Current status of endoscopic ultrasound in the diagnosis of intraductal papillary mucinous neoplasms.

The new Kyoto guidelines for the management of intraductal papillary mucinous neoplasm (IPMN) provide evidence-based recommendations for the diagnosis and treatment of IPMN. Endoscopic ultrasonography (EUS) is a diagnostic modality with a high spatial resolution that allows detailed observation and obtaining cyst fluid or tissue samples via EUS-guided fine needle aspiration (EUS-FNA). Currently, EUS is an indispensable examination method for the diagnosis of pancreatic diseases. On the other hand, there have been concerns that EUS imaging tends to be highly operator-dependent, and may lack objectivity. Previous guidelines have assigned EUS as an option for patients with worrisome features. However, recent reports indicate that the sensitivity of EUS for the diagnosis of mural nodules (MNs) is more than 90%, comparable or superior to that of contrast-enhanced computed tomography or magnetic resonance cholangiopancreatography. The specific advantages of EUS in the diagnosis of IPMN are: (1) high spatial resolution imaging for the diagnosis of MNs, (2) contrast-enhanced EUS for differentiation of intra-cystic MNs from mucous clots, and (3) pathological diagnosis using EUS-FNA and differential diagnosis of a pancreatic cystic tumor by cystic fluid analysis. In order to utilize EUS in the diagnosis of IPMN, endoscopists are required to have the skills to provide sufficiently objective imaging findings.

Assessing the impact of nodule features and software algorithm on pulmonary nodule measurement uncertainty for nodules sized 20 mm or less.

Background: Measurements are not exact, so that if a measurement is repeated, one would get a different value each time. The spread of these values is the measurement uncertainty. Understanding measurement uncertainty of pulmonary nodules is important for proper interpretation of size and growth measurements. Larger amounts of measurement uncertainty may require longer follow-up intervals to be confident that any observed growth is due to actual growth rather than measurement uncertainty. We examined the influence of nodule features and software algorithm on measurement uncertainty of small, solid pulmonary nodules. Methods: Volumes of 107 nodules were measured on 4-6 repeated computed tomography (CT) scans (Siemens Somatom AS, 100 kVp, 120 mA, 1.0 mm slice thickness reconstruction) prospectively obtained during CT-guided fine needle aspiration biopsy between 2015-2021 at Department of Diagnostic, Molecular, and Interventional Radiology in Icahn School of Medicine at Mount Sinai, using two different automated volumetric algorithms. For each, the coefficient of variation (standard deviation divided by the mean) of nodule volume measurements was determined. The following features were considered: diameter, location, vessel and pleural attachments, nodule surface area, and extent of the nodule in the three acquisition dimensions of the scanner. Results: Median volume of 107 nodules was 515.23 and 535.53 mm3 for algorithm #1 and #2, respectively with excellent agreement (intraclass correlation coefficient =0.98). Median coefficient of variation of nodule volume was low for the two algorithms, but significantly different (4.6% vs. 8.7%, P<0.001). Both algorithms had a trend of decreasing coefficient of variation of nodule volume with increasing nodule diameter, though only significant for algorithm #2. Coefficient of variation of nodule volume was significantly associated with nodule volume (P=0.02), attachment to blood vessels (P=0.02), and nodule surface area (P=0.001) for algorithm #2 using a multiple linear regression model. Correlation between the coefficient of variation (CoV) of nodule volume and the CoV of the x, y, z measurements for algorithm #1 were 0.29 (P=0.0021), 0.25 (P=0.009), and 0.80 (P<0.001) respectively, and for algorithm #2, 0.46 (P<0.001), 0.52 (P<0.001), and 0.58 (P<0.001), respectively. Conclusions: Even in the best-case scenario represented in this study, using the same measurement algorithm, scanner, and scanning protocol, considerable measurement uncertainty exists in nodule volume measurement for nodules sized 20 mm or less. We found that measurement uncertainty was affected by interactions between nodule volume, algorithm, and shape complexity.

Differentiation of benign and malignant lesions in Bethesda III and IV thyroid nodules via dual-energy computed tomography quantitative parameters and morphologic features.

