Utility of a new notation to visualize flow cytometry analysis results: first preliminary comparison with immunohistochemistry to detect CD30 expression on T-cell lymphoma cells

Background It is important to confirm CD30 expression in T-cell lymphoma cases, but immunohistochemical staining for CD30 is not commonly performed and no comparison has been done between the results of flow cytometry (FCM) and immunohistochemical staining for CD30. Therefore, we devised a notation that we termed proportion of immunoreactivity/expression for FCM (PRIME-F notation), based on the cellular proportion showing different antigen-antibody reactivity. Methods We retrospectively compiled 211 cases of T-cell lymphoma, assessed via FCM, from major hospitals in Miyagi Prefecture from January 2012 to January 2019, and compared 52 of these cases with the immunohistochemical immunoreactive (IR) pattern of CD30 (PRIME-I notation). The PRIME-F notation was divided into five levels: notations starting with “-” followed by 3, 2, and 1 “>” correspond to level-I, level-II, or level-III; notations starting with “(dim)+” correspond to level-IV; and those starting with “+” or “(bright)+” correspond to level-V. Results The 52 cases of PRIME-F notation with “+” included 16 cases of peripheral T-cell lymphoma (PTCL/NOS), 3 of follicular T-cell lymphoma (FTL), 3 of angioimmunoblastic T-cell lymphoma (AITL), 6 of extranodal NK/T-cell lymphoma/nasal type (ENKL), 18 of adult T-cell lymphoma (ATL), and 6 cases of anaplastic large cell lymphoma (ALCL). Eight of the 52 cases were immunohistochemically CD30-negative. In the PRIME-F level-I to III group (excluding false-positive cases), 21.7% (5 out of 23 cases) were < 10% positive for CD30 upon immunohistochemistry (IHC). Contrarily, in the level-IV & -V group, no CD30 positivity rate of < 10% upon IHC was found (0%) (p = 0.0497). In level-IV, 42.9% of cases presented a CD30 negative rate > 1/3 upon IHC, while in level-V, only 7.1% (one out of 14 cases) did. The CD30 negative rate tended to be low (p = 0.0877) in level-V. Conclusions To our knowledge, this is the first report describing the correspondence between FCM and immunohistochemistry findings for CD30 through newly proposed notations. The PRIME-F and PRIME-I notations for CD30 showed a minor positive correlation. The PRIME notation is considered universally applicable to antibodies, and notations of both FCM and IHC show great potential for big data.

Comparing the performance of linear regression versus deep learning on detecting melanoma skin cancer using apple core ML

Melanoma is a type of deadly skin cancer. The survival rate of the patients can fall as low as 15.7% if the cancer cell has reached its final stage. Delayed treatment of melanoma can be attributed to its likeness to that of common nevus (moles). Two machine learning models were developed, each with a different approach and algorithm, to detect the presence of melanoma. Image classification is using the regression algorithm, and object detection is using deep learning. The two models are then compared, and the best model is determined according to the achieved metrics. The testing was conducted using 120 testing data and is made up of 60 positive data and 60 negative data. The testing result shows that object detection achieved 70% accuracy than image classification’s 68%. More importantly, linear regression’s 43% false-negative rate is noticeably high compared to convolutional neural network’s (CNN) 25%. A false-negative rate of 43% means almost half of sick patients tested using image classification will be diagnosed as healthy. This is dangerous as it can lead to delayed treatment and, ultimately, death. Thus it can be concluded that CNN is the best method in detecting the presence of melanoma.

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.

Clinical Study of Sentinel Lymph Node Detection Using Photodynamic Eye for Abdominal Radical Trachelectomy

This study aimed to assess the accuracy of predicting pelvic lymph node status using sentinel lymph node (SLN) biopsy with indocyanine green (ICG) and to examine the outcomes of SLN biopsy-guided abdominal radical trachelectomy (ART). Patients with stage IA2–IB2 cervical cancer from January 2009 to January 2021 were included. ICG was injected before ART and SLNs were identified, excised, and assessed intraoperatively using fast-frozen sections. Systemic pelvic lymphadenectomy was subsequently performed. The SLN detection rate, sensitivity, and false-negative rate were determined. Thirty patients desiring fertility preservation were enrolled, of whom 26 successfully completed ART and four underwent radical hysterectomies because of metastatic primary SLNs. Bilateral SLNs were identified in all patients. The sensitivity, false-negative rate, and negative predictive value were 100%, 7.7%, and 92.3%, respectively. Three (12%) patients were lost to follow-up: two relapsed and one died of tumor progression. Of the nine patients who tried to conceive after surgery, four achieved pregnancy and three delivered healthy live infants. In women with early-stage cervical cancer who desired to conserve fertility, SLN mapping with ICG had a very high detection rate, sensitivity, and low false-negative rate. SLN biopsy-guided ART is a feasible and accurate method for assessing pelvic node status.

