Diagnostic Judgments Research Articles

An Enquiry into Application-Based Diagnostic Support System for Distal Humerus Fracture using Deep Learning

Abstract Background: Recently, the development of deep learning has been remarkable and the accuracy of the image recognition has improved. Distal humerus fracture treatment is a complex injury requiring good diagnostic judgment and management protocol. There have been no attempts toward development of artificial intelligence (AI) in treating distal humerus. Objectives: To find out whether deep learning (AI) gives reasonable image-based recommendation for the surgical procedure of distal end humerus fractures. Methods: The image of the distal end humerus will be sent to application (app)-based deep learning software. The result of the deep learning software diagnosis and intervention will be compared with two senior orthopedic surgeons’ opinion. Intra- and inter-observer reliability will be studied, and Student’s t-test will be used for identifying the P value of the objective. Expected Outcome: We will identify the layers required for the deep learning software to process the distal humerus fractures and reach a conclusion. The app will help in identification and planning the management of the fracture. Conclusion: The Application based diagnostic support system for the distal humerus fracture is an initial investigation for the usage of AI in peripheral centres and can provided further diagnostic support.

Diagnostic Value of Inflammation-Related Indicators in Distinguishing Early Colon Cancer and Adenomatous Polyps.

There are few clinical symptoms in early colorectal cancer, so it is necessary to find a simple and economical tumor detection index for auxiliary diagnosis. This study aims to explore the diagnostic value of preoperative inflammation-related indicators, such as neutrophil, lymphocyte, platelet count, platelet to lymphocyte ratio (PLA), neutrophil to lymphocyte ratio (NLR), and systemic immune-inflammation index (SII), for early colorectal cancer, and determine whether inflammation-related indicators can provide more accurate diagnostic judgment for patients. This study was a retrospective study. Patients who were first diagnosed with colorectal cancer or colorectal adenomatous polyp at Beijing Friendship Hospital from October 2016 to October 2017 were retrospectively collected. According to inclusion and exclusion criteria, a total of 342 patients were included, including 216 patients with colorectal cancer and 126 patients with colorectal adenomatous polyp. Fasting venous blood and other clinical features were collected to compare the differences between colorectal cancer and colorectal adenoma. There were statistically significant differences in age, carcinoembryonic antigen, albumin, hemoglobin, mean platelet volume, lymphocyte, monocyte, NLR, PLA, SII, and mean platelet volume to platelet count ratio between colorectal cancer group and colorectal adenoma group (P < .05), and a Nomogram model was established. Using inflammatory markers to differentiate colorectal and colorectal polyps produced greater AUC than using tumor markers alone (.846 vs .695). Inflammation-related indicators, such as lymphocyte, monocyte, and mean platelet volume, may serve as potential indicators to assist in the diagnosis of early colorectal cancer.

Prospective Teachers’ Diagnostic Thinking on Students’ Understanding of Multi-Digit Multiplication: A Content-Related Analysis on Unpacking of Knowledge Elements

Teachers’ in-depth diagnostic thinking has been shown to be crucial for student-centered teaching as they need to perceive and interpret students’ understanding for well-informed decision-making on adaptive teaching practices. The paper presents a content-related approach to analyzing diagnostic thinking processes with respect to the mathematical knowledge elements that prospective teachers identify as students’ resources and obstacles. Prospective teachers’ challenge is that some relevant knowledge elements first have to be unpacked, because compact concepts (such as the place value concept) or procedures (such as for multi-digit multiplication) comprise several smaller knowledge elements (such as the positional property) that have to be made explicit for students to foster their learning processes adequately. Our study examines what knowledge elements prospective teachers perceive and interpret in a transcript vignettes on multi-digit multiplication (of decimal and natural numbers) and its underlying basic arithmetic concepts (place value understanding and meaning of multiplication) in written diagnostic judgments on students’ resources and obstacles (N = 196). A comparative design within the vignette is used to investigate how far the process of perceiving can be supported by thematic cues. The analysis reveals that those knowledge elements cued in the vignette by being already unpacked and explicitly addressed are perceived and interpreted more often (but with lower correctness) than those that are uncued and therefore have to be unpacked by the prospective teachers themselves. This confirms the need to prepare prospective teachers for unpacking mathematical concepts themselves.