Background: Thyroid nodules (TNs) cytologically defined as category Bethesda III and IV pose a major diagnostic challenge before surgery, demanding new methods to reduce unnecessary diagnostic thyroid lobectomies for patients with benign TNs. This study aimed to assess whether a model combining dual-energy computed tomography (DECT) quantitative parameters with morphologic features could reliably differentiate between benign and malignant lesions in Bethesda III and IV TNs. Methods: Data from 77 patients scheduled for thyroid surgery for Bethesda III and IV TNs (malignant =48; benign =29) who underwent DECT scans were reviewed. DECT quantitative parameters including normalized iodine concentration (NIC), attenuation on the slope of spectral Hounsfield unit (HU) curve, and normalized effective atomic number (Zeff) were measured in the arterial phase (AP) and venous phase (VP). DECT quantitative parameters and morphologic features were compared between the malignant and benign cohorts. The receiver operating characteristic curve was performed to compare the performances of significant DECT quantitative parameters, morphologic features, or the models combining the DECT parameters, respectively, with morphologic features. A nomogram was constructed from the optimal performance model, and the performance was evaluated via the calibration curve and decision curve analysis. Results: The areas under the receiver operating characteristic curve with 95% confidence interval (CI) of the NIC in the AP (AP-NIC), slope of spectral HU curve in the AP, and NZeff in the AP were 0.749 (95% CI: 0.641-0.857), 0.654 (95% CI: 0.530-0.778), and 0.722 (95% CI: 0.602-0.842), respectively. The model combining AP-NIC with enhanced blurring showed the highest diagnostic performance, with an area under the receiver operating characteristic curve (AUC), sensitivity, and specificity of 0.808, 0.854, and 0.655, respectively; it was then used to construct a nomogram. The calibration curve showed that the discrepancy between the prediction of the nomogram and actual observations was less than 5%. The decision curve analysis indicated the nomogram had a positive net benefit in threshold risk ranges of 14% to 58% or 60% to 91% for malignant Bethesda III and IV TNs. Conclusions: The model combining AP-NIC with enhanced blurring could reliably differentiate between benign and malignant lesions in Bethesda III and IV TNs.

Preoperative computed tomography semantic features in predicting lymph node metastasis of part-solid nodules in non-small cell lung cancer: a multicenter retrospective study.

Background: Lymph node metastasis (LNM) is the most common route of metastasis for lung cancer, and it is an independent risk factor for long-term survival and recurrence in patients with non-small cell lung cancer (NSCLC). The purpose of this study was to explore the value of preoperative computed tomography (CT) semantic features in the differential diagnosis of LNM in part-solid nodules (PSNs) of NSCLC. Methods: A total of 955 patients with NSCLC confirmed by postoperative pathology were retrospectively enrolled from January 2019 to March 2023. The clinical, pathological data and preoperative CT images of these patients were investigated and statistically analyzed in order to identify the risk factors for LNM. Multivariate logistic regression was used to select independent risk factors and establish different prediction models. Ten-fold cross-validation was used for model training and validation. The area under the curve (AUC) of the receiver operating characteristic (ROC) curve was calculated, and the Delong test was used to compare the predictive performance between the models. Results: LNM occurred in 68 of 955 patients. After univariate analysis and adjustment for confounding factors, smoking history, pulmonary disease, solid component proportion, pleural contact type, and mean diameter were identified as the independent risk factors for LNM. The image predictors model established by the four independent factors of CT semantic features, except smoking history, showed a good diagnostic efficacy for LNM. The AUC in the validation group was 0.857, and the sensitivity, specificity, and accuracy of the model were all 77.6%. Conclusions: Preoperative CT semantic features have good diagnostic value for the LNM of NSCLC. The image predictors model based on pulmonary disease, solid component proportion, pleural contact type, and mean diameter demonstrated excellent diagnostic efficacy and can provide non-invasive evaluation in clinical practice.

Construction and validation of a risk score system for diagnosing invasive adenocarcinoma presenting as pulmonary pure ground-glass nodules: a multi-center cohort study in China.

