and no ISH amplification) and HER2-zero (IHC-0), and the clinicopathological characteristics of the cases were collected. Results: This study included 1140 patients with invasive breast cancer who received preoperative neoadjuvant therapy from 2018 to 2021, of which 365 patients achieved pCR and 775 were non-pCR. In the non-pCR cohort, HER2-low cases accounted for 59.61% of primary tumors and 55.36% of residual tumors. Among HER2-negative cases, HR-positive tumors had a higher incidence of low HER2 expression compared with triple-negative tumors (80.27% vs 60.00% in primary tumors and 72.68% vs 50.77% in residual tumors). The inconsistency rate of HER2 expression was 21.42%, mainly manifested as the conversion of HER2-low cases to HER2-zero (10.19%) and the conversion of HER2-zero to HER2-low (6.45%). Among the HER2-negative cases in the primary tumor, the HER2 discordance rate of HR-positive cases was lower than that of triple-negative cases (23.34% VS 36.92%). This difference was mainly caused by the case switching from HER2-low to HER2-zero. Compared with HER2-zero cases, there were statistically significant differences in RCB grade, MP grade and the number of metastatic lymph nodes in HER2-low cases. Patients with low HER2 expression had a lower pathological response rate and a higher number of metastatic lymph nodes. Conclusion: HER2-low breast cancer is highly unstable during disease evolution and has certain biological characteristics. HER2-low breast cancer is not only correlated with positive HR, but also has a certain correlation with positive AR. Re-detection of HER2 in breast cancer after neoadjuvant therapy may lead to new treatment opportunities for a certain proportion of patients.
ABSTRACT
The most commonly applied techniques to assess human epidermal growth factor receptor 2 (HER2) expression in breast cancer are immunohistochemistry (IHC) and fluorescence in situ hybridization (FISH). HER2 detection by reverse transcription quantitative polymerase chain reaction (RT-qPCR) can provide standardized, objective and automated assessment and reflect the HER2 expression continuity. Currently, there is lack of sufficient evidence to validate whether RTqPCR technique is more appropriate for the detection of HER2 low expression, especially ultra-low expression. Here, we primarily utilized RT-qPCR to differentiate HER2 true negative, ultra-low and 1 +, and compare the clinicopathological features and prognosis between RT-qPCR and IHC. 136 breast cancer cases with HER2 0 or 1 + were collected, also included 21 cases with HER2 2 + FISH negative as well as 25 cases with HER2 positive during the same period for comparative analysis. Compared the mRNA levels based on IHC/FISH scores. The receiver operating characteristic (ROC) curve was utilized to determine the threshold for reclassification, and the clinicopathological characteristics and prognosis differences among IHC true negative, ultra-low and 1 + after re-classification by RT-qPCR were analyzed. The mRNA level significantly differed between the IHC 0 and 1 + groups (p < 0.001). The IHC 0 group was further divided into true negative and ultra-low, there was no statistically significant difference in mRNA levels between true negative and ultra-low groups, while the difference between ultra-low and 1 + mRNA levels was statistically significant (p < 0.001). After reclassification of IHC true negative, ultra-low and 1 + by RT-qPCR, there were statistically significant differences in histological grade, ER, PR and TILs expression. There was no significant difference between DFS and OS in the two classification methods. RT-qPCR classification aids in distinguishing clinicopathological characteristics and can serve as a supplementary technique for detecting HER2-low by IHC.
Subject(s)
Biomarkers, Tumor , Breast Neoplasms , Humans , Female , Immunohistochemistry , Biomarkers, Tumor/analysis , In Situ Hybridization, Fluorescence , Receptor, ErbB-2/genetics , Receptor, ErbB-2/metabolism , Breast Neoplasms/diagnosis , Breast Neoplasms/genetics , Breast Neoplasms/metabolism , RNA, Messenger/geneticsABSTRACT
BACKGROUND: PD-L1 staining using long-stored paraffin sections may not be consistent with the true PD-L1 expression of patients. Therefore, it is necessary to explore the expression of PD-L1(SP142) in paraffin sections of invasive breast cancer with different storage times and the optimal storage temperature for unstained paraffin sections. METHODS: The study included 71 cases of PD-L1(SP142) positive breast cancer. The unstained paraffin sections were stored at room temperature conditions (20-25 °C), 4 °C, -20 °C and - 80 °C, respectively. PD-L1 staining was performed at 1, 2, 3, 4, 8, 12 and 24 weeks of storage. PD-L1 expression was assessed with a continuity score. RESULTS: The PD-L1 antigen was gradually lost as the storage time of paraffin sections increased. The PD-L1 positivity rate was 97.18% at 1 week for the sections stored at room temperature, and decreased from 83.10 to 71.83% for the sections stored for 2 weeks to 4 weeks, and 61.97%, 54.93%, and 32.93% for 8, 12, and 24 weeks, respectively. When stored at low temperatures of 4 °C, -20 °C and - 80 °C, the positivity rate decreases with the same trend but more slowly compared to room temperature. The mean IC score of PD-L1 also showed a gradual decrease in all cases. In the consistency analysis, PD-L1 expression in slices stored at room temperature for 2 weeks was consistent with PD-L1 expression in fresh slices (ICC ≥ 0.9 for all slices), and PD-L1 expression in slices stored at 4 °C or -20 °C for 4 weeks was consistent with PD-L1 expression in fresh slices (ICC ≥ 0.9 for all slices). When stored under refrigeration at -80 °C, PD-L1 expression in slices stored for 3 weeks was consistent with that in fresh slices (ICC ≥ 0.9). CONCLUSIONS: To our knowledge, this is the first article on the effect of preservation time and preservation temperature of paraffin sections on PD-L1 expression in breast cancer. Long-term storage of paraffin sections of unstained invasive breast cancer can lead to antigen loss of PD-L1 (SP142). Refrigerated storage of paraffin sections can delay antigen loss, with best results at 4 °C or -20 °C, and a storage time of no more than 4 weeks is recommended.
