QUALITY CONTROL IN ECHOCARDIOGRAPHY REPORTING (PART A)

For cardiac evaluation echocardiography is of immense importance. Easy availability, low cost, and portability lands it in the hands of novices at times. It has a learning curve and expertise must be obtained to keep the standard of reports high and reliable. The referring physician must be fully conversant with the indications of echocardiography. The echocardiographic machine should deliver images of high resolution and fully equipped with all the basic modalities. Availability of 3D (3-dimensional) imaging, tissue synchronization imaging and strain analysis are added advantages. Preliminary data of patient must be collected and the study should be recorded for off-line analysis. Finally, the findings should be narrated on a proforma in the form of a standardized report showing all the relevant features, especially directed to the query of referring physician, thus completing the loop.

Accuracy of the Electronic Nose Breath Tests in Clinical Application: A Systematic Review and Meta-Analysis

(1) Background: An electronic nose applies a sensor array to detect volatile biomarkers in exhaled breath to diagnose diseases. The overall diagnostic accuracy remains unknown. The objective of this review was to provide an estimate of the diagnostic accuracy of sensor-based breath tests for the diagnosis of diseases. (2) Methods: We searched the PubMed and Web of Science databases for studies published between 1 January 2010 and 14 October 2021. The search was limited to human studies published in the English language. Clinical trials were not included in this review. (3) Results: Of the 2418 records identified, 44 publications were eligible, and 5728 patients were included in the final analyses. The pooled sensitivity was 90.0% (95% CI, 86.3–92.8%, I2 = 47.7%), the specificity was 88.4% (95% CI, 87.1–89.5%, I2 = 81.4%), and the pooled area under the curve was 0.93 (95% CI 0.91–0.95). (4) Conclusion: The findings of our review suggest that a standardized report of diagnostic accuracy and a report of the accuracy in a test set are needed. Sensor array systems of electronic noses have the potential for noninvasiveness at the point-of-care in hospitals. Nevertheless, the procedure for reporting the accuracy of a diagnostic test must be standardized.

Digital Semiology: A Prototype for Standardized, Computer-Based Semiologic Encoding of Seizures

Video-EEG monitoring (VEM) is imperative in seizure classification and presurgical assessment of epilepsy patients. Analysis of VEM is currently performed in most institutions using a freeform report, a time-consuming process resulting in a non-standardized report, limiting the use of this essential diagnostic tool. Herein we present a pilot feasibility study of our experience with “Digital Semiology” (DS), a novel seizure encoding software. It allows semiautomated annotation of the videos of suspected events from a predetermined, hierarchal set of options, with highly detailed semiologic descriptions, somatic localization, and timing. In addition, the software's semiologic extrapolation functions identify characteristics of focal seizures and PNES, sequences compatible with a Jacksonian march, and risk factors for SUDEP. Sixty episodes from a mixed adult and pediatric cohort from one level 4 epilepsy center VEM archives were analyzed using DS and the reports were compared with the standard freeform ones, written by the same epileptologists. The behavioral characteristics appearing in the DS and freeform reports overlapped by 78–80%. Encoding of one episode using DS required an average of 18 min 13 s (standard deviation: 14 min and 16 s). The focality function identified 19 out of 43 focal episodes, with a sensitivity of 45.45% (CI 30.39–61.15%) and specificity of 87.50% (CI 61.65–98.45%). The PNES function identified 6 of 12 PNES episodes, with a sensitivity of 50% (95% CI 21.09–78.91%) and specificity of 97.2 (95% CI 88.93–99.95%). Eleven events of GTCS triggered the SUDEP risk alert. Overall, these results show that video recordings of suspected seizures can be encoded using the DS software in a precise manner, offering the added benefit of semiologic alerts. The present study represents an important step toward the formation of an annotated video archive, to be used for machine learning purposes. This will further the goal of automated VEM analysis, ultimately contributing to wider utilization of VEM and therefore to the reduction of the treatment gap in epilepsy.

