Design and evaluation of an anthropomorphic neck phantom for improved ultrasound diagnostics of thyroid gland tumors.

PURPOSE: Thyroid cancer is one of the most common cancers worldwide, with ultrasound-guided biopsy being the method of choice for its early detection. The accuracy of diagnostics directly depends on the qualifications of the ultrasonographers, whose performance can be enhanced through training with phantoms. The aim of this study is to propose a reproducible methodology for designing a neck phantom for ultrasound training and research from widely available materials and to validate its applicability. METHODS: The phantom was made using polyvinyl chloride mixed with additives to reproduce different levels of brightness on ultrasound screens. 3D printing and casting were used to create the neck model and various structures of the neck, including bones, cartilage, arteries, veins, lymph nodes, thyroid gland, and soft tissues. The small objects, such as tumor and lymph node models, were shaped manually. All the phantom's materials were carefully selected to match the ultrasonic speed and attenuation values of real soft tissues and bones. RESULTS: The thyroid gland contains models of a cancerous and cystic nodule. In the neck, there are models of carotid arteries and jugular veins filled with ultrasound-transparent gel. Additionally, there are replicas of lymph nodes and bone structures such as hyoid bone, thyroid cartilage, trachea, and vertebrae. The resulting phantom covers the entire neck area and has been positively received by practicing ultrasound specialists. CONCLUSIONS: The proposed manufacturing technology offers a reliable and cost-effective approach to produce an anthropomorphic neck phantom for ultrasound diagnosis of the thyroid gland. The realistic simulation provided by the phantom enhances the quality and accuracy of ultrasound examinations, contributing to better training for medical professionals and improved patient care. Subsequent research efforts can concentrate on refining the fabrication process and exploring additional features to enhance the phantom's capabilities.

B-Mode ultrasound imaging in diagnosing carpal tunnel syndrome: an auxiliary diagnostic tool for hand surgeons.

Objective: The purpose of this article is to explore the effectiveness of B-Mode ultrasound as an auxiliary diagnostic tool for carpal tunnel syndrome (CTS). It aims to demonstrate the advantages of B-Mode ultrasound, including its non-invasive nature and its ability to provide real-time imaging, in localizing nerve compression and predicting postoperative outcomes. Methods: The study included 40 patients who were subjected to preoperative B-ultrasonography. The approach focused on evaluating the consistency of B-Mode ultrasound results with intraoperative findings. It also assessed the importance of employing standardized imaging techniques and emphasized the need for cooperation between hand surgeons and sonographers for accurate diagnosis. Results: B-Mode ultrasound findings in the study were consistent with intraoperative observations, indicating its reliability. Additionally, B-Mode ultrasound was able to identify other anatomical abnormalities within the carpal canal that may contribute to CTS symptoms, such as persistent median arteries, median nerve bifurcation, and space-occupying lesions like cysts and tumors. Conclusion: The article concludes that B-Mode ultrasound should be considered a valuable supplementary diagnostic tool for CTS, particularly in instances where clinical signs and electrophysiological studies do not offer clear results. However, it should not replace established diagnostic methods for CTS.

Intramuscular Dissecting Baker's Cysts: A Case Series Highlighting Ultrasound Diagnosis and Differential Considerations.

Baker's cysts, commonly incidental findings, can occasionally present as intramuscular dissecting cysts within the medial gastrocnemius muscle. This case report highlights the ultrasound features and differential diagnoses of intramuscular dissecting Baker's cysts through the examination of three distinct cases: a 64-year-old woman with severe osteoarthritis, an 80-year-old man with a palpable mass in the popliteal fossa, and a 37-year-old man with early degenerative arthropathy. Each case was investigated using ultrasound, revealing fusiform hypoechoic fluid collections with heterogeneous echostructure parallel to the medial gastrocnemius muscle bundle and lacking posterior reinforcement. The clinical context and ultrasound findings were critical in differentiating these cases from other conditions, such as superficial thrombophlebitis, intramuscular seroma, and intramuscular myxoma. These cases emphasize the role of ultrasound in diagnosing intramuscular dissecting Baker's cysts. Accurate diagnosis requires careful consideration of ultrasound features in conjunction with clinical findings.