Diagnostic argumentation in teacher education: Making the case for justification, disconfirmation, and transparency

Research on diagnosing in teacher education has primarily emphasized the accuracy of diagnostic judgments and has explained it in terms of factors such as diagnostic knowledge. However, approaches to scientific argumentation and information processing suggest differentiating between diagnostic judgment and diagnostic argumentation: When making accurate diagnostic judgments, the underlying reasoning can remain intuitive, whereas diagnostic argumentation requires controlled and explicable reasoning about a diagnostic problem to explain the reasoning in a comprehensible and persuasive manner. We suggest three facets of argumentation for conceptualizing diagnostic argumentation, which are yet to be addressed in teacher education research: justification of a diagnosis with evidence, disconfirmation of differential diagnoses, and transparency regarding the processes of evidence generation. Therefore, we explored whether preservice teachers’ diagnostic argumentation and diagnostic judgment might represent different diagnostic skills. We also explored whether justification, disconfirmation, and transparency should be considered distinct subskills of preservice teachers’ diagnostic argumentation. We reanalyzed data of 118 preservice teachers who learned about students’ learning difficulties with simulated cases. For each student case, the preservice teachers had to indicate a diagnostic judgment and provide a diagnostic argumentation. We found that preservice teachers’ diagnostic argumentation seldom involved all three facets, suggesting a need for more specific training. Moreover, the correlational results suggested that making accurate diagnostic judgments and formulating diagnostic argumentation may represent different diagnostic skills and that justification, disconfirmation, and transparency may be considered distinct subskills of diagnostic argumentation. The introduced concepts of justification, disconfirmation, and transparency may provide a starting point for developing standards in diagnostic argumentation in teacher education.

THIRD bedside ultrasound protocol for rapid diagnosis of undifferentiated shock: a prospective observational study.

It is clinically challenging to differentiate the pathophysiological types of shock in emergency situations. Here, we evaluated the ability of a novel bedside ultrasound protocol (Tamponade/tension pneumothorax, Heart, Inferior vena cava, Respiratory system, Deep venous thrombosis/aorta dissection [THIRD]) to predict types of shock in the emergency department. An emergency physician performed the THIRD protocol on all patients with shock who were admitted to the emergency department. All patients were closely followed to determine their final clinical diagnoses. The kappa index, sensitivity, specificity, positive predictive value, and negative predictive value were calculated for the initial diagnostic impression provided by the THIRD protocol, compared with each patient's final diagnosis. In total, 112 patients were enrolled in this study. The kappa index between initial impression and final diagnosis was 0.81 (95% confidence interval=0.73-0.89; P<0.001). For hypovolaemic, cardiogenic, distributive, and obstructive types of shock, the sensitivities of the THIRD protocol were 100%, 100%, 93%, and 100%, respectively; the sensitivity for a 'mixed' shock aetiology was 86%. The negative predictive value of the THIRD protocol for all five types of shock was ≥96%. Initial diagnostic judgements determined using the THIRD protocol showed favourable agreement with the final diagnosis in patients who presented with undifferentiated shock. The THIRD protocol has great potential for use as a bedside approach that can guide the rapid management of undifferentiated shock in emergency settings, particularly for patients with obstructive, hypovolaemic, or cardiogenic shock.

Machine learning techniques for CT imaging diagnosis of novel coronavirus pneumonia: a review.

