Incorrect Diagnosis Research Articles

Survey on Eczema; Its Perceptions and Characterization

Eczema (atopic dermatitis) is a common inflammatory skin disease. It causes physical discomfort and also cause stress due to constant itching, which in the end leads to painful wounds. It can be triggered by environmental, genetic, stress, and anxiety factors. The symptoms of eczema are similar to other skin disorders. In some cases, incorrect diagnosis results in the administration of medication for other skin disorders. Objectives: To understand the patients’ knowledge about the disease and to create a sense of awareness for them. Methods: We prepared a questionnaire to get sense of people's understanding about eczema and surveyed students at Punjab University as well as we collected data with help of online google forms. There were 103 responses from people of both genders, age ranges from 20 to 35 years, and different educational backgrounds. Results: Most of the people think they understand what eczema is, but they have confused it with other skin conditions. According to the responses, sudden change in surroundings is the most triggering factor in causing eczema. Only 1% of people think it could be a contact disorder and can be triggered by pets and refined carbs. The most challenging weather for eczema is winter and the time is night. Conclusions: it was concluded that eczema is a really disturbing disease. This disorder is incurable yet. However, with proper care, timely treatment, and by taking preventive measures, can prevent to flare-up.

Posterior Cruciate Ligament and Posterolateral Corner Reconstruction: Clinical Outcomes Following Popliteal Tendon Tenodesis and Popliteal Tendon Reconstruction.

Injuries to the posterolateral compartment (PLC) of the knee require special attention, as incorrect diagnosis and treatment may lead to considerable morbidity. However, no gold standard treatment has been established for PLC injuries. 38 patients with concomitant (posterior cruciate ligament (PCL) and PLC injuries were divided into two groups according to surgical treatment of the proximal popliteal tendon injury. They were treated with anatomic popliteal tendon, lateral collateral ligament (LCL), and popliteofibular ligament (PFL) reconstruction (group 1; n = 19) and were treated with popliteal tendon tenodesis, LCL, and PFL reconstruction (group 2; n = 19). The Lysholm score, dial test, and lateral compartment opening on varus stress X-ray were used as outcome measurements evaluated before surgery and at 6, 12, and 24months of follow-up. Overall, there was a progressive improvement in the Lysholm score and the lateral opening on varus stress radiography during the evaluated periods for both groups (p < 0.001). Patients from group 2 recorded better Lysholm scores than those from group 1 at 12- and 24-month follow-up (p = 0.02). Dial test was negative in all patients after 6, 12, and 24months. Patients with popliteal tendon tenodesis were found to have better Lysholm scores than patients with reconstruction after 12 and 24months of follow-up. There was no difference in the lateral joint opening evaluated by stress radiography between groups. These results show that tenodesis could be a viable treatment option for lateral femoral condyle popliteal disruptions in the context of PLC and PCL combined injuries, and should be considered in the surgical planning process.

What factors influence cellular pathologists' confidence in case reporting?

Histopathology is a challenging interpretive discipline, and the level of confidence a pathologist has in their diagnosis is known to vary, which is conveyed descriptively in pathology reports. There has been little study to accurately quantify pathologists' diagnostic confidence or the factors that influence it. In this study involving sixteen pathologists from six NHS trusts, we assessed diagnostic confidence across multiple variables and four specialties. Each case was reported by four pathologists, with each pathologist reporting each case twice (on light microscopy (LM) and digital pathology (DP)). For each diagnosis, pathologists recorded their confidence on a 7-point Likert scale. This provided 16,187 diagnoses and associated confidence scores for analysis. All variables investigated were found to be significantly predictive of diagnostic confidence, except level of pathologist experience. Confidence was lower for difficult to report cases, cases where there was inter- and intra-pathologist variation in the diagnosis, and cases where the pathologist made an incorrect diagnosis. Confidence was higher, although nominally, for LM diagnoses than DP (rate ratio 1.09 (95% CI 1.01-1.18), p = 0.035), although results indicate pathologists are confident to report on DP. Lowest confidence scores were seen in areas of known diagnostic complexity and cases with quality issues. High confidence in incorrect diagnoses were almost invariably attributed to interpretive diagnostic differences which occurred across both rare and common lesions. The results highlight the value of external quality control schemes and the benefits of selective peer review when reporting.