Granulomatous orchitis: A case report of misdiagnosis and review of the literature.

Granulomatous orchitis is a relatively rare clinical testicular lesion. The imaging manifestations and clinical symptoms are similar to those of testicular tumors. In order to improve the understanding of this disease, this article reports the ultrasonographic manifestations of a case of granulomatous orchitis and reviews the relevant literature with.

Comparative diagnostic accuracy of the IOTA SRR and LR2 scoring systems for discriminating between malignant and Benign Adnexal masses by junior physicians in Chinese patients: a retrospective observational study.

BACKGROUND: The accuracy of ultrasound in distinguishing benign from malignant adnexal masses is highly correlated with the experience of ultrasound physicians. In China, most of ultrasound differentiation is done by junior physicians. PURPOSE: To compare the diagnostic performance of the International Ovarian Tumour Analysis (IOTA) Simple Rules Risk (SRR) and IOTA Logistic Regression Model 2 (LR2) scoring systems in Chinese patients with adnexal masses. METHODS: Retrospective analysis of ovarian cancer tumor patients who underwent surgery at a hospital in China from January 2016 to December 2021. Screening patients with at least one adnexal mass on inclusion and exclusion criteria. Two trained junior physicians evaluated each mass using the two scoring systems. A receiver operating characteristic curve was used to test the diagnostic performance of each system. RESULTS: A total of 144 adnexal masses were retrospectively collected. Forty masses were histologically diagnosed as malignant. Compared with premenopausal women, postmenopausal women had a much higher rate of malignant masses. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) of the SRR was 97.5% (95% CI: 86.8 -99.9%), 82.7% (95% CI: 74.0 -89.4%), 68.4% (95% CI: 58.7 -76.8%) and 98.9% (95% CI: 92.5 -99.8%). The sensitivity, specificity, PPV, NPV of the LR2 were 90.0% (95% CI: 76.5 -97.2%), 89.4% (95% CI: 81.9 -94.6%), 76.6% (95% CI: 65.0 -85.2%), and 95.9% (95% CI: 90.2 -98.3%). There was good agreement between two scoring systems, with 84.03% total agreement and a kappa value of 0.783 (95% CI: 0.70-0.864). The areas under the curve for predicting malignant tumours using SRR and LR2 were similar for all patients (P > 0.05 ). CONCLUSION: The two scoring systems can effectively distinguish benign from malignant adnexal masses. Both scoring systems have high diagnostic efficacy, and diagnostic efficacy is stable, which can provide an important reference for clinical decision making.

A deep learning model for the differential diagnosis of benign and malignant salivary gland tumors based on ultrasound imaging and clinical data.

Background: The preoperative differentiation between benign parotid gland tumors (BPGTs) and malignant parotid gland tumors (MPGTs) is of great significance for therapeutic decision-making. Deep learning (DL), an artificial intelligence algorithm based on neural networks, can help overcome inconsistencies in conventional ultrasonic (CUS) examination outcomes. Therefore, as an auxiliary diagnostic tool, DL can support accurate diagnosis using massive ultrasonic (US) images. This current study developed and validated a DL-based US diagnosis for the preoperative differentiation of BPGT from MPGT. Methods: A total of 266 patients, including 178 patients with BPGT and 88 patients with MPGT, were consecutively identified from a pathology database and enrolled in this study. Ultimately, considering the limitations of the DL model, 173 patients were selected from the 266 patients and divided into 2 groups: a training set, and a testing set. US images of the 173 patients were used to construct the training set (including 66 benign and 66 malignant PGTs) and testing set (consisting of 21 benign and 20 malignant PGTs). These were then preprocessed by normalizing the grayscale of each image and reducing noise. Processed images were imported into the DL model, which was then trained to predict the images from the testing set and evaluated for performance. Based on the training and validation datasets, the diagnostic performance of the 3 models was assessed and verified using receiver operating characteristic (ROC) curves. Ultimately, before and after combining the clinical data, we compared the area under the curve (AUC) and diagnostic accuracy of the DL model with the opinions of trained radiologists to evaluate the application value of the DL model in US diagnosis. Results: The DL model showed a significantly higher AUC value compared to doctor 1 + clinical data, doctor 2 + clinical data, and doctor 3 + clinical data (AUC =0.9583 vs. 0.6250, 0.7250, and 0.8025 respectively; all P<0.05). In addition, the sensitivity of the DL model was higher than the sensitivities of the doctors combined with clinical data (97.2% vs. 65%, 80%, and 90% for doctor 1 + clinical data, doctor 2 + clinical data, and doctor 3 + clinical data, respectively; all P<0.05). Conclusions: The DL-based US imaging diagnostic model has excellent performance in differentiating BPGT from MPGT, supporting its value as a diagnostic tool for the clinical decision-making process.