Since 2020, novel coronavirus pneumonia has been spreading rapidly around the world, bringing tremendous pressure on medical diagnosis and treatment for hospitals. Medical imaging methods, such as computed tomography (CT), play a crucial role in diagnosing and treating COVID-19. A large number of CT images (with large volume) are produced during the CT-based medical diagnosis. In such a situation, the diagnostic judgement by human eyes on the thousands of CT images is inefficient and time-consuming. Recently, in order to improve diagnostic efficiency, the machine learning technology is being widely used in computer-aided diagnosis and treatment systems (i.e., CT Imaging) to help doctors perform accurate analysis and provide them with effective diagnostic decision support. In this paper, we comprehensively review these frequently used machine learning methods applied in the CT Imaging Diagnosis for the COVID-19, discuss the machine learning-based applications from the various kinds of aspects including the image acquisition and pre-processing, image segmentation, quantitative analysis and diagnosis, and disease follow-up and prognosis. Moreover, we also discuss the limitations of the up-to-date machine learning technology in the context of CT imaging computer-aided diagnosis.

I value the problem, but I don’t think my students will: preservice teachers’ judgments of task value and self-efficacy for modelling, word, and intramathematical problems

According to expectancy-value models, two important motivational constructs are task value and self-efficacy expectations. As students work intensively on mathematical problems in the classroom, teachers need the competence to judge whether students value solving the problem and how confident they are that they will succeed. However, not much is known about the mechanisms behind teachers’ judgments concerning students’ motivation. The goal of the present study was to answer the following research questions: (a) How do preservice teachers rate their own task value and self-efficacy for modelling, word, and intramathematical problems? (b) Are there differences in preservice teachers’ diagnostic judgments concerning school students’ task value and self-efficacy for modelling, word, and intramathematical problems? (c) Do preservice teachers’ own task value and self-efficacy for modelling, word, and intramathematical problems differ from preservice teachers’ judgments of school students’ task value and self-efficacy? A total of 182 preservice teachers were asked about the value of 12 problems, their confidence in solving the problems, and how hypothetical ninth graders would judge these constructs. Preservice teachers’ ratings of their own perceptions regarding both constructs were lower for modelling problems than for other problems. When judging school students’ motivation, ratings of both constructs were higher for word problems. Preservice teachers’ ratings of their own motivation were significantly higher across all types of problems than their judgments of school students’ perspectives. A positive correlation between preservice teachers’ own motivation and their judgments of school students’ motivation indicates the importance of teachers’ perceptions of their own motivation to solve mathematical problems for diagnostic judgments.

Analysis of the “Diagnostic Reasoning” Concept in Nursing

Objective: To develop an operational definition of the “diagnostic reasoning” concept in nursing. Materials and methods: This concept analysis is based on Walker and Avant’s model. All the referential steps were followed: concept selection, determining the objectives and proposals for concept analysis, identifying the possible uses of the concept, determining the defining attributes, identifying a model case, identifying the contrary case, and identifying the precedents and consequences of the concept. Results: A sample of 20 studies was selected, identifying the following attributes: specialized thinking, cognitive skills, existing knowledge, intellectual competence; hypothesis-oriented reasoning; precedents: clinical assessment, practical experience, data interpretations, intuition, diagnostic judgment, information processing, clinical reasoning; consequences: improvement of nursing care, communication, planning interventions, addressing the identified problem, achieving effective results, autonomous actions, and quality of patient records. Conclusions: The study contributes to understanding the operational definition of the diagnostic reasoning concept in nursing by identifying the core attributes, precedents, and consequences.