Background: Anxiety-driven clinical interventions have been queried due to the nondeterminacy of pure ground-glass nodules (pGGNs). Although radiomics and radiogenomics aid diagnosis, standardization and reproducibility challenges persist. We aimed to assess a risk score system for invasive adenocarcinoma in pGGNs. Methods: In a retrospective, multi-center study, 772 pGGNs from 707 individuals in The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital were grouped into training (509 patients with 558 observations) and validation (198 patients with 214 observations) sets consecutively from January 2017 to November 2021. An additional test set of 143 observations in Hainan Cancer Hospital was analyzed in the same period. Computed tomography (CT) signs and clinical features were manually collected, and the quantitative parameters were achieved by artificial intelligence (AI). The positive cutoff score was ≥3. Risk scores system 3 combined carcinoma history, chronic obstructive pulmonary disease (COPD), maximum diameters, nodule volume, mean CT values, type II or III vascular supply signs, and other radiographic characteristics. The evaluation included the area under the curves (AUCs), accuracy, sensitivity, specificity, positive predictive values (PPV), and negative predictive values (NPV) for both the risk score systems 1, 2, 3 and the AI model. Results: The risk score system 3 [AUC, 0.840; 95% confidence interval (CI): 0.789-0.890] outperformed the AI model (AUC, 0.553; 95% CI: 0.487-0.619), risk score system 1 (AUC, 0.802; 95% CI: 0.754-0.851), and risk score system 2 (AUC, 0.816; 95% CI: 0.766-0.867), with 88.0% (0.850-0.904) accuracy, 95.6% (0.932-0.972) PPV, 0.620 (0.535-0.702) NPV, 89.6% (0.864-0.920) sensitivity, and 80.6% (0.717-0.872) specificity in the training sets. In the validation and test sets, risk score system 3 performed best with AUCs of 0.769 (0.678-0.860) and 0.801 (0.669-0.933). Conclusions: An AI-based risk scoring system using quantitative image parameters, clinical features, and radiographic characteristics effectively predicts invasive adenocarcinoma in pulmonary pGGNs.

A Rare Case of Diffuse Idiopathic Pulmonary Neuroendocrine Cell Hyperplasia: A Case Report.

Diffuse idiopathic pulmonary neuroendocrine cell hyperplasia (DIPNECH) is a rare pulmonary disease characterized by the diffuse proliferation of neuroendocrine cells in the bronchial epithelium. It is considered a preinvasive precursor to carcinoid tumors and usually presents with obstructive symptoms. We present the case of a 71-year-old female, non-smoker, with a past medical history of asthma, osteoarthritis, allergic rhinitis, and hyperlipidemia who was referred to the pulmonology clinic in view of incidental chest CT findings of multiple pulmonary nodules. Physical examination and labs were unremarkable. CT of the chest showed scattered multiple noncalcified pulmonary nodules with a 10 mm dominant nodule in the inferior right middle lobe and several subcentimeter hypodensities in the left and right lobes of the lung. A PET scan confirmed the CT findings along with no abnormal hypermetabolic activity to suggest malignancy. The patient was followed up in the pulmonology clinic at six months, 12 months, and then 18 months. At 18 months owing to a slight increase in the size of the largest lung nodule, a CT-guided biopsy done was conclusive of a carcinoid. The tumor cells were positive for synaptophysin, chromogranin, insulinoma-associated protein 1 (INSM-1), and thyroid transcription factor 1 (TTF-1). The Ki-67 (Keil) index was <1%. A video-assisted thoracic surgery with right middle lobectomy along with mediastinal lymph node dissection was then done, and the patient was found to have stage pT1aN0 typical carcinoid tumor (1.0 cm), with multiple carcinoid tumors and neuroendocrine hyperplasia, consistent with DIPNECH. She has been under clinical follow-up for over three years at present and continues to be asymptomatic with complete remission following surgery. DIPNECH primarily affects middle-aged, non-smoking females who present with cough and dyspnea, and diagnosis is often delayed due to clinical features overlapping with those of obstructive lung disease. Imaging shows lung nodules, ground-glass opacities, and/or mosaic attenuation. Due to the rarity of the conditions, there are no established clinical trials, and therefore, there is a need to establish guidelines.