Study on diagnosis of thyroid nodules based on convolutional neural network.

OBJECTIVE: An artificial intelligence (AI) algorithm based on convolutional neural networks was used in ultrasound diagnosis in order to evaluate its performance in judging the nature of thyroid nodules and nodule classification. METHODS: A total of 105 patients with thyroid nodules confirmed by surgery or biopsy were retrospectively analyzed. The properties, characteristics, and classification of thyroid nodules were evaluated by sonographers and by AI to obtain combined diagnoses. Receiver operating characteristic curves were generated to evaluate the performance of AI, the sonographer, and their combined effort in diagnosing the nature of thyroid nodules and classifying their characteristics. In the diagnosis of thyroid nodules with solid components, hypoechoic appearance, indistinct borders, Anteroposterior/transverse diameter ratio > 1(A/T > 1), and calcification performed by sonographers and by AI, the properties exhibited statistically significant differences. RESULTS: Sonographers had a sensitivity of 80.7%, specificity of 73.7%, accuracy of 79.0%, and area under the curve (AUC) of 0.751 in the diagnosis of benign and malignant thyroid nodules. AI had a sensitivity of 84.5%, specificity of 81.0%, accuracy of 84.7%, and AUC of 0.803. The combined AI and sonographer diagnosis had a sensitivity of 92.1%, specificity of 86.3%, accuracy of 91.7%, and AUC of 0.910. CONCLUSION: The efficacy of a combined diagnosis for benign and malignant thyroid nodules is higher than that of an AI-based diagnosis alone or a sonographer-based diagnosis alone. The combined diagnosis can reduce unnecessary fine-needle aspiration biopsy procedures and better evaluate the necessity of surgery in clinical practice.

Differential Diagnosis of DCIS and Fibroadenoma Based on Ultrasound Images: a Difference-Based Self-Supervised Approach.

Differentiation of ductal carcinoma in situ (DCIS, a precancerous lesion of the breast) from fibroadenoma (FA) using ultrasonography is significant for the early prevention of malignant breast tumors. Radiomics-based artificial intelligence (AI) can provide additional diagnostic information but usually requires extensive labeling efforts by clinicians with specialized knowledge. This study aims to investigate the feasibility of differentially diagnosing DCIS and FA using ultrasound radiomics-based AI techniques and further explore a novel approach that can reduce labeling efforts without sacrificing diagnostic performance. We included 461 DCIS and 651 FA patients, of whom 139 DCIS and 181 FA patients constituted a prospective test cohort. First, various feature engineering-based machine learning (FEML) and deep learning (DL) approaches were developed. Then, we designed a difference-based self-supervised (DSS) learning approach that only required FA samples to participate in training. The DSS approach consists of three steps: (1) pretraining a Bootstrap Your Own Latent (BYOL) model using FA images, (2) reconstructing images using the encoder and decoder of the pretrained model, and (3) distinguishing DCIS from FA based on the differences between the original and reconstructed images. The experimental results showed that the trained FEML and DL models achieved the highest AUC of 0.7935 (95% confidence interval, 0.7900-0.7969) on the prospective test cohort, indicating that the developed models are effective for assisting in differentiating DCIS from FA based on ultrasound images. Furthermore, the DSS model achieved an AUC of 0.8172 (95% confidence interval, 0.8124-0.8219), indicating that our model outperforms the conventional radiomics-based AI models and is more competitive.