Nutrient Stress Symptom Detection in Cucumber Seedlings Using Segmented Regression and a Mask Region-Based Convolutional Neural Network Model

The health monitoring of vegetable and fruit plants, especially during the critical seedling growth stage, is essential to protect them from various environmental stresses and prevent yield loss. Different environmental stresses may cause similar symptoms, making visual inspection alone unreliable and potentially leading to an incorrect diagnosis and delayed corrective actions. This study aimed to address these challenges by proposing a segmented regression model and a Mask R-CNN model for detecting the initiation time and symptoms of nutrient stress in cucumber seedlings within a controlled environment. Nutrient stress was induced by applying two different treatments: an indicative nutrient deficiency with an electrical conductivity (EC) of 0 dSm−1, and excess nutrients with a high-concentration nutrient solution and an EC of 6 dSm−1. Images of the seedlings were collected using an automatic image acquisition system two weeks after germination. The early initiation of nutrient stress was detected using a segmented regression analysis, which analyzed morphological and textural features extracted from the images. For the Mask R-CNN model, 800 seedling images were annotated based on the segmented regression analysis results. Nutrient-stressed seedlings were identified from the initiation day to 4.2 days after treatment application. The Mask R-CNN model, implemented using ResNet-101 for feature extraction, leveraged transfer learning to train the network with a smaller dataset, thereby reducing the processing time. This study identifies the top projected canopy area (TPCA), energy, entropy, and homogeneity as prospective indicators of nutritional deficits in cucumber seedlings. The results from the Mask R-CNN model are promising, with the best-fit image achieving an F1 score of 93.4%, a precision of 93%, and a recall of 94%. These findings demonstrate the effectiveness of the integrated statistical and machine learning (ML) methods for the early and accurate diagnosis of nutrient stress. The use of segmented regression for initial detection, followed by the Mask R-CNN for precise identification, emphasizes the potential of this approach to enhance agricultural practices. By facilitating the early detection and accurate diagnosis of nutrient stress, this approach allows for quicker and more precise treatments, which improve crop health and productivity. Future research could expand this methodology to other crop types and field conditions to enhance image processing techniques, and researchers may also integrate real-time monitoring systems.

Diagnostic challenge of cutis Verticis Gyrata (CVG) in a patient presenting clinical features of Noonan or turner syndrome

Cutis Verticis Gyrata (CVG) is an uncommon condition, often classified as primary (idiopathic) or secondary to other diseases or syndromes. Its pathogenesis remains poorly understood, and its association with genetic syndromes is particularly rare. Noonan and Turner syndromes are distinct genetic disorders with characteristic phenotypes and multiple systemic involvements. This report aims to highlight the diagnostic complexities when CVG presents in the backdrop of these syndromes. A 38 years old patient was presented with chief complaints of receding hairline, dropping eyelids, cerebral deformations with deep furrows and thickened dermis. On the basis of patient's complaints, Noonan or turner syndrome was considered as possible diagnosis. This particular report presents a case of patient suffering from CVG having history of noonan and turner syndrome. With the detailed MRI, histology etc. CVG was finally confirmed. The novelty of this case lies in its rarity, diagnostic complexity, and the need for a multidisciplinary approach to unravel and manage the intersecting conditions. It contributes valuable insights to the existing medical literature, enhancing our understanding of the interplay between dermatological and genetic conditions. Patients with Noonan and turner syndrome exhibit clinical signs and symptoms that are strikingly similar to those of CVG, suggesting that this presents a significant diagnostic problem. An unfavorable outcome could arise from delayed or incorrect diagnosis. Because of this, it is recommended that healthcare fraternities should include uncommon illnesses like CVG as differential diagnosis. Considering CVG in differential diagnosis is crucial for early identification, accurate diagnosis, and comprehensive management. It ensures that associated systemic and genetic conditions are not overlooked and that patients receive holistic and personalized care.

Timing of onset of intraoperative transfusion anaphylaxis: a literature review.