Soybean symbiotic-nodule zonation and cell differentiation are defined by NIN2 signaling and GH3-dependent auxin homeostasis.

Symbiotic nodules comprise two classes, indeterminate and determinate, defined by the presence/absence of apical meristem and developmental zonation. Why meristem and zonation are absent from determinate nodules remains unclear. Here, we define cell types in developing soybean nodules, highlighting the undifferentiated infection zones and differentiated nitrogen-fixation zones. Auxin governs infection zone maintenance. GRETCHEN HAGEN 3 (GH3) enzymes deactivate auxin by conjugation and promote cell differentiation. gh3 mutants increased undifferentiated cells and enlarged infection zones. The central symbiosis-transcription factor NIN2a activates GH3.1 to reduce auxin levels and facilitates cell differentiation. High auxin promotes NIN2a protein accumulation and enhances signaling, further deactivating auxin and depleting infection zones. Our findings shed light on the NIN2a-GH3-auxin module that drives soybean nodule cell differentiation. This study challenges our understanding of determinate nodule development and proposes that the regulation of nodule zonation offers valuable insights into broader mechanisms of cell differentiation across plant species.

Coronary intravascular lithotripsy in contemporary practice: challenges and opportunities in coronary intervention.

Percutaneous coronary intervention (PCI) of calcified coronary arteries is associated with poor outcomes. Poorly modified calcified lesion hinders the stent delivery, disrupts drug-carrying polymer, impairs drug elution kinetics and results in under-expanded stent (UES). UES is the most common cause of acute stent thrombosis and in-stent restenosis after PCI of calcified lesions. Angiography has poor sensitivity for recognition and quantification of coronary calcium, thereby mandating the use of intravascular imaging. Intravascular imaging, like intravascular ultrasound and optical coherence tomography, has the potential to accurately identify and quantify the coronary calcium and to guide appropriate modification device before stent placement. Available options for the modification of calcified plaque include modified balloons (cutting balloon, scoring balloon and high-pressure balloon), atherectomy devices (rotational atherectomy and orbital atherectomy) and laser atherectomy. Coronary intravascular lithotripsy (IVL) is the newest addition to the tool box for calcified plaque modification. It produces the acoustic shockwaves, which interact with the coronary calcium to cause multiplanar fractures. These calcium fractures increase the vessel compliance and result in desirable minimum stent areas. Coronary IVL has established its safety and efficacy for calcified lesion in series of Disrupt CAD trials. Its advantages over atherectomy devices include ease of use on workhorse wire, ability to modify deep calcium, no debris embolization causing slow flow or no-flow and minimal thermal injury. It is showing promising results in modification of difficult calcified lesion subsets such as calcified nodule, calcified left main bifurcation lesions and chronic total occlusion. In this review, authors will summarize the mechanism of action for IVL, its role in contemporary practice, evidence available for its use, its advantages over atherectomy devices and its imaging insight in different calcified lesion scenarios.

Shock the rock with coronary intravascular lithotripsyPresence of coronary calcium during stenting is associated with the risk of stent under expansion. It's imperative to adequately modify this coronary calcium before placing the stent. Till recent past, the most effective method for calcium modification is debulking it with rotational artherectomy, which is associated with the risk of coronary perforation, slow flow or abrupt vessel closure. Recently, a balloon-based lithotripsy device has established its safety and efficacy for treating such lesions. Coronary intravascular lithotripsy (IVL) is an easy to use calcium modification device and is associated with almost negligible complications, when compared with artherectomy devices. In this review, we will discuss the mechanism of IVL action and its use in different scenarios of calcified coronary artery disease.

Effect of seed priming with polyethylene glycol, distilled water, and sorbitol on physical, chemical quality parameters, and nodule microbiota of lentil.

