Feasibility of ABUS as an Alternative to Handheld Ultrasound for Response Control in Neoadjuvant Breast Cancer Treatment.

INTRODUCTION: The Invenia Automated Breast Ultrasound Screening (ABUS) is indicated as an adjunct to mammography for breast cancer screening in asymptomatic women with high-density breast tissue. ABUS provides time-efficient evaluation of the 3-dimensional recordings within 3 to 6 minutes. The role and advantages of ABUS in everyday clinical practice, especially in routine examination during neoadjuvant chemotherapy (NACT), is not clear. The aim of this monocentric, noninterventional retrospective study is to evaluate the use of ABUS in patients who are under NACT treatment for response control. METHODS: Regular sonographic response check with handheld ultrasound (HHUS) examination and with ABUS were conducted in 83 women who underwent NACT. The response controls were conducted every 3 to 6 weeks during NACT. The handheld sonography was performed with GE Voluson S8. Handheld sonographic measurements and ABUS measurements were compared with the final pathologic tumor size. RESULTS: There was no statistical difference between the measurements with HHUS examination or ABUS compared with final pathologic tumor size (P = .47). The average difference from ABUS measured tumor size to final pathologic tumor size was 9.8 mm. The average difference from handheld measured tumor size to final pathologic tumor size was 9/3 mm. Both the specificity of ABUS and HHUS examination in predicting pathologic complete remission was 100%. CONCLUSION: ABUS seems to be a suitable method to conduct response control in neoadjuvant breast cancer treatment. ABUS may facilitate preoperative planning and offers remarkable time saving for physicians compared with HHUS examination and thus should be considered for clinical practice.

Cognition: development of a cognitive testing battery on the iPad for the evaluation of patients with brain Mets.

To make assessment of neurocognitive decline in patients with brain metastases more reliable and feasible, Brainlab AG developed an application 'Cognition' for the iPad by gamifying validated paper and pencil tests. This study aims at validating the computerized tests. We assessed reliability and comparability of 'Cognition' with similar well-established paper and pencil tests in two consecutive sessions per participant. The electronic tests used the same assignments with different stimuli than the paper and pencil tests. Domains involved are learning and memory, attention and processing speed, verbal fluency and executive functions. In total 5 employees and 25 cancer patients without disease in the CNS participated, of whom 24 completed both sessions. Reliability was found satisfying for the domains learning and memory (p = 0.08; p = 0.612; p = 0.4445) and verbal fluency (p = 0.064). A learning effect showed for attention and processing speed (p = 0.001) while executive functioning showed a significant decline, possibly due to radiotherapy-related fatigue (p = 0.013). Concerning comparability between electronic and paper results, a significant correlation was found for attention and processing speed (p = 0.000), for verbal fluency (p = 0.03), for executive functions (p = 0.000), but not for learning and memory (p = 0.41; p = 0.25). Overall 'Cognition' showed moderate comparability, probably caused by the consecution of tests during sessions and the unfamiliarity with electronic test in older patients. After improving its functionality, the application needs to be validated in patients with brain metastases before it can detect cognitive decline and possible early radiation toxicity or relapses.

Implementation of artificial intelligence algorithms for melanoma screening in a primary care setting.

Skin cancer is currently the most common type of cancer among Caucasians. The increase in life expectancy, along with new diagnostic tools and treatments for skin cancer, has resulted in unprecedented changes in patient care and has generated a great burden on healthcare systems. Early detection of skin tumors is expected to reduce this burden. Artificial intelligence (AI) algorithms that support skin cancer diagnoses have been shown to perform at least as well as dermatologists' diagnoses. Recognizing the need for clinically and economically efficient means of diagnosing skin cancers at early stages in the primary care attention, we developed an efficient computer-aided diagnosis (CAD) system to be used by primary care physicians (PCP). Additionally, we developed a smartphone application with a protocol for data acquisition (i.e., photographs, demographic data and short clinical histories) and AI algorithms for clinical and dermoscopic image classification. For each lesion analyzed, a report is generated, showing the image of the suspected lesion and its respective Heat Map; the predicted probability of the suspected lesion being melanoma or malignant; the probable diagnosis based on that probability; and a suggestion on how the lesion should be managed. The accuracy of the dermoscopy model for melanoma was 89.3%, and for the clinical model, 84.7% with 0.91 and 0.89 sensitivity and 0.89 and 0.83 specificity, respectively. Both models achieved an area under the curve (AUC) above 0.9. Our CAD system can screen skin cancers to guide lesion management by PCPs, especially in the contexts where the access to the dermatologist can be difficult or time consuming. Its use can enable risk stratification of lesions and/or patients and dramatically improve timely access to specialist care for those requiring urgent attention.