Clinical diagnosis of intraoperative transfusion anaphylaxis using clinical symptoms is challenging and should be made carefully, as an incorrect clinical diagnosis can exacerbate surgical bleeding secondary to stopping a clinically indicated blood transfusion. The timing of onset of anaphylaxis to start of transfusion may be the key to correctly diagnosing intraoperative transfusion anaphylaxis clinically. However, the reliability of this measure remains unknown. A literature search was conducted using MEDLINE, Embase, the Cochrane Database of Systematic Reviews, and the Cochrane Central Register of Controlled Trials up to June 29, 2021. No language restriction was applied. Two pairs of review authors independently reviewed intraoperative transfusion anaphylaxis cases and extracted data on the timing of onset of anaphylaxis to start of transfusion. A total of 8,918 articles were reviewed, the full texts of 186 articles were assessed, and 20 intraoperative transfusion anaphylaxis cases were included in this study. The 20 intraoperative transfusion anaphylaxis cases included a precise timing of onset. With nine cases, cardiovascular surgery was the most prevalent, and one case was fatal. Fifteen cases had a timing of onset in minutes, and of those, 14 reported timeframes within 30 minutes of initiation of transfusion (median: 15.5, 5-30 minutes). Almost all cases of intraoperative transfusion anaphylaxis occurred within 30 minutes of the transfusion initiation. This timeframe may be helpful in the clinical diagnosis of intraoperative transfusion anaphylaxis.

Enhancing cardiovascular risk assessment with advanced data balancing and domain knowledge-driven explainability

In medical risk prediction, such as predicting heart disease, machine learning (ML) classifiers must achieve high accuracy, precision, and recall to minimize the chances of incorrect diagnoses or treatment recommendations. However, real-world datasets often have imbalanced data, which can affect classifier performance. Traditional data balancing methods can lead to overfitting and underfitting, making it difficult to identify potential health risks accurately. Early prediction of heart attacks is of paramount importance, and researchers have developed ML-based systems to address this problem. However, much of the existing ML research is based on a single dataset, often ignoring performance evaluation across multiple datasets. As the demand for interpretable ML models grows, model interpretability becomes central to revealing insights and feature effects within predictive models. To address these challenges, we present a novel data balancing technique that uses a divide-and-conquer strategy with the K-Means clustering algorithm to segment the dataset. The performance of our approach is highlighted through comparisons with established techniques, which demonstrate the superiority of our proposed method. To address the challenge of inter-dataset discrepancies, we use two different datasets. Our holistic pipeline, strengthened by the innovative balancing technique, effectively addresses performance discrepancies, culminating in a significant improvement from 81% to 90%. Furthermore, through advanced statistical analysis, it has been determined that the 95% confidence interval for the AUC metric of our method ranges from 0.8187 to 0.8411. This observation serves to underscore the consistency and reliability of our approach, demonstrating its ability to achieve high performance across a range of scenarios. Incorporating Explainable AI (XAI), we examine the feature rankings and their contributions within the best performing Random Forest model. While the domain expert feedback is consistent with the explanatory power of XAI, some differences remain. Nevertheless, a remarkable convergence in feature ranking and weighting is observed, bridging the insights from XAI tools and domain expert perspectives.

Kista Dentigerus

One of the abnormalities in the mouth that is often found in practice is cysts. Dentigerous cysts are the most common odontogenic cysts and represent approximately 20% of all cysts surrounded by epithelium that can affect the maxillary bone. Local factors causing dentigerous cysts can be related to the development of the crown or permanent tooth and can also arise from residual enamel epithelium. Patients usually show no symptoms or are asymptomatic, so these cysts are discovered accidentally during routine dental radiology examinations. However, pain may be experienced when bone expansion or resorption of adjacent teeth occurs. The goal of treatment for dentigerous cysts is to eliminate pathological abnormalities and preserve the tooth with minimal surgical intervention. The surgical technique in patients with dentigerous cysts is enucleation and marsupialization. Complications after surgery cannot be avoided in the form of paresthesia and the appearance of scars around the incision area. The prognosis after treatment is mostly excellent, and recurrence of dentigerous cysts is very rare. However, if a cystic lesion recurs, it could be the result of incomplete removal of the cyst or incorrect diagnosis of the lesion.