Teacher expertise for fostering at-risk students’ understanding of basic concepts: conceptual model and evidence for growth

Various intervention programs for fostering at-risk students’ understanding of basic concepts (such as place value understanding or meanings of multiplication and division) have been developed and evaluated. However, little is known about the teacher expertise required to enact these intervention programs, and how this teacher expertise can be promoted. The article suggests a conceptual model for teacher expertise for fostering at-risk students’ understanding based on three recurrent jobs: (a) specify learning content (in basic concepts), (b) monitor students’ learning progress (in basic concepts) and (3) enhance students’ understanding (of basic concepts). Mastering these jobs with productive teaching practices involves four orientations in particular (conceptual rather than procedural orientation, diagnostic rather than syllabus-led orientation, communicative rather than individualistic orientation, and long-term rather than short-term orientation) as well as detailed pedagogical content categories for unpacking relevant knowledge elements. The paper reports on the professional development program Mastering Math which aims at promoting this expertise and its evaluation using a pre–post-design. For 95 participating teachers, the practices for specifying goals and monitoring and enhancing at-risk students’ understanding were captured in self-reports and situated in vignette-based activities for eliciting diagnostic judgments. Teachers’ development across different aspects of their expertise from the beginning and the end of the 1-year PD reveals the first quantitative evidence that the PD was effective in promoting growth of expertise. Whereas specifying and monitoring practices had substantially developed, the enhancement practices were hindered by a persistent short-term orientation.

Evaluation of the NANDA International, Inc. diagnostic classification in Spain: Development and validation of the EVALUAN-I tool.

To develop and validate a tool to evaluate the NANDA International, Inc. diagnostic classification. The tool, EVALUAN-I, was validated in a non-probabilistic sample (N = 460) on Spanish Registered Nurses (September-December 2019) in two phases. First, design and construct the instrument in three steps: (1) literature review to define the construct focusing on the orientation toward nursing concepts and theoretical foundations, the level of scientific evidence, the structural configuration, the applicability, the nurses' clinical reasoning skills, and the attitudes toward nursing diagnosis, (2) substantiation of the questionnaire items and design according to the criteria for a diagnostic classification, (3) expert test to establish the face validity and content validity. The second phase revolved around (4) conducting a pilot test and measuring the temporal stability (test-retest) and Cohen's kappa coefficient; assessing psychometric properties by measuring (5) reliability (internal consistency using Cronbach alpha and interfactor correlation) and (6) construct validity (exploratory and confirmatory factor analysis). The manuscript follows the STROBE checklist. The study was approved by the Research Ethics Committee with registration number 2019-190-1. EVALUAN-I displayed moderate test-retest stability, adequate construct validity, and excellent reliability. The confirmatory factor analysis provided evidence about the configuration of EVALUAN-I in relation to nine analytical dimensions: clinical competence, nurses' reasoning skills, attitudes towards nursing diagnosis, discipline's central concepts, classification's contents, physiopathological attributes, level of scientific evidence, diagnostic precision, and conceptual correspondence between terminologies. EVALUAN-I is a valid and reliable instrument, which can be used to improve the epistemological, normative, and intuitive configuration of NANDA International, Inc. in a structured, systematic manner. Comprehensive evaluation of NANDA International, Inc. in different clinical settings around the world using a validated instrument, like EVALUAN-I, would allow strengths and weaknesses to be identified and contribute to the classification's development and practical application.

Diagnostic cases in pre-service teacher education: effects of text characteristics and empathy on text-based cognitive models

In teacher education, case-based learning with text-based cases is an efficient method to foster pre-service teachers’ diagnostic competence. To adaptively utilize text-based cases, knowledge about effects of text characteristics and empathy on processing text-based diagnostic information is needed, but still scarce. Our study focuses on effects of two text characteristics, text style and text subject, and of empathy on the accuracy of case-based cognitive models. We examined this experimentally. 391 pre-service teachers read a case in psycho-narrative or externally focalised style (text style) about test anxiety or dyscalculia (text subject). We measured self-reported state- and trait-empathy and assessed cognitive models with a recognition and verification test. Regression analyses showed no main effects of text characteristics, trait- and state-empathy, but moderation effects of text style and affective (but not cognitive) state-empathy. We draw implications for adaptively designing text-based cases and possible mechanisms of how empathy is involved in diagnostic judgement formation.