CAD systems for colorectal cancer from WSI are still not ready for clinical acceptance.

Most oncological cases can be detected by imaging techniques, but diagnosis is based on pathological assessment of tissue samples. In recent years, the pathology field has evolved to a digital era where tissue samples are digitised and evaluated on screen. As a result, digital pathology opened up many research opportunities, allowing the development of more advanced image processing techniques, as well as artificial intelligence (AI) methodologies. Nevertheless, despite colorectal cancer (CRC) being the second deadliest cancer type worldwide, with increasing incidence rates, the application of AI for CRC diagnosis, particularly on whole-slide images (WSI), is still a young field. In this review, we analyse some relevant works published on this particular task and highlight the limitations that hinder the application of these works in clinical practice. We also empirically investigate the feasibility of using weakly annotated datasets to support the development of computer-aided diagnosis systems for CRC from WSI. Our study underscores the need for large datasets in this field and the use of an appropriate learning methodology to gain the most benefit from partially annotated datasets. The CRC WSI dataset used in this study, containing 1,133 colorectal biopsy and polypectomy samples, is available upon reasonable request.

Batch enrollment for an artificial intelligence-guided intervention to lower neurologic events in patients with undiagnosed atrial fibrillation: rationale and design of a digital clinical trial.

BACKGROUND: Clinical trials are a fundamental tool to evaluate medical interventions but are time-consuming and resource-intensive. OBJECTIVES: To build infrastructure for digital trials to improve efficiency and generalizability and test it using a study to validate an artificial intelligence algorithm to detect atrial fibrillation (AF). DESIGN: We will prospectively enroll 1,000 patients who underwent an electrocardiogram for any clinical reason in routine practice, do not have a previous diagnosis of AF or atrial flutter and would be eligible for anticoagulation if AF is detected. Eligible patients will be identified using digital phenotyping algorithms, including natural language processing that runs on the electronic health records. Study invitations will be sent in batches via patient portal or letter, which will direct patients to a website to verify eligibility, learn about the study (including video-based informed consent), and consent electronically. The method aims to enroll participants representative of the general patient population, rather than a convenience sample of patients presenting to clinic. A device will be mailed to patients to continuously monitor for up to 30 days. The primary outcome is AF diagnosis and burden; secondary outcomes include patients' experience with the trial conduct methods and the monitoring device. The enrollment, intervention, and follow-up will be conducted remotely, ie, a patient-centered site-less trial. SUMMARY: This is among the first wave of trials to adopt digital technologies, artificial intelligence, and other pragmatic features to create efficiencies, which will pave the way for future trials in a broad range of disease and treatment areas. Clinicaltrials.gov: NCT04208971.

First proof-of-concept evaluation of the FUSION-X-US-II prototype for the performance of automated breast ultrasound in healthy volunteers.

PURPOSE: The FUSION-X-US-II prototype was developed to combine 3D-automated breast ultrasound (ABUS) and digital breast tomosynthesis in a single device without decompressing the breast. We evaluated the technical function, feasibility of the examination workflow, image quality, breast tissue coverage and patient comfort of the ABUS device of the new prototype. METHODS: In this prospective feasibility study, the FUSION-X-US-II prototype was used to perform ABUS in 30 healthy volunteers without history of breast cancer. The ABUS images of the prototype were interpreted by a physician with specialization in breast diagnostics. Any detected lesions were measured and classified using BI-RADS® scores. Image quality was rated subjectively by the physician and coverage of the breast was measured. Patient comfort was evaluated by a questionnaire after the examination. RESULTS: One hundred and six scans were performed (61 × CC, 23 × ML, 22 × MLO) in 60 breasts. Image acquisition and processing by the prototype was fast and accurate. Breast coverage by ABUS was approximately 90.8%. Sixteen breast lesions (all benign, classified as BIRADS® 2) were identified. The examination was tolerated by all patients. CONCLUSION: The FUSION-X-US-II prototype allows a rapid ABUS scan with mostly high patient comfort. Technical developments resulted in an improvement of quality and coverage compared to previous prototype versions. The results are encouraging for a test of the prototype in a clinical setting in combination with tomosynthesis.