Glioblastoma Surgery Imaging–Reporting and Data System: Validation and Performance of the Automated Segmentation Task

For patients with presumed glioblastoma, essential tumor characteristics are determined from preoperative MR images to optimize the treatment strategy. This procedure is time-consuming and subjective, if performed by crude eyeballing or manually. The standardized GSI-RADS aims to provide neurosurgeons with automatic tumor segmentations to extract tumor features rapidly and objectively. In this study, we improved automatic tumor segmentation and compared the agreement with manual raters, describe the technical details of the different components of GSI-RADS, and determined their speed. Two recent neural network architectures were considered for the segmentation task: nnU-Net and AGU-Net. Two preprocessing schemes were introduced to investigate the tradeoff between performance and processing speed. A summarized description of the tumor feature extraction and standardized reporting process is included. The trained architectures for automatic segmentation and the code for computing the standardized report are distributed as open-source and as open-access software. Validation studies were performed on a dataset of 1594 gadolinium-enhanced T1-weighted MRI volumes from 13 hospitals and 293 T1-weighted MRI volumes from the BraTS challenge. The glioblastoma tumor core segmentation reached a Dice score slightly below 90%, a patientwise F1-score close to 99%, and a 95th percentile Hausdorff distance slightly below 4.0 mm on average with either architecture and the heavy preprocessing scheme. A patient MRI volume can be segmented in less than one minute, and a standardized report can be generated in up to five minutes. The proposed GSI-RADS software showed robust performance on a large collection of MRI volumes from various hospitals and generated results within a reasonable runtime.

Clinical Evaluation of Automatic Coronary Artery Disease Reporting and Data System (CAD-RADS TM) in Coronary CT Angiography Using Convolutional Neural Networks

Background: The coronary artery disease reporting and data system (CAD-RADSTM) was recently introduced for standard reporting. We aimed to evaluate the utility of an automatic post-processing and reporting system based on CAD-RADS in suspected CAD patients.Methods: The clinical evaluation was encompassed 346 patients who underwent coronary computed tomography angiography (CCTA). We compared deep learning (DL)-based CCTA with Readers for classification of CAD-RADS with commercially-available automated segmentation and manual post-processing in a prospective validation cohort. Results: Compared with invasive coronary angiography (ICA), the sensitivity, specificity, positive predictive value, negative predictive value and accuracy of DL model for diagnosis of CAD were 79.02%, 86.52%, 89.50%, 73.94% and 82.08%, respectively. There was no significant difference between the DL-based and Readers-based CAD-RADS grading in CCTA. The consistency test showed that the Kappa value between the model and Readers was 0.775 (95% CI: 0.728-0.823, P < 0.001), 0.802 (95% CI: 0.756-0.847, P<0.001), and 0.796 (95% CI: 0.750-0.843, P < 0.001), respectively. This system reduces the time consumed from 14.97 ± 1.80 min to 5.02 ± 0.8 min (P < 0.001).Conclusion: The standardized report of DL-based CAD-RADS in CCTA can accurately evaluate suspected CAD patients with time-saving, and has good consistency with the radiologists.

Adverse Events in Neurosurgery: The Novel Therapy-Disability-Neurology Grade

BACKGROUND The most widely used classifications of adverse events (AEs) in neurosurgery define their severity according to the therapy used to treat them. This concept has substantial shortcomings because it does not reflect the severity of AEs that are not treated, such as new neurological deficits. OBJECTIVE To present a novel multidimensional and patient-centered classification of the severity of AE in neurosurgery and evaluate its applicability. METHODS The Therapy-Disability-Neurology (TDN) grading system classifies AEs depending on the associated therapy, disability, and neurological deficits. We conducted a 2-center retrospective observational study on 6071 interventions covering the whole neurosurgical spectrum with data prospectively recorded between 2013 and 2019 at 2 institutions from 2 countries. RESULTS Using the first patient cohort (4680 interventions), a positive correlation was found between severity of AE and LOS as well as treatment cost. Each grade was associated with a greater deterioration of the Karnofsky Performance Status Scale (KPS) at discharge and at follow-up. When using the same methods on the external validation cohort (1391 interventions), correlations between the grades of AE, LOS, and KPS at discharge were even more pronounced. CONCLUSION Our results suggest that the TDN grade is consistent with clinical and economic repercussions of AE and thus reflects AE severity. It is easily interpreted and enables comparison between different medical centers. The standardized report of the severity of AE in the scientific literature could constitute an important step forward toward a more critical, patient-centered, and evidence-based decision-making in neurosurgery.