Managing Pediatric Burns: A Case Report of Fecal Scalding

Scald burns occur when the skin encounters hot liquid or steam. Although most scald burns are accidental, the medical provider must assess for possible abuse. We report a case of a 2-year-old female who presented to the hospital with her parents due to a burn to the buttocks with a history of stool expelling from the anus and becoming trapped against the skin. Medical providers need to consider accidental and inflicted differentials, as accidental injuries do occur in children, and an incorrect diagnosis may have severe medicolegal consequences.

MRI features of combined hepatocellular-cholangiocarcinoma.

Combined hepatocellular cholangiocarcinoma (cHCC-CCA) is a rare liver tumor which has a more aggressive behavior and worse survival outcome than hepatocellular carcinoma (HCC), with a prognosis similar to that of intrahepatic cholangiocarcinoma (iCCA). With limited literature on the appearance of this tumor on MRI, it remains a diagnostic challenge. In this review, we looked at the currently described MRI findings in this uncommon entity. Based on studies conducted to date, a mixed pattern at imaging has demonstrated the highest specificity, seen as a combination of areas showing progressive enhancement of the lesion, arterial enhancement with washout, and areas of arterial enhancement without washout and/or hypovascularity. Tumor markers may aid in identification, particularly in cases where the imaging appearance mimics that of isolated HCC or iCCA. Intratumoral heterogeneity leads to difficulties with pathologic diagnosis from sampling due to the possibility of an incorrect diagnosis if the biopsy specimen does not contain adequate tissue comprising both histologic components.

A two-stage image enhancement and dynamic feature aggregation framework for gastroscopy image segmentation

Accurate and reliable automatic segmentation of lesion areas in gastroscopy images can assist endoscopists in making diagnoses and reduce the possibility of missed or incorrect diagnoses. This paper presents a two-stage framework for segmenting gastroscopy images, which aims to improve the accuracy of medical image segmentation tasks using limited datasets. The proposed framework consists of two stages: the Image Enhancement Stage and the Lesion Segmentation Stage. First, in the Image Enhancement Stage, an image enhancement solution called TDC-Enhance is proposed to enrich the original small-scale gastroscopy image dataset. This solution performs Texture Enhancement, Detail Enhancement, and Color Enhancement on the original images. Then, in the Lesion Segmentation Stage, a multi-path automatic segmentation network for gastroscopy images, named DynaSiam, is introduced. DynaSiam comprises a Dependent Encoder, a Shared Encoder, and a Fusion Decoder. It learns feature information related to the lesion region by encoding the different enhanced images obtained in the Image Enhancement Stage as inputs to the multi-path network. Additionally, a Dynamic Feature Interaction (DFI) block is designed to capture and learn deeper image information, thereby improving the segmentation performance of the model. The experimental results show that the proposed method achieves a 90.80% mIoU, 92.71% Dice coefficient and 96.31% Accuracy. Other performance metrics also indicate the best performance, suggesting that the proposed model has significant potential for clinical analysis and diagnosis. Code and implementation details can be found on GitHub: https://github.com/kyasulee/DynaSiam.

Fatigue fracture of the second rib in a professional athlete

A fatigue fracture, also known as stress fracture or overuse fracture, is caused by the summation of micro-injuries resulting from a chronic state of bone overload. It affects 1.4 %- 4.4 % of professional athletes. The most common site of fatigue fractures are the lower limbs. This is related to the heavy load caused by body weight and performing dynamic activities like jumping, running. Typical fractures are fractures of the fifth metatarsal bone, fibula and tibia, and less common fractures of the femur. Fractures involving the bones of the upper limbs and thorax are less commonly reported in the literature. It affect athletes in strength sports and athletes who perform dynamic and repetitive movements with their upper limbs, most often boxers, weightlifters, wrestlers, judokas, swimmers, golfers, rowers. Fractures in the thorax most often involve the first rib. Fractures of ribs II through XII are extremely rarely described. We present an unusual case of a second rib fracture in a professional athlete. A 26-year-old athlete training in racewalking reported increasing pain in the left scapula area 7 days before competing in the European Championships. Immediately after the competition, the pain changed location to the anterior thorax area, making movement of the upper limb and breathing much more difficult. A chest tomography was performed and it revealed a fatigue fracture of the second rib on the left side. The case report presents an atypical fracture in a female racewalking athlete and presents the uncharacteristic symptoms accompanying this fracture. Incorrect initial diagnosis and application of physiotherapy procedures without performing basic diagnostic tests, delay the diagnosis and initiation of proper treatment, and thus the athlete's recovery.