Prospective Development and Validation of the Computerized Adaptive Screen for Suicidal Youth.

Importance: The rate of suicide among adolescents is rising in the US, yet many adolescents at risk are unidentified and receive no mental health services. Objective: To develop and independently validate a novel computerized adaptive screen for suicidal youth (CASSY) for use as a universal screen for suicide risk in medical emergency departments (EDs). Design, Setting, and Participants: Study 1 of this prognostic study prospectively enrolled adolescent patients at 13 geographically diverse US EDs in the Pediatric Emergency Care Applied Research Network. They completed a baseline suicide risk survey and participated in 3-month telephone follow-ups. Using 3 fixed Ask Suicide-Screening Questions items as anchors and additional items that varied in number and content across individuals, we derived algorithms for the CASSY. In study 2, data were collected from patients at 14 Pediatric Emergency Care Applied Research Network EDs and 1 Indian Health Service hospital. Algorithms were independently validated in a prospective cohort of adolescent patients who also participated in 3-month telephone follow-ups. Adolescents aged 12 to 17 years were consecutively approached during randomly assigned shifts. Exposures: Presentation at an ED. Main Outcome and Measure: A suicide attempt between ED visit and 3-month follow-up, measured via patient and/or parent report. Results: The study 1 CASSY derivation sample included 2075 adolescents (1307 female adolescents [63.0%]; mean [SD] age, 15.1 [1.61] years) with 3-month follow-ups (72.9% retention [2075 adolescents]). The study 2 validation sample included 2754 adolescents (1711 female adolescents [62.1%]; mean [SD] age, 15.0 [1.65] years), with 3-month follow-ups (69.5% retention [2754 adolescents]). The CASSY algorithms had excellent predictive accuracy for suicide attempt (area under the curve, 0.89 [95% CI, 0.85-0.91]) in study 1. The mean number of adaptively administered items was 11 (range, 5-21). At a specificity of 80%, the CASSY had a sensitivity of 83%. It also demonstrated excellent accuracy in the study 2 validation sample (area under the curve, 0.87 [95% CI, 0.85-0.89]). In this study, the CASSY had a sensitivity of 82.4% for prediction of a suicide attempt at the 80% specificity cutoff established in study 1. Conclusions and Relevance: In this study, the adaptive and personalized CASSY demonstrated excellent suicide attempt risk recognition, which has the potential to facilitate linkage to services.

Early screening of autism spectrum disorder using cry features.

The increase in the number of children with autism and the importance of early autism intervention has prompted researchers to perform automatic and early autism screening. Consequently, in the present paper, a cry-based screening approach for children with Autism Spectrum Disorder (ASD) is introduced which would provide both early and automatic screening. During the study, we realized that ASD specific features are not necessarily observable in all children with ASD and in all instances collected from each child. Therefore, we proposed a new classification approach to be able to determine such features and their corresponding instances. To test the proposed approach a set of data relating to children between 18 to 53 months which had been recorded using high-quality voice recording devices and typical smartphones at various locations such as homes and daycares was studied. Then, after preprocessing, the approach was used to train a classifier, using data for 10 boys with ASD and 10 Typically Developed (TD) boys. The trained classifier was tested on the data of 14 boys and 7 girls with ASD and 14 TD boys and 7 TD girls. The sensitivity, specificity, and precision of the proposed approach for boys were 85.71%, 100%, and 92.85%, respectively. These measures were 71.42%, 100%, and 85.71% for girls, respectively. It was shown that the proposed approach outperforms the common classification methods. Furthermore, it demonstrated better results than the studies which used voice features for screening ASD. To pilot the practicality of the proposed approach for early autism screening, the trained classifier was tested on 57 participants between 10 to 18 months. These 57 participants consisted of 28 boys and 29 girls and the results were very encouraging for the use of the approach in early ASD screening.