ADHD Symptoms and Health-Related Quality of Life of Adolescents and Young Adults

Abstract. Background: Adolescence and young adulthood present particularly challenging periods for individuals affected by attention-deficit hyperactivity disorder (ADHD) symptoms. However, unlike childhood ADHD, ADHD among adolescents and young adults has been studied less frequently. A concept that can be used to characterize the experiences of individuals with ADHD symptoms is health-related quality of life (HRQoL), which encompasses well-being in various dimensions. Aims: The present study used a school-based sample in the German-speaking part of Switzerland to investigate the association between ADHD symptoms and HRQoL of adolescents and young adults. Method: A total of 907 individuals aged 14–24 years ( M = 17.69; SD = 1.66; 58.9% female) were surveyed regarding ADHD symptoms and HRQoL. Results: Multiple hierarchical regression analyses disclosed that ADHD symptoms were negatively related to all subdimensions of HRQoL. Moreover, adolescents with clinically significant or subclinical ADHD symptoms showed lower values in all examined dimensions – physical, emotional, self-esteem, family, friends/peers, and school/education – than adolescents with unremarkable ADHD symptoms. An exception was the well-being concerning friends/peers. Limitations: The present study used a cross-sectional design and a selective sample of school classes. ADHD symptoms were assessed using self-reports without any diagnostic judgment. Conclusion: The results illustrate the comprehensive effects of ADHD symptoms on well-being during adolescence and young adulthood. They highlight the importance of focusing more on ADHD during these stages of age, also considering individuals with symptoms in the subclinical range.

Engineering judgement in undergraduate structural design education: enhancing learning with failure case studies

ABSTRACT Universities face the challenge of developing undergraduate structural engineering students' design judgement. This study evaluates whether introducing ‘learning from failure', centralised around ‘real-world' case studies, serves to facilitate the development of engineering judgement in structural design. The study identifies the use of three characteristics of engineering judgement: diagnostic, inductive, and interpretive in the work of the first-year undergraduate structural design students. Thematic analysis, combined with a constant comparison method and the rigour of inter-researcher reliability, was used to develop coding and mapping to evaluate students' work. The majority of students correctly applied diagnostic engineering judgement to the definition of a problem for a failure case study; and displayed the inductive aspect of judgement. Students' interpretive understanding embraced multi-faceted considerations, with engineering practice, complexity in causality, and learning from history being dominant. Introducing case studies deepened students’ enquiry, stimulating the development of a more nuanced understanding of structural engineering judgement.

Teachers’ diagnostic judgments on tasks as information processing – The role of pedagogical content knowledge for task diagnosis

When assessing task difficulty, teachers perceive, interpret, and integrate information about relevant features of the task by applying their topic-specific pedagogical content knowledge (PCK). These assumptions on the processes underlying diagnostic judgements on tasks have rarely been modeled and investigated systematically. In an experimental study, we assume two processes (identifying relevant task features and integrating information on multiple features) and predict the influence of PCK and available time on the accuracy of task judgments of 212 student teachers. The results support that PCK is required for both processes and that time pressure only affects the complex process of integrating information.