Misdiagnosis Based on Neoplastic Markers-Extremely High Alpha-Fetoprotein in Patients with Intrahepatic Cholangiocarcinoma with Literature Review of the Published Cases.

Background: Alpha-fetoprotein (AFP) and carbohydrate antigen 19-9 (CA 19-9) are two tumor markers that are widely used in the differential diagnosis in patients with primary liver tumors. Very high levels of AFP are sporadically observed in patients with intrahepatic cholangiocarcinoma (ICC) and may cause an incorrect initial diagnosis of hepatocellular carcinoma (HCC). Methods: Two cases of tumors in cirrhotic livers were described, in which the initial diagnosis, based on very high AFP levels (Patient I: 10,464 ng/mL, Patient II: 2212 ng/mL, reference range: ≤8.04 ng/mL) was HCC. In addition, the PubMed database was searched for cases of ICC with elevated AFP. Discussion: In both individuals, liver cirrhosis was diagnosed, but there was no typical rapid "washout" in the contrast-enhanced computed tomography. Based on the histological assessment of samples obtained in the core biopsies, the initially assumed diagnosis of HCC was changed to ICC in both cases. Only nine cases of patients with ICC and high AFP levels were found in the PubMed database. The AFP levels ranged from slightly elevated to over 16,000 ng/mL. Conclusions: A very high AFP level does not necessarily correlate with the presence of HCC. Therefore, the diagnosis has to be verified histologically, when the radiological imaging is uncertain in patients with liver cirrhosis.

External Quality Assessment (EQA) scheme for serological diagnostic test for SARS-CoV-2 detection in Sicily Region (Italy), in the period 2020-2022.

Since December 2019, worldwide public health has been exposed to a severe acute respiratory syndrome caused by Coronavirus-2. Serological testing is necessary for retrospective assessment of seroprevalence rates, and the determination of vaccine response and duration of immunity. For this reason, it was necessary to introduce a panel of tests able to identify and quantify Covid-19 antibodies. As a Regional Reference Centre, the CRQ Laboratory (Regional Laboratory for the Quality Control) developed and conducted an External Quality Assessment (EQA) panel of assays, to evaluate the quality of various methods, that were used by 288 Sicilian laboratories, previously authorized on behalf of the Public Health Service. The performance test was based on pooled samples with different levels of concentration of antibodies. 97 , 98, and 95 % of the participating laboratories tested all samples correctly in 2020, 2021, and 2022 respectively. The best performance was observed in the test of total Ig. The general performance of laboratories improved over the years. The incorrect diagnosis had and could still have important implications on vaccination cycles. Only through the effort of laboratory professionals, and the extension of the EQA scheme, a better harmonization of methods, protocols, and thus results, to guarantee a better healthcare system, will be possible.

Classification of Diabetic Retinopathy Severity Using Deep Learning Techniques on Retinal Images

In order to diagnose DR by utilizing the grayscale intensity and texture information extracted from the fundus image, deep learning approach is used. The writers came up with the strategy on their own. The APTOS 2019 Blindness Detection (APTOS 2019 BD) dataset is employed. extensively during the course of this investigation. A method powered by deep learning was used to locate and recover the photos. We use a large number of image processing methods, as well as two ways to feature extraction, and one method for feature selection. Because of this, the F-measure is 92.3% (0.5%), and the classification accuracy is 93.2% (with an error margin of 0.32%). Durability and dependability of the approach that was proposed have been shown by performance-related criteria for the operation. There is a possibility that classification performance might be improved using a weighted ensemble model that makes use referring to the models EfficientNet-B0, B5, and B7.This research highlights the need of extra diagnostic procedures being performed by medical experts in order to avoid incorrect diagnoses as well as false positives.

Chronic Pain and Joint Hypermobility: A Brief Diagnostic Review for Clinicians and the Potential Application of Infrared Thermography in Screening Hypermobile Inflamed Joints.