Theoretical Background to Automated Diagnosing of Oral Leukoplakia: A Preliminary Report.

Oral leukoplakia represents the most common oral potentially malignant disorder, so early diagnosis of leukoplakia is important. The aim of this study is to propose an effective texture analysis algorithm for oral leukoplakia diagnosis. Thirty-five patients affected by leukoplakia were included in this study. Intraoral photography of normal oral mucosa and leukoplakia were taken and processed for texture analysis. Two features of texture, run length matrix and co-occurrence matrix, were analyzed. Difference was checked by ANOVA. Factor analysis and classification by the artificial neural network were performed. Results revealed easy possible differentiation leukoplakia from normal mucosa (p < 0.05). Neural network discrimination shows full leukoplakia recognition (sensitivity 100%) and specificity 97%. This objective analysis in the neural network revealed that involving 3 textural features into optical analysis of the oral mucosa leads to proper diagnosis of leukoplakia. Application of texture analysis for leukoplakia is a promising diagnostic method.

Toward standardized premarket evaluation of computer aided diagnosis/detection products: insights from FDA-approved products.

INTRODUCTION: Computer aided detection and diagnosis (CADe and CADx) products are an emerging branch of medical device industry. However, limited technical standard has been developed for product verification and validation. It will be helpful to investigate the current practice of preclinical and clinical evaluation of approved products and provide insights for future standardization. AREAS COVERED: Document review was conducted on 56 products approved by the United States Food and Drug Administration, including Summary of Safety and Effectiveness Data, 510(k) decision and de novo decision summaries. Key parameters describing product characteristics, preclinical studies and clinical studies were collected. Evaluation strategies for CADe/CADx products were analyzed and assessed. EXPERT OPINION: Preclinical studies were widely adopted in the verification of CADe/CADx products. Standalone performance testing was a common procedure, but the selection of testing dataset and performance metrics showed significant variability and flexibility among manufacturers. Clinical studies were reported by all class III products and some class II products, and Multi-Reader Multi-Case design was commonly used. However, statistical analysis and presentation/interpretation of results was oftentimes incomplete. To resolve above issues, systematic development of standards of CADe/CADx is encouraged, which can be implemented at different aspects through the product lifecycle.

Initial testing of an electronic application of the simplified modified Rankin Scale questionnaire (e-smRSq).

INTRODUCTION AND PURPOSE: To facilitate modified Rankin scale (mRS) assessments, we developed and tested a smartphone/web application of the simplified mRS questionnaire (e-smRSq). The e-smRSq guides raters towards a final score according to the smRSq algorithm, and offers hints for scoring based on the conventional mRS concepts. METHODS: Initially, three experienced mRS certified raters prepared 30 vignettes of unstructured stroke patient interviews, and determined consensus reference scores. Using the e-smRSq, 16 raters of varied professional backgrounds without mRS training scored the mRS for 24 randomly selected vignettes. Subsequently, 5 certified and 5 uncertified raters using the e-smRSq scored 23 mRS certification vignettes developed and used in the Strategies to Innovate Emergency Care Clinical Trials Network-Neurological Emergencies Treatment Trials (SIREN-NETT). Cohen's and Fleiss's kappa (κ), weighted kappa (κw), and intra-class correlation (ICC) compared rater scores with reference scores and assessed interrater reliability. RESULTS: For the 16 initial raters using the e-smRSq with 24 vignettes, the κ (Fleiss) was 0.62 and ICC 0.87 (CI 0.80-0.93). Comparing raters' scores with reference scores, Cohen's κ was 0.68 and κw 0.90. For the 10 subsequent raters using the e-smRSq on SIREN-NETT vignettes, κ (Fleiss) was 0.8 and ICC 0.95 (CI 0.91-0.97). Comparing all 10 raters scores with SIREN-NETT reference scores, Cohen's κ was 0.88 and κw 0.97. There was no significant difference between certified and uncertified raters. CONCLUSIONS: The e-smRSq appears to have good reproducibility and validity metrics among both certified and non-certified mRS raters, possibly owing to its simplicity. Further testing in stroke patients in warranted.

A valuable and affordable handheld ultrasound in combating COVID-19.