Fetal hydrometrocolpos: Challenges of prenatal differential diagnosis on ultrasound.

Hydrometrocolpos is a pelvic cystic mass representing the distension of the vagina and uterus due to a lower genital tract obstruction causing accumulation of utero-cervical-vaginal secretions or urine in the vagina and endometrial cavity. Prenatal diagnosis is uncommon and differential diagnosis of the underlying etiologies is quite challenging in the prenatal period. We present three cases of female fetuses with hydrometrocolpos and discuss the prenatal differential diagnoses in the light of ultrasound findings along with postnatal diagnoses and outcomes.

Heterotopic Interstitial Pregnancy: Early Ultrasound Diagnosis of 179 Cases After In Vitro Fertilization-Embryo Transfer.

OBJECTIVES: What is the role of transvaginal sonography (TVS) in the early diagnosis of hectopic interstitial pregnancy (HIP) after in vitro fertilization-embryo transfer (IVF-ET)? METHODS: A retrospective observational study was conducted from January 2005 to December 2018. Routine two-dimensional and three-dimensional TVS were used to confirm clinical pregnancy. Women were diagnosed with HIP when an intrauterine gestational sac was combined with an extrauterine chorionic sac, which was at least 1 cm away from the uterine cavity and surrounded by a thin myometrial layer (<5 mm). Surgery and pathology results were the gold standard for diagnosing interstitial pregnancy. Non-surgical patients were excluded from the study. The performance of TVS and the pregnancy outcomes of intrauterine pregnancies (IUPs) were evaluated. RESULTS: A total of 97,161 women underwent IVF treatment and TVS examinations in our hospital during this study. Of these, 194 patients were diagnosed with HIP, with an incidence of 0.2% (194/97,161). Surgical and pathological findings confirmed 179 interstitial pregnancies, of which 174 were diagnosed by TVS, 4 were missed, and 1 was misdiagnosed. The sensitivity of TVS diagnosis was 97.8% and the positive predictive value was 99.4%. The mean time to diagnosis was 31 days after transplantation. One hundred and thirty-nine cases of HIP (77.7%) were diagnosed at the time of initial TVS examination. In 132 patients (73.7%), IUPs resulted in live births. CONCLUSIONS: In our practice, most HIPs following IVF-ET can be accurately diagnosed by TVS, which facilitates early management of interstitial pregnancies and enables high live birth rates for IUPs.

Automatic ovarian tumors recognition system based on ensemble convolutional neural network with ultrasound imaging.

BACKGROUND: Upon the discovery of ovarian cysts, obstetricians, gynecologists, and ultrasound examiners must address the common clinical challenge of distinguishing between benign and malignant ovarian tumors. Numerous types of ovarian tumors exist, many of which exhibit similar characteristics that increase the ambiguity in clinical diagnosis. Using deep learning technology, we aimed to develop a method that rapidly and accurately assists the different diagnosis of ovarian tumors in ultrasound images. METHODS: Based on deep learning method, we used ten well-known convolutional neural network models (e.g., Alexnet, GoogleNet, and ResNet) for training of transfer learning. To ensure method stability and robustness, we repeated the random sampling of the training and validation data ten times. The mean of the ten test results was set as the final assessment data. After the training process was completed, the three models with the highest ratio of calculation accuracy to time required for classification were used for ensemble learning pertaining. Finally, the interpretation results of the ensemble classifier were used as the final results. We also applied ensemble gradient-weighted class activation mapping (Grad-CAM) technology to visualize the decision-making results of the models. RESULTS: The highest mean accuracy, mean sensitivity, and mean specificity of ten single CNN models were 90.51 ± 4.36%, 89.77 ± 4.16%, and 92.00 ± 5.95%, respectively. The mean accuracy, mean sensitivity, and mean specificity of the ensemble classifier method were 92.15 ± 2.84%, 91.37 ± 3.60%, and 92.92 ± 4.00%, respectively. The performance of the ensemble classifier is better than that of a single classifier in three evaluation metrics. Moreover, the standard deviation is also better which means the ensemble classifier is more stable and robust. CONCLUSION: From the comprehensive perspective of data quantity, data diversity, robustness of validation strategy, and overall accuracy, the proposed method outperformed the methods used in previous studies. In future studies, we will continue to increase the number of authenticated images and apply our proposed method in clinical settings to increase its robustness and reliability.