The aim of this study was to investigate the effects of different seed priming solutions on physical and chemical quality parameters of lentils as well as nodule bacterial diversity before sowing. Therefore, lentil seeds were treated with polyethylene glycol (PEG 6000) (15%), sorbitol (6%), and distilled water, and none pretreated lentils (Lens culinaris) were used as control. The seeds were kept in these solutions for 24 h, then dried on toweling paper for 24 h, and used for the experiment. For nodule microbiota analysis, the plant root was divided into two equal parts, upper and lower, according to the root length and all nodules were collected from each region. According to the results, it was observed that emergence and flowering started late in the control compared to other seed priming treatments. Sorbitol application was found to provide advantages in terms of germination and seedling development. PEG and distilled water (DW) treatments showed an increase in total phenolic component activity; however, no significant change was observed in DPPH radical scavenging activity. Amplicon-based metagenomic analysis revealed that sorbitol and distilled water were the seed priming solutions altering the species diversity, especially Rhizobium sp. as the genus. In the comparison of samples taken from different parts of the root nodules, more Rhizobium sp. as a genus and Rhizobium leguminosarum as the species were found in the nodules collected from the top of the root. According to the overall results of lentil pod, lentil plant, and microbiota, sorbitol and DW can be considered to be a good priming solutions.

Deep learning in pulmonary nodule detection and segmentation: a systematic review.

OBJECTIVES: The accurate detection and precise segmentation of lung nodules on computed tomography are key prerequisites for early diagnosis and appropriate treatment of lung cancer. This study was designed to compare detection and segmentation methods for pulmonary nodules using deep-learning techniques to fill methodological gaps and biases in the existing literature. METHODS: This study utilized a systematic review with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, searching PubMed, Embase, Web of Science Core Collection, and the Cochrane Library databases up to May 10, 2023. The Quality Assessment of Diagnostic Accuracy Studies 2 criteria was used to assess the risk of bias and was adjusted with the Checklist for Artificial Intelligence in Medical Imaging. The study analyzed and extracted model performance, data sources, and task-focus information. RESULTS: After screening, we included nine studies meeting our inclusion criteria. These studies were published between 2019 and 2023 and predominantly used public datasets, with the Lung Image Database Consortium Image Collection and Image Database Resource Initiative and Lung Nodule Analysis 2016 being the most common. The studies focused on detection, segmentation, and other tasks, primarily utilizing Convolutional Neural Networks for model development. Performance evaluation covered multiple metrics, including sensitivity and the Dice coefficient. CONCLUSIONS: This study highlights the potential power of deep learning in lung nodule detection and segmentation. It underscores the importance of standardized data processing, code and data sharing, the value of external test datasets, and the need to balance model complexity and efficiency in future research. CLINICAL RELEVANCE STATEMENT: Deep learning demonstrates significant promise in autonomously detecting and segmenting pulmonary nodules. Future research should address methodological shortcomings and variability to enhance its clinical utility. KEY POINTS: Deep learning shows potential in the detection and segmentation of pulmonary nodules. There are methodological gaps and biases present in the existing literature. Factors such as external validation and transparency affect the clinical application.

The negative outlook: Long-term follow up of ThyroSeq negative and low-risk nodules.

BACKGROUND: Molecular testing of thyroid nodules is an essential tool to help risk stratify nodules with indeterminate cytology. Although ThyroSeq testing has been around for over a decade, there is a paucity of long-term follow-up data on cytologically indeterminate nodules that are determined to be molecularly negative or low-risk. The objective of this study is to assess the outcomes of nodules with indeterminate cytology (Bethesda III or IV) and negative or low-risk ThyroSeq results. METHODS: This is a single academic institution retrospective cohort study. Patients with at least one thyroid nodule sampled with fine-needle aspiration who underwent ThyroSeq testing from 2012 to 2018 and had negative or low-risk ThyroSeq results on a cytologically indeterminate sample (n = 159 patients, 167 nodules) were included in the study. Outcomes include the false-negative rate and negative predictive value of each test version, as well as follow-up length for each nodule. RESULTS: There were 159 patients with a mean age of 58 years (7-84 years) included in this study; the majority were female (81.8%). The mean follow-up was 4.0 years. Of 167 nodules, three were found to be malignant on resection (1.8%). The negative predictive value for the entire cohort was 98.2% and it was 89.3% for the surgical series. CONCLUSION: ThyroSeq testing has good negative predictive value and can help risk stratify cytologically indeterminate nodules. Routine follow-up allows for safe monitoring of nodules for features suggestive of malignancy.