The handheld ultrasound demonstrates clinical and economic value in combating COVID-19 based on interviews with frontline ultrasound physician and cardiologist as well as a national expert in medical ultrasound.

A Noninvasive Assistant System in Diagnosis of Lumbar Disc Herniation.

The purpose of this study is the application of pressure sensors in diagnostics and evaluation of the accuracy diagnostics of lumbar disc herniation at levels L4/L5 and L5/S1 using the aforementioned platform. The motivation behind the idea to apply the pressure measurement platform is the fact that the motor weakness of plantar and dorsal flexia of the feet is one of the absolute indications for the operative treatment of patients with lumbar disc herniation at the indicated levels. In patients, MRI diagnosis of the lumbosacral spine served as the ground truth in the diagnosis of herniation at L4/L5 and L5/S1 levels. The inclusive criteria for the study were the proven muscle weakness based on manual muscle tests performed prior to surgery, after seven days of surgery and after physical therapy. The results obtained with the manual muscular test were compared with the results obtained using our platform. The study included 33 patients who met the inclusion criteria. The results of the measurements indicate that the application of our platform with pressure sensors has the same sensitivity diagnostics as a manual muscle test, when done preoperatively and postoperatively. After physical therapy, pressure sensors show statistically significantly better sensitivity compared to the clinical manual muscle test. The obtained results are encouraging in the sense that the pressure platform can be an additional diagnostic method for lumbar disc herniation detection and can indicate the effectiveness of operative treatment and physical therapy after operation. The main advantage of the system is the cost; the whole system with platform and sensors is not expensive.

Machine-Scored Syntax: Comparison of the CLAN Automatic Scoring Program to Manual Scoring.

Purpose The results of automatic machine scoring of the Index of Productive Syntax from the Computerized Language ANalysis (CLAN) tools of the Child Language Data Exchange System of TalkBank (MacWhinney, 2000) were compared to manual scoring to determine the accuracy of the machine-scored method. Method Twenty transcripts of 10 children from archival data of the Weismer Corpus from the Child Language Data Exchange System at 30 and 42 months were examined. Measures of absolute point difference and point-to-point accuracy were compared, as well as points erroneously given and missed. Two new measures for evaluating automatic scoring of the Index of Productive Syntax were introduced: Machine Item Accuracy (MIA) and Cascade Failure Rate- these measures further analyze points erroneously given and missed. Differences in total scores, subscale scores, and individual structures were also reported. Results Mean absolute point difference between machine and hand scoring was 3.65, point-to-point agreement was 72.6%, and MIA was 74.9%. There were large differences in subscales, with Noun Phrase and Verb Phrase subscales generally providing greater accuracy and agreement than Question/Negation and Sentence Structures subscales. There were significantly more erroneous than missed items in machine scoring, attributed to problems of mistagging of elements, imprecise search patterns, and other errors. Cascade failure resulted in an average of 4.65 points lost per transcript. Conclusions The CLAN program showed relatively inaccurate outcomes in comparison to manual scoring on both traditional and new measures of accuracy. Recommendations for improvement of the program include accounting for second exemplar violations and applying cascaded credit, among other suggestions. It was proposed that research on machine-scored syntax routinely report accuracy measures detailing erroneous and missed scores, including MIA, so that researchers and clinicians are aware of the limitations of a machine-scoring program. Supplemental Material https://doi.org/10.23641/asha.11984364.

Continuous Wearable Monitoring Analytics Predict Heart Failure Hospitalization: The LINK-HF Multicenter Study.