Prenatal ultrasound diagnosis of primary myxomatous degeneration of cardiac valves in a fetus: Case report.

Primary myxomatous degeneration of cardiac valves is a rare cardiac malformation. We discovered a case of fetal primary myxomatous degeneration of cardiac valves during routine prenatal ultrasound examination. This is the first time such a case has been detected on prenatal ultrasound.

Linfadenopatía cervical y supraclavicular ipsilateral a la vacunación de refuerzo con Pfizer-BioNTech COVID-19 / Cervical and supraclavicular lymphadenopathy after Pfizer-BioNTech COVID-19 vaccination

La COVID-19 es la enfermedad causada por el nuevo coronavirus conocido como SARS-CoV-2. Para finales del 2020, la FDA de los Estados Unidos aprobó la primera vacuna para su uso de emergencia contra el COVID-19, desarrollada por Pfizer y BioNTech (BNT162b2). Este nuevo tipo de vacuna utiliza ARN mensajero modificado, el cual le da instrucciones al organismo para generar un fragmento de la proteína espiga de la superficie del virus, y que por sí sola desencadena una respuesta inmunitaria que ayuda a proteger el organismo contra una infección por COVID-19. Dentro de los eventos adversos menos comunes reportados en los estudios clínicos iniciales está la linfadenopatía (0.3 %). Objetivo: reportar el caso de paciente masculino que acude a evaluación sonográfica por preocupación de nódulo palpable en región supraclavicular. Resultados: a la evaluación sonográfica se observa cadena ganglionar reactiva compatible con una linfadenopatía. Paciente reporta vacunación de refuerzo con la vacuna Pfizer 8 días antes de la evaluación, subsecuente a dos vacunas Coronavac, corroborando de que se trata de una linfadenopatía reactiva, secundaria a una respuesta inmune robusta al refuerzo con la vacuna Pfizer. Se realiza una medición de Anti-SARS-CoV-2 TrimericS IgG cuantitativa a los 15 días del refuerzo con Pfizer, reportando valores elevados de 10,600 BAU/mL. Se orientó al paciente a regresar en una semana para seguimiento ecográfico, el cual evidenció resolución espontánea sin secuelas. Conclusiones: los hallazgos de adenopatía axilar o supraclavicular unilateral subsecuentes a la vacunación por COVID-19 deben ser informados tanto a médicos como pacientes, como un efecto secundario temporal producto de la respuesta inmunológica post vacuna. Este hallazgo benigno no requiere seguimiento adicional de imágenes y mucho menos de procedimientos invasivos como biopsias, los cuales generan mucha ansiedad al paciente, además de ser muy costosos para los mismos