Artificial intelligence classification model for macular degeneration images: a robust optimization framework for residual neural networks

Background The prevalence of chronic disease is growing in aging societies, and artificial-intelligence–assisted interpretation of macular degeneration images is a topic that merits research. This study proposes a residual neural network (ResNet) model constructed using uniform design. The ResNet model is an artificial intelligence model that classifies macular degeneration images and can assist medical professionals in related tests and classification tasks, enhance confidence in making diagnoses, and reassure patients. However, the various hyperparameters in a ResNet lead to the problem of hyperparameter optimization in the model. This study employed uniform design—a systematic, scientific experimental design—to optimize the hyperparameters of the ResNet and establish a ResNet with optimal robustness. Results An open dataset of macular degeneration images (https://data.mendeley.com/datasets/rscbjbr9sj/3) was divided into training, validation, and test datasets. According to accuracy, false negative rate, and signal-to-noise ratio, this study used uniform design to determine the optimal combination of ResNet hyperparameters. The ResNet model was tested and the results compared with results obtained in a previous study using the same dataset. The ResNet model achieved higher optimal accuracy (0.9907), higher mean accuracy (0.9848), and a lower mean false negative rate (0.015) than did the model previously reported. The optimal ResNet hyperparameter combination identified using the uniform design method exhibited excellent performance. Conclusion The high stability of the ResNet model established using uniform design is attributable to the study’s strict focus on achieving both high accuracy and low standard deviation. This study optimized the hyperparameters of the ResNet model by using uniform design because the design features uniform distribution of experimental points and facilitates effective determination of the representative parameter combination, reducing the time required for parameter design and fulfilling the requirements of a systematic parameter design process.

Accurately Locating Metastatic Foci in Lymph Nodes With Lugol’s Iodine-Enhanced Micro-CT Imaging

BackgroundAccurate evaluation of lymph node (LN) status is the key factor to determine the treatment and evaluate prognosis for patients with cancer. However, traditional pathological examination resulted in a 30% false-negative rate of detection of metastases in LNs. This study aimed to utilize Lugol’s iodine (I2-IK)-enhanced micro-CT imaging to reveal the 3-dimensional structure of regional LNs and decrease the false-negative rate in pathological examination.MethodsTo explore the feasibility of I2-IK-enhanced micro-CT imaging in locating metastatic lesion in LNs, nonmetastatic and metastatic LNs from mice were used to mimic the imaging process. Then, the LNs from oral squamous cell carcinoma (OSCC) patients were applied to verify the value of I2-IK-enhanced micro-CT imaging in revealing LN structure and locating metastatic lesions in LNs. The glycogen content in nonmetastatic and metastatic LNs was further detected by the use of a glycogen assay kit and periodic acid–Schiff (PAS) staining to explain the imaging differences between them.ResultsIn nude mice, 0.5% I2-IK staining for 4 h was the best parameter for normal LN. The metastatic foci in metastatic LNs were also clearly outlined in this condition. For nonmetastatic LNs from patients with OSCC, 1% I2-IK staining for 12 h was the best parameter. However, due to the increased volume of metastatic LNs, the image effect of 3% I2-IK staining for 12 h was superior to 1% I2-IK staining [tumor background ratio (TBR), 3% vs. 1%, 1.89 ± 0.10 vs. 1.27 ± 0.07, p &lt; 0.001]. Compared with subsequent pathological sections, we found the CT intensity of metastatic foci in LNs and muscle tissues was significantly higher than in nonmetastatic regions. Meanwhile, the glycogen content of metastatic foci in LNs detected was also significantly higher than in nonmetastatic region.ConclusionsI2-IK-enhanced micro-CT imaging could identify the spatial location of metastatic foci in LNs. This will be an effective method to assist in decreasing the LN false-negative rate for cancer pathology.

Novel Method for Identifying Care Home Residents in England: A Validation Study

IntroductionThe ability to identify residents of care homes in routinely collected health care data is key to informing healthcare planning decisions and delivery initiatives targeting the older and frail population. Health-care planning and delivery implications at national level concerning this population subgroup have considerably and suddenly grown in urgency following the onset of the COVID-19 pandemic, which has especially hit care homes. The range of applicability of this information has widened with the increased availability in England of retrospectively collected administrative databases, holding rich patient-level details on health and prognostic status who have made or are in contact with the National Health Service. In practice lack of a national registry of care homes residents in England complicates assessing an individual's care home residency status, which has been typically identified via manual address matching from pseudonymised patient-level healthcare databases linked with publicly availably care home address information. ObjectivesTo examine a novel methodology based on linking unique care home address identifiers with primary care patient registration data, enabling routine identification of care home residents in health-care data. MethodsThis study benchmarks the proposed strategy against the manual address matching standard approach through a diagnostic assessment of a stratified random sample of care home post codes in England. ResultsDerived estimates of diagnostic performance, albeit showing a non-insignificant false negative rate (21.98%), highlight a remarkable true negative rate (99.69%) and positive predictive value (99.35%) as well as a satisfactory negative predictive value (88.25%). ConclusionsThe validation exercise lends confidence to the reliability of the novel address matching method as a viable and general alternative to manual address matching.

1185 Acute Paediatric Appendicitis(AA)-Decreasing The Negative Rate Of Appendicectomy

Aim The COVID -19 pandemic has forced changes in the management of Acute Appendicitis (AA), such as prioritising conservative management and avoiding laparoscopic procedures. This observational study aims to monitor and reduce the negative rate of paediatric appendicectomy and optimise the acute paediatric management following the newly introduced workflow. Method Retrospective patient data collection via electronic sources for all paediatric patients(0-16 years old) admitted with AA between March 23rd and October 31st 2020. Results During this period 74 patients were admitted with suspected AA. Conservative treatment was performed in 16 (22%) patients and operative management in 58 (78%), of which 15 (26%) had an open appendicectomy, while 43 (74%) underwent laparoscopic appendicectomy. The first trimester the negative appendicectomy rate was 25%, which dropped to 11% because of the newly introduced paediatric AA workflow and the more extensive use of US in the context of diagnosis of appendicitis.In the beginning of the study, the percentage of US scanning was 72% and was increased to 90% after the end of the 3rd period. Conclusions The introduction of the paediatric AA workflow and the more extensive use of US helped to decrease the percentage of negative rate of paediatric appendicecomy the number of children who underwent unnecessary operation.