Joint hypermobility syndromes, particularly chronic pain associated with this condition, including Hypermobile Ehlers-Danlos Syndrome (hEDS) and Hypermobility Spectrum Disorders (HSD), present diagnostic challenges due to their multifactorial origins and remain poorly understood from biomechanical and genomic-molecular perspectives. Recent diagnostic guidelines have differentiated hEDS, HSD, and benign joint hypermobility, providing a more objective diagnostic framework. However, incorrect diagnoses and underdiagnoses persist, leading to prolonged journeys for affected individuals. Musculoskeletal manifestations, chronic pain, dysautonomia, and gastrointestinal symptoms illustrate the multifactorial impact of these conditions, affecting both the physical and emotional well-being of affected individuals. Infrared thermography (IRT) emerges as a promising tool for joint assessment, especially in detecting inflammatory processes. Thermal distribution patterns offer valuable insights into joint dysfunctions, although the direct correlation between pain and inflammation remains challenging. The prevalence of neuropathies among hypermobile individuals accentuates the discordance between pain perception and thermographic findings, further complicating diagnosis and management. Despite its potential, the clinical integration of IRT faces challenges, with conflicting evidence hindering its adoption. However, studies demonstrate objective temperature disparities between healthy and diseased joints, especially under dynamic thermography, suggesting its potential utility in clinical practice. Future research focused on refining diagnostic criteria and elucidating the underlying mechanisms of hypermobility syndromes will be essential to improve diagnostic accuracy and enhance patient care in this complex and multidimensional context.

Knowledge correction and [formula omitted]-insensitive criterion-leveraged zero-order TSK fuzzy system for rice leaf disease diagnosis

The advent of complex application scenarios introduces new challenges for diagnosing rice leaf diseases using machine learning methods. Two critical requirements are identified: 1) The model must exhibit high interpretability to mitigate the adverse effects of incorrect diagnoses; and 2) practical applications often suffer from insufficient samples and noise in rice leaf disease datasets, which requires the model to have strong generalization ability and robustness. However, existing methods still have certain limitations in practical scenarios due to a lack of comprehensive consideration of interpretability, generalization ability, and robustness. To address this issue, this article proposes a novel knowledge correction and ε-insensitive criterion-leveraged zero-order TSK fuzzy system (0-TSK-FS), named KE-0-TSK-FS. The KE-0-TSK-FS method is developed with 0-TSK-FS as the baseline, enhancing the generalization ability of the model by introducing the knowledge correction method and its iterative learning strategy to extract more information from limited samples. In addition, the objective function based on the ε-insensitive criterion makes KE-0-TSK-FS exhibit robustness when the samples contain noise. On three rice leaf disease datasets and six real-world non-rice leaf disease datasets, experiments were conducted on three metrics, namely accuracy, GM, and rule complexity. The experimental results show that the KE-0-TSK-FS method outperforms other comparative algorithms in terms of generalization ability, interpretability, and robustness in the diagnosis of rice leaf diseases under insufficient samples and noise situations, and its average accuracy on rice leaf disease datasets is nearly 3% higher than that of other comparative algorithms.

Radiographic Errors in Intraoral Periapical Radiographs

Background: Radiographs are considered as pivotal aid in the diagnosis and treatment planning of various Oro-dental pathologies. Changes in the quality of radiographs may lead to misinterpretation, which results in incorrect diagnosis and treatment planning. The technical and processing errors can largely influence the radiographic interpretation. Both paralleling and bisecting angle techniques can have both technical and manual errors. Aims: To estimate the frequency of radiographical errors in conventional radiographs taken by undergraduate dental students. Materials And Method: Thousand (1000) dental radiographs taken by undergraduate students were examined. Patient's age ranged between 5 -75 years. X- ray films were examined on X-ray film viewer and were classified according to type of errors and anatomical distribution. Results: The study aimed to identify common faults encountered during routine radiography. The most frequently observed error was Improper Vertical Angulation. Interns performed better in obtaining radiographs compared to Final year students. Keywords: Radiographic errors, Dental students, Bisecting angle technique.