Perioperative and Anesthetic Adverse Events in Thailand (PAAd Thai) Study: An Analysis of Suspected Myocardial Ischemia/Infarction

Background: Perioperative myocardial ischemia or infarction (PMI) is infrequent but is a life-threatening complication. The pathophysiology is complex, and the diagnosis can be difficult due to asymptomatic presentations. Objective: To investigate the patient, anesthetic, and surgical characteristics of the suspected PMI incidents, as well as the outcomes, and suggested corrective strategies to avoid the adverse events. Materials and Methods: The suspected PMI incident reports were extracted from the database of the Perioperative and Anesthetic Adverse Events in Thailand (PAAd Thai) study, conducted between January 1, and December 31, 2015. Surgical patients undergoing anesthesia with suspected PMI reported in 22 hospitals were included. Three anesthesiologists independently reviewed the reports. The patient, anesthetic, and surgical profiles, and other incident details were collected from the standardized report forms. Descriptive statistics were used. Results: Suspected PMI was reported in 29 non-cardiac surgical patients with the mortality rate of 20.7% (6/29 patients). PMI was confirmed in 24 patients (82.8%). Non-ST-elevation MI (NSTEMI) was the predominant diagnosis of all reports (15/29 patients, 51.7%). Most incidents occurred in the operating room and were asymptomatic at presentation. Patient factor was considered the most common predisposing factor (96.5%), followed by surgery (58.6%), and anesthesia (37.9%). Quality assurance activity was the most recommended corrective strategies. Conclusion: PMI is not common among non-cardiac surgical patients in Thailand but causes significant mortality. Understanding the pathophysiology and being aware of PMI are important for appropriate perioperative management. Furthermore, early detection, along with multidisciplinary assessment for optimization of the treatment are crucial for prognostic outcomes. Keywords: Perioperative, Adverse event, Anesthesia, Myocardial, Infarction, Ischemia, Complication

Research of Automatic Generation for Engineering Geological Survey Reports Based on a Four-Dimensional Dynamic Template

Errors and inefficiency may be caused by manual processing of complex templates for the preparation and management of engineering survey reports. To address this problem, this paper analyzes the multidimensional variable features of professional field documents and proposes a generation model of standardized reports based on a four-dimensional dynamic template. This approach splits the standardized report into multiple parts to construct a hierarchical tree that represents the report structure according to the report rules, then stores the tree in a graph database, and finally generates the desired report dynamically by retrieving the relational tree for the template and obtaining the relevant data. The model has been applied to the engineering geological survey report system and is shown to improve the working efficiency and data accuracy of the report preparation. Results indicate that the model is feasible and effective.

Skin Reaction Report Form: Development and Design of a Standardized Report Form for Skin Reactions Due to Medical Devices for Diabetes Management

Background: Skin reactions due to medical devices for diabetes management have become a common problem in diabetes technology. There is a varying degree in how detailed skin reactions are described in scientific literature and diabetes practice, and no uniform structured documentation is given. Whereas most articles only describe findings, some others already document final diagnoses, such as contact dermatitis. Furthermore, inconsistent wordings for comparable issues were used. Methods: A more detailed and standardized documentation, possibly facilitated by a generally accepted guideline for structured descriptions, of skin reactions could be helpful to enable better differentiations between the described skin reactions. Therefore, a report form to assess skin reactions due to medical devices in diabetes therapy was developed and will be presented in this article. Results: The one-page report form is divided into four categories and a separate instruction paper. Beside general information the form includes the location, size, severity and duration of skin appearances, the grading of itching, and suspected diagnoses. Conclusion: A consistent use of the form in daily practice and clinical trials could facilitate a fast and standardized documentation and help to evaluate the occurrence and severity of different skin reactions due to medical devices in diabetes management.