COVID-19 is a disease caused by a new coronavirus identified as SARS-CoV-2. Towards the end of 2020, the FDA of the United States approved the first vaccine for emergency use against COVID-19, which was developed by Pfizer and BioNTech (BNT162b2). This new type of vaccine uses a modified RNA Messenger, which gives instructions to the host cells of the vaccinated person to produce a fragment of the spike protein of the virus, which then generates an inmune response and protects the recipient of the vaccine against COVID-19. Among the adverse events less frequently reported in the initial clinical studies of the vaccine is lymphadenopathy which was reported by 0.3% of the participants. Objective: Presentation of a case report of a male subject that came to a ultrasound evaluation due to concern of a palpable nodule in the supraclavicular región. Results: Ultrasound exam showed reactive unilateral cervical and supraclavicular lymphadenopathy. Patient reports a third dose booster with the Pfizer-BioNTech COVID-19 (BNT162b2) vaccine, 8 days prior to the evaluation, after completing a two-dose vaccination schedule with the Coronavac/Sinovac vaccine, confirming a vigorous immune response to the mRNA anti-COVID vaccines. This response was validated by elevated Anti-SARS-CoV-2 TrimericS IgG (10,600 BAU/mL). Patient was informed to return in a week for an echography follow-up which showed spontaneous resolution without leaving sequelae. Conclusions: It is of great importance to inform this benign finding of supraclavicular or axillar adenopathy subsequent to COVID vaccination to the medical community and patients, to avoid unnecessary medical interventions such as imaging or biopsies, which generate anxiety to the patient as well as additional costs

Benign Pancreatic Neurofibroma with Malignant Imaging Features: A Case Report and Literature Review.

Pancreatic neurofibroma is a very rare benign neurogenic tumor unrelated to neurofibromatosis type 1 (NF-1). As the volume increases, it has the risk of malignant transformation. The surgical prognosis of pancreatic neurofibroma is good, but its preoperative imaging features are very similar to those of malignant tumors, which may affect the formulation of treatment plans. This article reports a case of giant neurofibroma of the pancreas with contrast-enhanced ultrasound (CEUS) as one of the diagnostic methods and discusses the tumor's preoperative clinical features, laboratory examinations, and imaging features.

Ultrasound imaging in orbital mucosa-associated lymphoid tissue lymphoma with IgG-4 positive.

This study describes the ultrasound imaging features of orbital mucosa-associated lymphoid tissue lymphoma with IgG-4 positive. The author supposes ultrasound can become a new imaging method for diagnosing orbital lymphoma.

Perinatal Outcomes after Fetal Endoscopic Tracheal Occlusion for Isolated Congenital Diaphragmatic Hernia: Rapid Review / Resultados perinatais após oclusão traqueal endoscópica fetal por hérnia diafragmática congênita isolada: Revisão rápida

Abstract Objective To compare the perinatal outcomes of fetuses with isolated congenital diaphragmatic hernia after fetal endoscopic tracheal occlusion (FETO) and antenatal expectant management. Data sources In this rapid review, searches were conducted in the MEDLINE, PMC, EMBASE and CENTRAL databases between August 10th and September 4th, 2020. Randomized controlled trials (RCTs), quasi-RCTs or cluster-RCTs published in English in the past ten years were included. Study selection We retrieved 203 publications; 180 studies were screened by abstract. Full-text selection was performed for eight studies, and 1 single center RCTmet the inclusion criteria (41 randomized women; 20 in the FETO group, and 21 in the control group). Data collection Data collection was performed independently, by both authors, in two steps (title and abstract and full-text reading). Data synthesis There were no cases of maternal mortality. The mean gestational age at delivery was of 35.6±2.4 weeks in the intervention group, and of 37.4±1.9 weeks among the controls (p<0.01). Survival until 6 months of age was reported in 50% of the intervention group, and in 5.8% of the controls (p<0.01; relative risk: 10.5; 95% confidence interval [95%CI]: 1.5-74.7). Severe postnatal pulmonary hypertension was found in 50% of the infants in the intervention group, and in 85.7% of controls (p=0.02; relative risk: 0.6; 95%CI: 0.4-0.9). An analysis of the study indicated some concerns of risk of bias. The quality of evidence was considered moderate to low. Conclusion Current evidence is limited but suggests that FETO may be an effective intervention to improve perinatal outcomes.