Intraoperative frozen section evaluation of ovarian sex cord-stromal tumours and their mimics: a study of 121 cases with emphasis on potential diagnostic pitfalls

Ovarian sex cord-stromal tumours (SCSTs) present diagnostic difficulties during frozen section (FS) consultations due to their diverse morphology. This study aimed to evaluate the accuracy of FS evaluation of SCSTs in our institution, as well as to examine the reasons leading to incorrect FS diagnosis. Cases mimicking SCSTs and diagnosed as such during FS were also highlighted. We analysed 121 ovarian SCST cases and their mimics which underwent FS consultations over a 10-year period, to evaluate FS accuracy, reasons for deferrals and discrepancies. FS diagnoses were concordant, deferred and discrepant compared to the final diagnosis in 50 (41.3%), 39 (32.2%) and 32 (26.5%) cases, respectively. Major discrepancies (9/121, 7.4%) were mostly related to the diagnosis of adult granulosa cell tumour (AGCT). A fibromatous AGCT was misinterpreted as fibroma on FS, while a cystic AGCT was called a benign cyst. Conversely, a mesonephric-like adenocarcinoma, a sertoliform endometrioid carcinoma and a thecoma were misinterpreted as AGCT on FS. Another discrepant case was a Krukenberg tumour with prominent fibromatous stroma in which malignant signet ring cells were overlooked and misinterpreted as fibroma. Minor discrepancies were primarily associated with fibroma (21/23, 91.3%), wherein minor but potentially impactful details such as cellular fibroma and mitotically active cellular fibroma were missed due to sampling issues and misinterpretation as leiomyoma. FS evaluation for ovarian SCSTs demonstrated an overall accuracy of 78.5%, 81.0% and 81.8% for benign, uncertain/low malignant potential and malignant categories, respectively. There was no FS-related adverse clinical impact in all cases with available follow-up information (120/121 cases). Intraoperative FS evaluation of ovarian SCSTs is challenging. A small number of cases were misinterpreted, with AGCTs being the primary group where errors occur. Awareness of common diagnostic pitfalls and difficulties, alongside application of a stepwise approach, including (1) obtaining comprehensive clinical information, (2) thorough macroscopic examination and directed sampling, (3) meticulous microscopic examination with consideration of pitfalls and mimics, (4) effective communication with surgeons in difficult cases, and (5) consultation of subspecialty colleagues in challenging cases, will enhance pathologists' reporting accuracy and management of such cases in the future.

РАННЯЯ ДИАГНОСТИКА МИОДИСТРОФИИ ДЮШЕННА: АКТУАЛЬНОСТЬ, ПРОБЛЕМЫ, ВОЗМОЖНОСТИ И ПЕРСПЕКТИВЫ

Duchenne muscular dystrophy (DMD) is an orphan neuromuscular progressive genetic disease that causes muscle breakdown and subsequent loss. Provided early diagnosis, complex standard and pathogenetic therapy significantly changes the trajectory of the disease, making it more benign. Diagnosis of DMD is a two-pillar system with creatine kinase (CK) level measured at the first stage followed by molecular genetic study in case the enzyme threshold values. The quality of genetic diagnostics in Russia has reached the best worldwide standards recently though identifying children with elevated CK levels is yet difficult. The number of diagnosed DMD patients in Russia is significantly lower than the statistically estimated global amount. The average age for diagnosis is not decreasing either. Thus, the median age for DMD and Becker muscular dystrophy (BMD) molecular diagnosis is 7 years and 8 months old. The number of identified children below the age of 2 y/o in Russia has remained consistently low over the past three years. According to the results of a familial cases survey, the correct primary diagnosis of DMD was established in less than half of all cases, 47.1%. The most common incorrect diagnoses were as follows: asymptotic hepatitis (25.1%), perinatal damage to the central nervous system (6.4%), cerebral palsy (2.7%), autism spectrum disorder (ASD) (2.7%) and flat feet, hallux valgus etc. (16% in total). The median duration between the initial DMD manifestation and molecular diagnosis is 3 years and 8 months as yet whilst the age-specific guidelines suggest prescribing standard and pathogenetic therapy during the 2 to 5 y/o period of life. Therefore, the Russia’s average age of DMD diagnosis above 7 y/o lies far beyond the optimal age for initiating of the DMD therapy with the purpose of gaining its maximum possible clinical benefit. The accumulated international and Russian experience demonstrates the possibility for improving of the primary DMD and BMD diagnosis in early preschool age and therefore requires its nationwide introduction.