Subject(s)
Breast Neoplasms , Humans , Female , Paraffin , B7-H1 Antigen/metabolism , Immunohistochemistry , Time Factors , Biomarkers, Tumor/analysisABSTRACT
Background: Currently, assessment of sentinel lymph node (SLN) requires cytology, hematoxylin-eosin (HE), and immunohistochemistry (IHC). However, routine pathological slides still suffer from certain sampling errors and have time limitations. This study sought to investigate the sensitivity and specificity of SLN detection by reverse transcription-polymerase chain reaction (RT-PCR), which quantifies the expression of mammaglobin and cytokeratin-19 genes to determine SLN status. Methods: The RT-PCR detection of cycles threshold (CT) values has a direct relationship with the lymph node metastasis. This study prospectively collected 256 sentinel lymph nodes from 150 patients diagnosed with breast cancer between August and November 2017. In the detection of metastases in lymph nodes, molecular markers can be verified at the cell-level and tissue-level of tumor cells. In this study, IHC results were used as the gold standard for judging sentinel lymph node status. Results: (I) According to the established cell models, as the lymph nodes in tumor cells increase, RT-PCR CT values decrease. (II) 83 lymph nodes were first collected, and the interpretation criteria for the molecular detection results were determined based on the IHC results. (III) The statistical analysis showed that the sensitivity of the RT-PCR was 80.49% and the specificity was 91.55%. The positive predictive and negative predictive values were 64.71% and 96.06%, respectively. There was no significant difference between RT-PCR detection and IHC detection (P=0.076). Statistical chi-square analysis also showed that the difference between intraoperative freezing and immunohistochemistry was statistically significant (P=0.000). There was a statistically significant difference between intraoperative freezing and RT-PCR detection (P=0.000). RT-PCR detection is more sensitive than intraoperative frozen detection, and is closer to the results of immunohistochemistry. Conclusions: RT-PCR had objective and rapid output advantages, and was proven to be true and reliable. RT-PCR detection can not only rapidly assess sentinel lymph node status in breast cancer patients during surgery, but its accuracy is also close to that of IHC. Correctly determine whether to perform axillary lymph node dissection and improve the survival rate of patients.
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Puncture robot can improve the accuracy and efficiency of puncture surgery, such as thoracoabdominal and liver puncture. However, as soft tissue is deformed and shifted under respiratory motion and during the puncture process, the needle is pulled, resulting in the needle's bending and deformation, which increases the risks and sufferings of the patient, a robotic puncture system with optical and mechanical feedback is necessary. Therefore, this paper proposes a multi-information sensing 'guide-clamp' end effector for puncture surgery to accurately detect the posture and force on the puncture needle in real time. And gravity bias method with trajectory planning and the compensational controlling model are also proposed to offset the interference of self-weight and achieve zero force following. This system is evaluated by the experiments of robot controlling and human tissue simulation and the results prove the excellent robustness of the system, which meet the clinical requirement.