Resumo Objetivo Comparar os resultados perinatais de fetos com hérnia diafragmática congênita após oclusão traqueal endoscópica fetal (OTEF) e conduta expectante pré-natal. Fontes dos dados Nesta revisão rápida, pesquisas foram conduzidas nas bases de dados MEDLINE, PMC, EMBASE e CENTRAL entre 10 de agosto de 2020 e 4 de setembro de 2020. Ensaios clínicos randomizados (ECRs), quase-ECRs e ECRs em cluster publicados em inglês nos últimos dez anos foram incluídos. Seleção dos estudos Foram recuperadas 203 publicações; 180 destas foram triadas pelo resumo. Fez-se a leitura do texto completo de 8 estudos, e 1 ECR cumpriu os critérios de inclusão (41 mulheres aleatorizadas; 20 no grupo OTEF e 21 no grupo de controle). Coleta de dados A coleta de dados realizada independentemente pelos dois autores, em duas etapas (título e resumo, e leitura do texto completo). Síntese dos dados Não houve casos de mortematerna. A idade gestacionalmédia no parto foi de 35,6±2,4 semanas no grupo de intervenção, e de 37,4±1,9 semanas entre os controles (p<0,01). A sobrevida até 6 meses de idade foi relatada em 50% do grupo de intervenção, e em 5,8% dos controles (p<0,01; risco relativo: 10,5; intervalo de confiança de 95% [IC95%]: 1,5-74,7). Hipertensão pulmonar grave ocorreu em 50% dos lactentes do grupo de intervenção, e em 85,7% dos controles (p = 0.02; risco relativo: 0,6; IC95%: 0,4-0,9). Uma análise do estudo indicou algumas preocupações quanto ao risco de viés. A qualidade da evidência foi considerada de moderada a baixa. Conclusão As evidências atuais são limitadas,mas sugeremque a OTEF pode ser uma intervenção eficaz para melhorar resultados perinatais.

Early Prenatal Ultrasound and Molecular Diagnosis of Apert Syndrome: Case Report with Postmortem CT-Scan and Chondral Plate Histology.

Background Apert syndrome is characterized by craniosynostosis, midface hypoplasia and symmetric syndactyly. Case report: A 36-year-old mother, G2P1 underwent an ultrasound scan at 19 week's gestation. There was craniosynostosis, brachi-turricephaly and bilateral hand syndactyly. Genomic DNA from amniocentesis revealed the mutation C758C>Gp. (Pro to Arg substitution) at 252 of the exon 8 of the FGFR2 encoding for Apert syndrome. The pregnancy was terminated. Femoral chondral plate histology showed an increased interstitial matrix between bony trabeculae. Compared with normal, the trabeculae were thinner, more irregular with numerous osteoclasts suggesting abnormal bone remodeling. Hands and feet had an abrupt transition between resting and proliferating cartilage. Conclusion: Apert syndrome has increased intertrabecular matrix, thin trabeculae, increased remodeling, and irregular transition between the maturing and mineralization zones in the femur, and abnormal abrupt transition between the resting and proliferating cartilage in the fingers and toes.

Evaluation of Role of Transabdominal and Transvaginal Ultrasound in Diagnosis of Female Genital Tuberculosis.