ТРЕХМЕРНОЕ БАЗИСНОЕ ТИПОЛОГИЧЕСКОЕ МОДЕЛИРОВАНИЕ И ИЗМЕРЕНИЕ АКЦЕНТУАЦИЙ ЛИЧНОСТИ

In the article, a three-dimensional basic typological model of personality accentuations is constructed, an appropriate author's basic test measuring accentuations is proposed, and its subsequent optimization is carried out. A basis is a set of elements that is characterized by completeness, orderliness and measurability. In the «basis» there is a single generalized dichotomy «external — internal», which in our article is projected on a separate personal dichotomy «social — individual». In «measurability» there are the following three basic characteristics: 1) a measure of information representation (image, word, number); 2) projection of information transformation (image into word, image into number, word into number). The last conversion (words to numbers) will be used here. 3) the assessment of the level of information measurement (low, medium, high, very high) will also be used by us. «Measurability» makes it possible to create basic multidimensional techniques (in our case, the creation of a basic three-dimensional test). The article shows the correspondence of the types of personality accentuations according to MMPI, with the professional typology of personality according to D. Holland and the new author's three-dimensional typology of personality temperament. The correspondence of the characteristics of the three typologies was carried out on the basis of the use of the principle of semantic proximity. A «typological isomorph» of three personality typologies was established. The reference semantic typological professional basis of personality according to D. Holland, consisting of six types («artistic», «conventional», «social», «realistic», «enterprising», «intellectual») was put on the basis of using the principle of semantic proximity to the six basic types of personality accentuations according to MMPI («hysterical», «psychopathic», «hypomanic», «depressive», «paranoid», «schizoid»). Correlations of the corresponding types from these typologies were found. In the future, a new author's basic test for measuring the types of personality accentuations by MMPI was developed, containing 24 diagnostic judgments. The constructive and criteria validity of the new test was established.

Liver tumor detection based on objects as points

The automatic detection of liver tumors by computed tomography is challenging, owing to their wide variations in size and location, as well as to their irregular shapes. Existing detection methods largely rely on two-stage detectors and use CT images marked with bounding boxes for training and detection. In this study, we propose a single-stage detector method designed to accurately detect multiple tumors simultaneously, and provide results demonstrating its increased speed and efficiency compared to prior methods. The proposed model divides CT images into multiple channels to obtain continuity information and implements a bounding box attention mechanism to overcome the limitation of inaccurate prediction of tumor center points and decrease redundant bounding boxes. The model integrates information from various channels using an effective Squeeze-and-Excitation attention module. The proposed model obtained a mean average precision result of 0.476 on the Decathlon dataset, which was superior to that of the prior methods examined for comparison. This research is expected to enable physicians to diagnose tumors very efficiently; particularly, the prediction of tumor center points is expected to enable physicians to rapidly verify their diagnostic judgments. The proposed method is considered suitable for future adoption in clinical practice in hospitals and resource-poor areas because its superior performance does not increase computational cost; hence, the equipment required is relatively inexpensive.

Cerebral autosomo-dominant arteriopathy with subcortical infarctions and leukoencephalopathy

The article presents an analysis of the literature and a clinical case of a rare disease from the group of diseases of small vessels — cerebral autosomal dominant arteriopathy with subcortical infarction and leukoencephalopathy (CADASIL).It is based on the deposition of osmiophilic granulation material in vessels of small and medium caliber. A mutation in the NOTCH3 gene on chromosome 19p13 leads to significant structural changes in the walls of small arteries due to impaired differentiation and maturation of smooth muscle cells.CADASIL is characterized by four key symptoms: migraines, recurrent ischemic strokes, mental disorders, and cognitive decline. The clinical case study is presented from the standpoint of a multidisciplinary patient-oriented approach of joint work of neurologists and morphologists. On the basis of clinical and laboratory criteria, a probable diagnosis was made. To confirm it, a muscle biopsy was performed (a musculocutaneous flap from the inner surface of the thighs and forearms), in order to conduct light and electron microscopy. The details of the results of the morphological study, which made it possible to verify the patient’s diagnosis, are presented. Differential diagnostic judgments are presented and recommendations for genetic studies in the family, prognosis and treatment of the patient are given.

Clinical Evaluation Criteria for Automatic Diagnosis of 12-lead Electrocardiograph

The automatic diagnosis function of the electrocardiograph (ECG) machine directly affects the clinical application of the device. However, there is currently no unified criteria for the evaluation of the automatic diagnosis function of the 12-lead ECG machine in clinic. We established a 12-lead ECG automatic diagnostic function clinical evaluation specification from the scope of the specification, the automatic diagnostic function judgment rules, general technical measurement requirements, test methods and conditions, and ECG data input. Emphasis is given to the judgment rules of the automatic diagnosis function, including the accuracy of ECG feature values, the interpretation and judgment of automatic diagnosis results. This specification aims to provide technical basis for the clinical evaluation for automatic diagnosis function of the 12-lead ECG.