Subject(s)
Robotic Surgical Procedures , Feedback , Humans , Motion , Needles , Punctures , Robotic Surgical Procedures/methodsABSTRACT
A solid-phase extraction-liquid chromatographic-tandem mass spectrometry method for the determination of nalbuphine concentrations in human plasma has been developed. Samples (1 mL) were extracted using a Strata™-X solid phase extraction cartridges. Chromatographic separation of nalbuphine and naloxone (internal standard) was achieved on a Phenomenex Kinetex PFP (2.6 µm, 100 A, 100 × 2.1 mm) column using a mobile phase consisting of 0.1% formic acid, 15 mM ammonium acetate in deionized water and acetonitrile (60:40, v/v). The flow rate was 0.3 mL/min and the total run time was 2 min. Detection of the analytes was achieved using positive ion electrospray ionization via multiple reactions monitoring mode. The mass transitions were m/z 358 â 340 for nalbuphine and m/z 328 â 310 for naloxone. The assay was linear over the concentration range 0.50-500.00 ng/mL, with correlation coefficients ≥0.995. The lower limit of quantitation was set at 0.5 ng/mL plasma based on an average signal-to-noise ratio of 44.79. The intra- and inter-day precision was less than 8.07% in terms of relative standard deviation and accuracy ranged from 94.97 to 106.29% at all quality control levels. The method was applied successfully to determine nalbuphine concentrations in human plasma samples obtained from subjects receiving intravenous administration of nalbuphine. The method is rapid, sensitive, selective and directly applicable to human pharmacokinetic studies involving nalbuphine.
Subject(s)
Chromatography, Liquid/methods , Nalbuphine/blood , Solid Phase Extraction/methods , Tandem Mass Spectrometry/methods , Female , Humans , Least-Squares Analysis , Male , Nalbuphine/pharmacokinetics , Reproducibility of Results , Sensitivity and Specificity , Spectrometry, Mass, Electrospray IonizationABSTRACT
The most common sites of breast cancer metastasis are the lymph nodes, lungs, bones, and liver. Gastrointestinal (GI) metastasis is relatively rare and often occurs within several years after a breast cancer diagnosis. Most patients experience abdominal pain, anorexia, bleeding, vomiting, and other digestive system symptoms, symptoms which are difficult to distinguish from primary gastric cancer. There is no characteristic change seen under a digestive tract endoscopy, and the difference in morphology under the pathological microscope from that of primary poorly differentiated gastric adenocarcinoma is so small that it can easily cause a misdiagnosis. This paper reports the case of 46-year-old female patient whose first symptom was GI discomfort. She was hospitalized for GI surgery with an unknown medical history, but, during the preoperative examination, multiple breast masses were found on both sides, which were proved by pathology to be invasive lobular cancer. According to the medical literature, bilateral breast cancer with gastric metastasis is very rare, and, so far, this is the first reported case. Despite it being a rare phenomenon, it is necessary to be aware of the possibility of metastatic lobular carcinoma in the diagnosis of poorly differentiated gastric adenocarcinoma by biopsy.
ABSTRACT
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.
Subject(s)
Artificial Intelligence , Biomarkers, Tumor/analysis , Breast Neoplasms/chemistry , Carcinoma, Ductal, Breast/chemistry , Image Interpretation, Computer-Assisted , Immunohistochemistry , Microscopy/instrumentation , Receptor, ErbB-2/analysis , Automation, Laboratory , Biomarkers, Tumor/genetics , Breast Neoplasms/genetics , Breast Neoplasms/pathology , Carcinoma, Ductal, Breast/genetics , Carcinoma, Ductal, Breast/pathology , China , Female , Humans , In Situ Hybridization, Fluorescence , Observer Variation , Predictive Value of Tests , Receptor, ErbB-2/genetics , Reproducibility of Results , Retrospective StudiesABSTRACT
Programmed death ligand-1 (PD-L1) expression is a key biomarker to screen patients for PD-1/PD-L1-targeted immunotherapy. However, a subjective assessment guide on PD-L1 expression of tumor-infiltrating immune cells (IC) scoring is currently adopted in clinical practice with low concordance. Therefore, a repeatable and quantifiable PD-L1 IC scoring method of breast cancer is desirable. In this study, we propose a deep learning-based artificial intelligence-assisted (AI-assisted) model for PD-L1 IC scoring. Three rounds of ring studies (RSs) involving 31 pathologists from 10 hospitals were carried out, using the current guideline in the first two rounds (RS1, RS2) and our AI scoring model in the last round (RS3). A total of 109 PD-L1 (Ventana SP142) immunohistochemistry (IHC) stained images were assessed and the role of the AI-assisted model was evaluated. With the assistance of AI, the scoring concordance across pathologists was boosted to excellent in RS3 (0.950, 95% confidence interval (CI): 0.936-0.962) from moderate in RS1 (0.674, 95% CI: 0.614-0.735) and RS2 (0.736, 95% CI: 0.683-0.789). The 2- and 4-category scoring accuracy were improved by 4.2% (0.959, 95% CI: 0.953-0.964) and 13% (0.815, 95% CI: 0.803-0.827) (p < 0.001). The AI results were generally accepted by pathologists with 61% "fully accepted" and 91% "almost accepted". The proposed AI-assisted method can help pathologists at all levels to improve the PD-L1 assay (SP-142) IC assessment in breast cancer in terms of both accuracy and concordance. The AI tool provides a scheme to standardize the PD-L1 IC scoring in clinical practice.