BACKGROUND: Implantable cardiac sensors have shown promise in reducing rehospitalization for heart failure (HF), but the efficacy of noninvasive approaches has not been determined. The objective of this study was to determine the accuracy of noninvasive remote monitoring in predicting HF rehospitalization. METHODS: The LINK-HF study (Multisensor Non-invasive Remote Monitoring for Prediction of Heart Failure Exacerbation) examined the performance of a personalized analytical platform using continuous data streams to predict rehospitalization after HF admission. Study subjects were monitored for up to 3 months using a disposable multisensor patch placed on the chest that recorded physiological data. Data were uploaded continuously via smartphone to a cloud analytics platform. Machine learning was used to design a prognostic algorithm to detect HF exacerbation. Clinical events were formally adjudicated. RESULTS: One hundred subjects aged 68.4±10.2 years (98% male) were enrolled. After discharge, the analytical platform derived a personalized baseline model of expected physiological values. Differences between baseline model estimated vital signs and actual monitored values were used to trigger a clinical alert. There were 35 unplanned nontrauma hospitalization events, including 24 worsening HF events. The platform was able to detect precursors of hospitalization for HF exacerbation with 76% to 88% sensitivity and 85% specificity. Median time between initial alert and readmission was 6.5 (4.2-13.7) days. CONCLUSIONS: Multivariate physiological telemetry from a wearable sensor can provide accurate early detection of impending rehospitalization with a predictive accuracy comparable to implanted devices. The clinical efficacy and generalizability of this low-cost noninvasive approach to rehospitalization mitigation should be further tested. Registration: URL: https://www.clinicaltrials.gov. Unique Identifier: NCT03037710.

Assessing Arm Volume in People During and After Treatment for Breast Cancer: Reliability and Convergent Validity of the LymphaTech System.

BACKGROUND: There are challenges related to the accurate and efficient measurement of lymphedema in people with breast cancer. The LymphaTech 3D Imaging System (LymphaTech, Atlanta, GA, USA) is a mobile, noninvasive platform that provides limb geometry measurements. OBJECTIVE: The objective of this study was to estimate the reliability and validity of the LymphaTech for measuring arm volume in the context of women seeking care in a specialty breast cancer rehabilitation clinic. DESIGN: This was a cross-sectional reliability and convergent validity study. METHODS: People who had stage I to IV breast cancer with lymphedema or were at risk for it were included. Arm volume was measured in 66 participants using the LymphaTech and perometer methods. Test-retest reliability for a single measure, limb volume difference, and agreement between methods was analyzed for 30 participants. A method-comparison analysis was also used to assess convergent validity between methods. RESULTS: Both LymphaTech and perometer methods displayed intraclass correlation coefficients (ICCs) of ≥0.99. The standard errors of measurement for the LymphaTech and length-matched perometer measurements were nearly identical. Similar intraclass correlation coefficients (0.97) and standard errors of measurement (38.0-40.7 mL) were obtained for the between-limb volume difference for both methods. The convergent validity analyses demonstrated no systematic difference between methods. LIMITATIONS: The sample size was not based on a formal sample size calculation. LymphaTech measurements included interrater variance, and perometer measurements contained intrarater variance. CONCLUSIONS: The LymphaTech had excellent test-retest reliability, and convergent validity was supported. This technology is efficient and portable and has a potential role in prospective surveillance and management of lymphedema in clinical, research, and home settings.

Effect of a deep-learning computer-aided detection system on adenoma detection during colonoscopy (CADe-DB trial): a double-blind randomised study.

BACKGROUND: Colonoscopy with computer-aided detection (CADe) has been shown in non-blinded trials to improve detection of colon polyps and adenomas by providing visual alarms during the procedure. We aimed to assess the effectiveness of a CADe system that avoids potential operational bias. METHODS: We did a double-blind randomised trial at the endoscopy centre in Caotang branch hospital of Sichuan Provincial People's Hospital in China. We enrolled consecutive patients (aged 18-75 years) presenting for diagnostic and screening colonoscopy. We excluded patients with a history of inflammatory bowel disease, colorectal cancer, or colorectal surgery or who had a contraindication for biopsy; we also excluded patients who had previously had an unsuccessful colonoscopy and who had a high suspicion for polyposis syndromes, inflammatory bowel disease, and colorectal cancer. We allocated patients (1:1) to colonoscopy with either the CADe system or a sham system. Randomisation was by computer-generated random number allocation. Patients and the endoscopist were unaware of the random assignment. To achieve masking, the output of the system was shown on a second monitor that was only visible to an observer who was responsible for reporting the alerts. The primary outcome was the adenoma detection rate (ADR), which is the proportion of individuals having a complete colonoscopy, from caecum to rectum, who had one or more adenomas detected. The primary analysis was per protocol. We also analysed characteristics of polyps and adenomas missed initially by endoscopists but detected by the CADe system. This trial is complete and is registered with http://www.chictr.org.cn, ChiCTR1800017675. FINDINGS: Between Sept 3, 2018, and Jan 11, 2019, 1046 patients were enrolled to the study, of whom 36 were excluded before randomisation, 508 were allocated colonoscopy with polyp detection using the CADe system, and 502 were allocated colonoscopy with the sham system. After further excluding patients who met exclusion criteria, 484 patients in the CADe group and 478 in the sham group were included in analyses. The ADR was significantly greater in the CADe group than in the sham group, with 165 (34%) of 484 patients allocated to the CADe system having one or more adenomas detected versus 132 (28%) of 478 allocated to the sham system (odds ratio 1·36, 95% CI 1·03-1·79; p=0·030). No complications were reported among all colonoscopy procedures. Polyps initially missed by the endoscopist but identified by the CADe system were generally small in size, isochromatic, flat in shape, had an unclear boundary, were partly behind colon folds, and were on the edge of the visual field. INTERPRETATION: Polyps initially missed by the endoscopist had characteristics that are sometimes difficult for skilled endoscopists to recognise. Such polyps could be detected using a high-performance CADe system during colonoscopy. The effect of CADe during colonoscopy on the incidence of interval colorectal cancer should be investigated. FUNDING: None.