In-stent restenosis caused by a reprotruding calcified nodule and stent fracture in the hinged coronary artery.

Calcified nodules (CNs) cause in-stent restenosis (ISR) frequently. Although reprotrusion of CNs through stent struts is one of the mechanisms of ISR, the process of this phenomenon has not been understood. Furthermore, little is known about stent fracture (SF) occurring at the site of CNs. We are presenting a case of an 82-year-old male who developed early ISR due to the combination of an in-stent CN and SF in the hinged right coronary artery. The process of progression of the in-stent CN was recorded sequentially with angiography and intravascular ultrasound (IVUS). IVUS from the fulcrum of hinge motion revealed the repetitive protruding movement of the CN into the stent lumen.

Safety and cosmesis of gasless endoscopic thyroidectomy: a retrospective study.

Despite growing interest in gasless endoscopic unilateral thyroid lobectomy via the axillary approach, there are a lack of sufficient data on its safety and cosmetic outcomes. This retrospective study analysed the clinical outcomes and postoperative complications of 161 patients who underwent this surgery for thyroid cancer and nodules, with particular attention given to complications and patient satisfaction with cosmetic outcomes. All 161 patients (143 females, 18 males) successfully underwent the operation without conversion to open surgery. Temporary vocal cord paralysis occurred in five patients, with no other serious complications observed. The cosmetic outcomes were generally good, with no recurrences or tumour implantations observed during follow-up. For carefully selected patients, gasless endoscopic unilateral thyroid lobectomy via the axillary approach is not only safe but also provides excellent cosmetic results.

Prevalence of thyroid nodule and relationship with physiological and psychosocial factors among adults in Zhejiang Province, China: a baseline survey of a cohort study.

BACKGROUND: Thyroid nodules have attracted much attention due to their high incidence and potential for malignant transformation. Compared with the clinical assessment and diagnosis of thyroid nodules, there are relatively few studies on the epidemiological risk factors for thyroid nodules. The aim of this study was to investigate the prevalence of thyroid nodule among adults in Zhejiang province and to explore their relationship with physiological and psychosocial factors. METHODS: The data used in this study were obtained from the baseline survey of the Zhejiang Provincial Cohort Study on Environment and Health. From June 2022 to December 2023, a total of 21,712 participants from five representative cities in Zhejiang were recruited for the baseline survey. Based on the inclusion and exclusion criteria, 15,595 adults were included in the analysis. The data were collected via self-report questionnaires and physical examinations. Multivariate logistic regression analysis was subsequently performed. RESULTS: The detection rate of thyroid nodules was 50.98% among adults in Zhejiang province. Age, gender, education level, BMI, tea and alcohol consumption all had a statistically significant association with thyroid nodules (p < 0.05). After adjusting for sociodemographic factors, results of logistic regression analysis showed that good life satisfaction (OR = 0.854, 95% CI: 0.780-0.934) had a lower risk of thyroid nodules, however, poor life satisfaction (OR = 1.406, 95% CI: 1.014-1.951), social isolation (OR = 1.294, 95% CI: 1.089-1.538) and a family history of thyroid nodules (OR = 1.334, 95% CI: 1.064-1.672) had a greater risk of thyroid nodules. CONCLUSION: The detection rate of thyroid nodules in adults of Zhejiang province was an increasing trend compared with that in previous years. In addition to the sensitive thyroid nodule screening technology, influencing factors mentioned in this study might also represent credible candidates for this increase. As variable influence factors, weight management, good interpersonal relationships and life satisfaction should be the focus of health interventions.

The clinical value of artificial intelligence in assisting junior radiologists in thyroid ultrasound: a multicenter prospective study from real clinical practice.