BACKGROUND: Female genital tuberculosis (FGTB) is a common problem in developing countries causing significant morbidity, especially infertility. Radiological imaging, especially ultrasound, can help in diagnosis of FGTB with tubo-ovarian masses. AIMS: The present study was performed to evaluate the role of ultrasound in diagnosis of FGTB and to see various findings of FGTB on ultrasound. STUDY SETTING AND DESIGN: It was a prospective cross-sectional study over 4-year period between August 2015 and August 2019 in a tertiary referral center. SUBJECTS AND METHODS: One hundred and seventy-five patients of infertility diagnosed to have FGTB on composite reference standard (CRS) of positive acid-fast bacilli on microscopy or culture of endometrial biopsy, positive polymerase chain reaction, positive GeneXpert, epithelioid granuloma on histology of endometrial biopsy, or definite or probable finding of FGTB on laparoscopy were subjected to transvaginal ultrasound by an experienced sonographer for various findings of FGTB. STATISTICAL ANALYSIS: Data analysis was carried out using STATA software 12.0. Comparison of categorical values was tested using Chi-square Fisher's exact test, with P < 0.05 being taken as significant. RESULTS: Mean age, body mass index, parity, and duration of infertility were 28.9 years, 22.9 kg/m2, 0.26, and 6.06 years, respectively. Menstrual dysfunction was common (44%). Diagnosis of FGTB was made by CRS. Ultrasound was normal in 112 (64%) cases and was abnormal in 63 (36%) cases. Various ultrasound findings were ovarian cyst (23.42%), tubo-ovarian masses (15.42%), unilateral or bilateral hydrosalpinx (13.71%), pyosalpinx (0.57%), adhesion (1.14%), adnexal fixity (6.28%), thin endometrium (24.57%), endometrial fluid (12.57%), endometrial calcification (1.7%), endometrial synechiae (4.57%), cornual synechiae (2.28%), impaired endometrial vascularity (21.71%), ascites (6.85%), and peritoneal or omental thickening (1.75%). CONCLUSION: Carefully performed ultrasound is a useful modality in diagnosis of FGTB, especially in adnexal masses.

Ultrasound-assisted diagnosis of Langerhans cell hyperplasia of the sternum: A case report.

Langerhans cell hyperplasia is a group of diseases characterized by the proliferation or dissemination of the Langerhans cell, which can come in the form of localized benign lesions, or extensive disseminated invasive neoplastic lesions. These lesions mainly invade the patient's bone. In this paper, we describe the case of a 3-year-old boy who was admitted to the pediatric department with sternum pain. Following a focused sternum ultrasound, a diagnosis was made of Langerhans cell histiocytosis.

An efficient deep convolutional neural network model for visual localization and automatic diagnosis of thyroid nodules on ultrasound images.

BACKGROUND: The aim of this study was to construct a deep convolutional neural network (CNN) model for localization and diagnosis of thyroid nodules on ultrasound and evaluate its diagnostic performance. METHODS: We developed and trained a deep CNN model called the Brief Efficient Thyroid Network (BETNET) using 16,401 ultrasound images. According to the parameters of the model, we developed a computer-aided diagnosis (CAD) system to localize and differentiate thyroid nodules. The validation dataset (1,000 images) was used to compare the diagnostic performance of the model using three state-of-the-art algorithms. We used an internal test set (300 images) to evaluate the BETNET model by comparing it with diagnoses from five radiologists with varying degrees of experience in thyroid nodule diagnosis. Lastly, we demonstrated the general applicability of our artificial intelligence (AI) system for diagnosing thyroid cancer in an external test set (1,032 images). RESULTS: The BETNET model accurately detected thyroid nodules in visualization experiments. The model demonstrated higher values for area under the receiver operating characteristic (AUC-ROC) curve [0.983, 95% confidence interval (CI): 0.973-0.990], sensitivity (99.19%), accuracy (98.30%), and Youden index (0.9663) than the three state-of-the-art algorithms (P<0.05). In the internal test dataset, the diagnostic accuracy of the BETNET model was 91.33%, which was markedly higher than the accuracy of one experienced (85.67%) and two less experienced radiologists (77.67% and 69.33%). The area under the ROC curve of the BETNET model (0.951) was similar to that of the two highly skilled radiologists (0.940 and 0.953) and significantly higher than that of one experienced and two less experienced radiologists (P<0.01). The kappa coefficient of the BETNET model and the pathology results showed good agreement (0.769). In addition, the BETNET model achieved an excellent diagnostic performance (AUC =0.970, 95% CI: 0.958-0.980) when applied to ultrasound images from another independent hospital. CONCLUSIONS: We developed a deep learning model which could accurately locate and automatically diagnose thyroid nodules on ultrasound images. The BETNET model exhibited better diagnostic performance than three state-of-the-art algorithms, which in turn performed similarly in diagnosis as the experienced radiologists. The BETNET model has the potential to be applied to ultrasound images from other hospitals.