A global field study of the international classification of diseases (ICD-11) mood disorders clinical descriptions and diagnostic guidelines

BackgroundWe report results of an internet-based field study evaluating the diagnostic guidelines for ICD-11 mood disorders. Accuracy of clinicians’ diagnostic judgments applying draft ICD-11 as compared to the ICD-10 guidelines to standardized case vignettes was assessed as well as perceived clinical utility. Methods1357 clinician members of the World Health Organization's Global Clinical Practice Network completed the study in English, Spanish, Japanese or Russian. Participants were randomly assigned to apply ICD-11 or ICD-10 guidelines to one of eleven pairs of case vignettes. ResultsClinicians using the ICD-11 and ICD-10 guidelines achieved similar levels of accuracy in diagnosing mood disorders depicted in vignettes. Those using the ICD-11 were more accurate in identifying depressive episode in recurrent depressive disorder. There were no statistically significant differences detected across classifications in the accuracy of identifying dysthymic or cyclothymic disorder. Circumscribed problems with the proposed ICD-11 guidelines were identified including difficulties differentiating bipolar type I from bipolar type II disorder and applying revised severity ratings to depressive episodes. Clinical utility of ICD-11 bipolar disorders was found to be significantly lower than for ICD-10 equivalent categories. LimitationsStandardized case vignettes were manipulated to evaluate specific changes. The degree of accuracy of clinicians’ diagnostic judgments may not reflect clinical decision-making with patients. ConclusionsAlignment of the ICD-11 with current research appears to have been achieved without sacrificing diagnostic accuracy or clinical utility though specific training may be necessary as ICD-11 is implemented worldwide. Areas in which the ICD-11 guidelines did not perform as intended resulted in further revisions.

Evaluation of laryngeal vascular changes with image1 s enhancement system in reference to the European laryngological society guideline.

To assess the feasibility of using Image1 S™ endoscopic enhancement system for discrimination of the vascular patterns in laryngeal lesions. Forty patients presenting with benign, dysplastic and malignant laryngeal lesions were examined with Image1 S system. The vascular patterns were classified by a group of authors according to the European Laryngological Society (ELS) guideline, as perpendicular or longitudinal, in all lesions. The relationship between the vascular patterns and the pathological results was statistically analysed. Endoscopic images of the lesions were evaluated through an online survey by a group of otolaryngologists with different levels of clinical expertise and asked them to choose a diagnosis and a vascular pattern. The vascular pattern evaluations of the participants were compared to the authors' evaluations to determine the interobserver reliability. The final diagnostic judgements of the participants were compared with the definitive histopathological diagnoses. Tertiary university hospital. Forty patients with laryngeal lesions and thirty otolaryngologists with different clinical experience levels. The study evaluates the usefulness of the Image1 S system for the detecting the vascular patterns associated with benign, dysplastic, and malignant lesions and measures the level of accuracy and inter observer agreement in detecting the final histopathology. Histopathological examination diagnosed 12 patients as benign, 12 dysplastic and 16 malignant. Using Image1 S, the vascular patterns were longitudinal in 11 lesions, perpendicular in 28 lesions and undetectable in 1 lesion. With white light, longitudinal pattern was observed in 14 lesions, perpendicular in 21 lesions and undetectable in 5 lesions. The correlation between the vascularisation pattern and the pathological diagnosis was found to be significant (p<.001). The qualitative evaluation of the vascular patterns by the two groups of observers showed significant reliability (κ=0.63, p<.001). The agreement with the final diagnoses was also significant (κ=0.56, p<.001). Image1 S endoscopic enhancement system with spectral modes provides an improved visibility of the vascular patterns defined by the ELS in laryngeal lesions. ELS classification can reliably distinguish benign lesions from suspected ones and can be applied even by less-experienced clinicians but the final diagnosis needs experience and should be confirmed with histopathology.