BACKGROUND: This study is to propose a clinically applicable 2-echelon (2e) diagnostic criteria for the analysis of thyroid nodules such that low-risk nodules are screened off while only suspicious or indeterminate ones are further examined by histopathology, and to explore whether artificial intelligence (AI) can provide precise assistance for clinical decision-making in the real-world prospective scenario. METHODS: In this prospective study, we enrolled 1036 patients with a total of 2296 thyroid nodules from three medical centers. The diagnostic performance of the AI system, radiologists with different levels of experience, and AI-assisted radiologists with different levels of experience in diagnosing thyroid nodules were evaluated against our proposed 2e diagnostic criteria, with the first being an arbitration committee consisting of 3 senior specialists and the second being cyto- or histopathology. RESULTS: According to the 2e diagnostic criteria, 1543 nodules were classified by the arbitration committee, and the benign and malignant nature of 753 nodules was determined by pathological examinations. Taking pathological results as the evaluation standard, the sensitivity, specificity, accuracy, and area under the receiver operating characteristic curve (AUC) of the AI systems were 0.826, 0.815, 0.821, and 0.821. For those cases where diagnosis by the Arbitration Committee were taken as the evaluation standard, the sensitivity, specificity, accuracy, and AUC of the AI system were 0.946, 0.966, 0.964, and 0.956. Taking the global 2e diagnostic criteria as the gold standard, the sensitivity, specificity, accuracy, and AUC of the AI system were 0.868, 0.934, 0.917, and 0.901, respectively. Under different criteria, AI was comparable to the diagnostic performance of senior radiologists and outperformed junior radiologists (all P < 0.05). Furthermore, AI assistance significantly improved the performance of junior radiologists in the diagnosis of thyroid nodules, and their diagnostic performance was comparable to that of senior radiologists when pathological results were taken as the gold standard (all p > 0.05). CONCLUSIONS: The proposed 2e diagnostic criteria are consistent with real-world clinical evaluations and affirm the applicability of the AI system. Under the 2e criteria, the diagnostic performance of the AI system is comparable to that of senior radiologists and significantly improves the diagnostic capabilities of junior radiologists. This has the potential to reduce unnecessary invasive diagnostic procedures in real-world clinical practice.

Artificial intelligence-based graded training of pulmonary nodules for junior radiology residents and medical imaging students.

BACKGROUND: To evaluate the efficiency of artificial intelligence (AI)-assisted diagnosis system in the pulmonary nodule detection and diagnosis training of junior radiology residents and medical imaging students. METHODS: The participants were divided into three groups. Medical imaging students of Grade 2020 in the Jinzhou Medical University were randomly divided into Groups 1 and 2; Group 3 comprised junior radiology residents. Group 1 used the traditional case-based teaching mode; Groups 2 and 3 used the 'AI intelligent assisted diagnosis system' teaching mode. All participants performed localisation, grading and qualitative diagnosed of 1,057 lung nodules in 420 cases for seven rounds of testing after training. The sensitivity and number of false positive nodules in different densities (solid, pure ground glass, mixed ground glass and calcification), sizes (less than 5 mm, 5-10 mm and over 10 mm) and positions (subpleural, peripheral and central) of the pulmonary nodules in the three groups were detected. The pathological results and diagnostic opinions of radiologists formed the criteria. The detection rate, diagnostic compliance rate, false positive number/case, and kappa scores of the three groups were compared. RESULTS: There was no statistical difference in baseline test scores between Groups 1 and 2, and there were statistical differences with Group 3 (P = 0.036 and 0.011). The detection rate of solid, pure ground glass and calcified nodules; small-, medium-, and large-diameter nodules; and peripheral nodules were significantly different among the three groups (P<0.05). After seven rounds of training, the diagnostic compliance rate increased in all three groups, with the largest increase in Group 2. The average kappa score increased from 0.508 to 0.704. The average kappa score for Rounds 1-4 and 5-7 were 0.595 and 0.714, respectively. The average kappa scores of Groups 1,2 and 3 increased from 0.478 to 0.658, 0.417 to 0.757, and 0.638 to 0.791, respectively. CONCLUSION: The AI assisted diagnosis system is a valuable tool for training junior radiology residents and medical imaging students to perform pulmonary nodules detection and diagnosis.

A Rare Case of Invasive Thyroid Aspergillosis Revealed on 18F-FDG-PET/CT.