Concurrent validity and intratester reliability of the video-based system for measuring gait poststroke.

BACKGROUND AND PURPOSE: Spatio-temporal parameters are commonly used in gait assessment. Advanced tools provide valid and reliable data, considered very effective for physiotherapy intervention. However, these tools may be limited in clinical usage caused by complicated applicability, inaccessibility, and high cost. Therefore, a video-based system is an alternative choice that is easy and affordable for the clinical setting. The purpose of the study was to evaluate the concurrent validity of the video-based system against the validated instrumented gait system (Force Distribution Measurement [FDM]) on the spatio-temporal gait parameters in individuals with stroke. In addition, the intratester reliability of a novice tester was determined. METHODS: Twenty individuals with stroke participated in the study. Gait was captured by the video-based and FDM systems simultaneously to measure the degree of concurrent validity. Parameters composed of the affected and unaffected step lengths (cm) and step time (s), stride length (cm), gait velocity (m/s), and cadence (steps/min). Pearson correlation coefficient, paired t test, and intraclass correlation coefficient (ICC) were used to determine the concurrent validity, the difference of the data, and intratester reliability. RESULTS: All spatio-temporal gait parameters showed excellent degrees of correlation (rp = .94 to.99, p <.001) between the video-based and FDM systems. No significant difference in all parameters was found between the two systems. Excellent intratester reliability (ICC3,1 = 0.91 to 0.99, p < .001) of all gait parameters were found in a novice tester. CONCLUSION: The video-based system was valid and reliable for a novice tester to measure the spatio-temporal gait parameters in individuals with stroke.

An Early Disc Herniation Identification System for Advancement in the Standard Medical Screening Procedure Based on Bayes Theorem.

The aim of this research was to analyze objectively the process of disc herniation identification using Bayes Theorem. One of the symptoms of discus hernia is muscle weakness on the foot that is caused by displaced discs in the space of two vertebrae. This fact is used by experts in initial diagnosis of herniated discs and we used it to create non-invasive platform for the same purposes by measuring force values from four sensors placed on both feet (first, second, and fourth metatarsal head as well as the heel). Dataset consisted of several minute force recordings of 56 subjects with discus hernia and 15 healthy individuals during normal standing, standing on forefeet and heels. The subjects were diagnosed by a specialist with either L4/L5 or L5/S1 discus hernia. Collected recordings were processed in several steps including filtering, extraction of forefeet and heel recordings, classification of average values for forefeet, and heel sensors to the groups with or without foot muscle weakness. Application of Bayes Theorem on the attributes of interest showed average 78.3% accuracy with 62.6% sensitivity and 80.9% specificity, while application of naive Bayes Network showed average 83.1% accuracy with 57.6% sensitivity and 88.2% specificity. Very weak or no correlation was observed between gender and disc hernia diagnosis (or obesity type and disc hernia diagnosis). Obtained results show that this method can be used in initial screening of patients and be a supportive tool to doctors to send the same patients for further examination.