Invasive aspergillosis (IA) represents a common form of fungal infection caused by various species of Aspergillus that most frequently affect immunocompromised patients. Typically, this disease occurs preferentially in high-risk groups including patients infected with the human immunodeficiency virus (HIV), patients with leukemia, patients with autoimmune diseases, and organ transplant patients undergoing medical immunosuppression. Considered the second most common cause of opportunistic fungal infection in humans after Candida albicans, this pathogen predominantly affects the lungs, but it may also spread by a hematogenous route to various organs and have a heterogeneous presentation. Owing to its high iodine levels, high perfusion, and enclosed capsule, the thyroid gland is considered to have a lower susceptibility to microbial invasion, and it is fairly uncommon to find associated infectious nodules. In metabolic imaging, 18F-FDG-PET/CT has become increasingly useful for detecting a wide range of infectious and inflammatory diseases and is already the gold standard for certain indications. According to the literature, no studies of hypermetabolic nodular thyroid aspergillosis on 18F-FDG-PET/CT confirmed on histology have yet been reported. Here, we report the first case of a patient with a heterogeneous presentation of IA and the presence of a hypermetabolic nodule in the thyroid with a surprising result.

3D airway geometry analysis of factors in airway navigation failure for lung nodules.

BACKGROUND: This study aimed to quantitatively reveal contributing factors to airway navigation failure during radial probe endobronchial ultrasound (R-EBUS) by using geometric analysis in a three-dimensional (3D) space and to investigate the clinical feasibility of prediction models for airway navigation failure. METHODS: We retrospectively reviewed patients who underwent R-EBUS between January 2017 and December 2018. Geometric quantification was analyzed using in-house software built with open-source python libraries including the Vascular Modeling Toolkit ( http://www.vmtk.org ), simple insight toolkit ( https://sitk.org ), and sci-kit image ( https://scikit-image.org ). We used a machine learning-based approach to explore the utility of these significant factors. RESULTS: Of the 491 patients who were eligible for analysis (mean age, 65 years +/- 11 [standard deviation]; 274 men), the target lesion was reached in 434 and was not reached in 57. Twenty-seven patients in the failure group were matched with 27 patients in the success group based on propensity scores. Bifurcation angle at the target branch, the least diameter of the last section, and the curvature of the last section are the most significant and stable factors for airway navigation failure. The support vector machine can predict airway navigation failure with an average area under the curve of 0.803. CONCLUSIONS: Geometric analysis in 3D space revealed that a large bifurcation angle and a narrow and tortuous structure of the closest bronchus from the lesion are associated with airway navigation failure during R-EBUS. The models developed using quantitative computer tomography scan imaging show the potential to predict airway navigation failure.

Evaluation and application of American College of Radiology Thyroid Imaging Reporting and Data System for improved malignancy detection in paediatric thyroid nodules.

OBJECTIVE: The American College of Radiology Thyroid Imaging Reporting and Data System (TI-RADS) is a widely used method for the management of adult thyroid nodules. However, its use in paediatric patients is controversial because adult fine needle aspiration biopsy (FNAB) recommendations may lead to delayed diagnoses of cancer in children. The objectives of this study were to evaluate the performance of TI-RADS in paediatric thyroid nodules and to tailor FNAB recommendations for children. METHODS: Consecutive surgically resected paediatric thyroid nodules from two tertiary care centres between 2003 and 2021 were reviewed. Ultrasounds were blindly scored by radiologists according to TI-RADS. Management recommendations based on TI-RADS were evaluated. Various modelling methodologies were used to determine the optimal cutoff for FNAB in children. RESULTS: Of the 96 patients, 79 (82%) were female and the median age at surgery was 16.1 years. Fifty (52%) nodules were malignant on surgical pathology. The area under the receiver operating characteristic curve of TI-RADS for predicting malignancy was 0.78. Adult TI-RADS recommendations would have resulted in 4% of cancerous nodules being lost to follow-up. Modifications to TI-RADS (FNAB of all TR3 nodules ≥1.5 cm, FNAB of TR4 and TR5 nodules ≥0.5 cm, surveillance of nodules ≥1 cm, consider surgery for nodules >4 cm) reduced this missed malignancy rate to 0%. CONCLUSIONS: TI-RADS can risk-stratify paediatric thyroid nodules. However, the system requires modifications to reduce the missed malignancy rate in paediatric thyroid nodules. Our data suggest that lower size thresholds for FNAB are warranted in children.