Interventional Pulmonology: Extending the Breadth of Thoracic Care.

Interventional pulmonary medicine has developed as a subspecialty focused on the management of patients with complex thoracic disease. Leveraging minimally invasive techniques, interventional pulmonologists diagnose and treat pathologies that previously required more invasive options such as surgery. By mitigating procedural risk, interventional pulmonologists have extended the reach of care to a wider pool of vulnerable patients who require therapy. Endoscopic innovations, including endobronchial ultrasound and robotic and electromagnetic bronchoscopy, have enhanced the ability to perform diagnostic procedures on an ambulatory basis. Therapeutic procedures for patients with symptomatic airway disease, pleural disease, and severe emphysema have provided the ability to palliate symptoms. The combination of medical and procedural expertise has made interventional pulmonologists an integral part of comprehensive care teams for patients with oncologic, airway, and pleural needs. This review surveys key areas in which interventional pulmonologists have impacted the care of thoracic disease through bronchoscopic intervention.

Integrative Multianalytical Model Based on Novel Plasma Protein Biomarkers for Distinguishing Lung Adenocarcinoma and Benign Pulmonary Nodules.

Given the pressing clinical problem of making a decision in diagnosis for subjects with pulmonary nodules, we aimed to discover novel plasma protein biomarkers for lung adenocarcinoma (LUAD) and benign pulmonary nodules (BPNs) and then develop an integrative multianalytical model to guide the clinical management of LUAD and BPN patients. Through label-free quantitative plasma proteomic analysis (data are available via ProteomeXchange with identifier PXD046731), 12 differentially expressed proteins (DEPs) in LUAD and BPN were screened. The diagnostic abilities of DEPs were validated in two independent validation cohorts. The results showed that the levels of three candidate proteins (PRDX2, PON1, and APOC3) were lower in the plasma of LUAD than in BPN. The three candidate proteins were combined with three promising computed tomography indicators (spiculation, vascular notch sign, and lobulation) and three traditional markers (CEA, CA125, and CYFRA21-1) to construct an integrative multianalytical model, which was effective in distinguishing LUAD from BPN, with an AUC of 0.904, a sensitivity of 81.44%, and a specificity of 90.14%. Moreover, the model possessed impressive diagnostic performance between early LUADs and BPNs, with the AUC, sensitivity, specificity, and accuracy of 0.868, 65.63%, 90.14%, and 82.52%, respectively. This model may be a useful auxiliary diagnostic tool for LUAD and BPN by achieving a better balance of sensitivity and specificity.

Indeterminate pulmonary nodules in non-rhabdomyosarcoma soft tissue sarcoma: A study of the European paediatric Soft Tissue Sarcoma Study Group.

BACKGROUND: The aim of this study was to assess the clinical impact of indeterminate pulmonary nodules (no more than four pulmonary nodules of less than 5 mm or one nodule measuring between 5 and less than 10 mm by computed tomography [CT]) in children and adolescents with adult-type non-rhabdomyosarcoma soft tissue sarcoma (NRSTS) at diagnosis. METHODS: Patients with NRSTS treated in 11 centers as part of the European paediatric Soft Tissue Sarcoma Study Group (EpSSG) were retrospectively assessed. Local radiologists, blinded to clinical information except for patients' age and tumor histotype, reviewed the chest CT at diagnosis and filled out a case report form. Because patients with or without indeterminate nodules in the EpSSG NRSTS 2005 study received the same type of treatment, event-free survival (EFS) and overall survival (OS) between groups by log-rank test were compared. RESULTS: Overall, 206 patients were examined: 109 (52.9%) were without any nodules, 78 (38%) had at least one indeterminate nodule, and 19 (9.2%) had nodules meeting the definition of metastases, which were then considered to be misclassified and were excluded from further analyses. Five-year EFS was 78.5% (95% CI, 69.4%-85.1%) for patients without nodules and 69.6% (95% CI, 57.9%-78.7%) for patients with indeterminate nodules (p = .135); 5-year OS was 87.4% (95% CI, 79.3%-92.5%) and 79.0% (95% CI, 67.5%-86.8%), respectively (p = .086). CONCLUSIONS: This study suggests that survival does not differ in otherwise nonmetastatic patients with indeterminate pulmonary nodules compared to nonmetastatic patients without pulmonary nodules. PLAIN LANGUAGE SUMMARY: Radiologists should be aware of the classification of indeterminate pulmonary nodules in non-rhabdomyosarcoma soft tissue sarcomas and use it in their reports. More than a third of patients with non-rhabdomyosarcoma soft tissue sarcoma can be affected by indeterminate pulmonary nodules. Indeterminate pulmonary nodules do not significantly affect the overall survival of pediatric patients with non-rhabdomyosarcoma soft tissue sarcoma.

The American Cancer Society National Lung Cancer Roundtable strategic plan: Optimizing strategies for lung nodule evaluation and management.

Lung nodules are frequently detected on low-dose computed tomography scans performed for lung cancer screening and incidentally detected on imaging performed for other reasons. There is wide variability in how lung nodules are managed by general practitioners and subspecialists, with high rates of guideline-discordant care. This may be due in part to the level of evidence underlying current practice guideline recommendations (primarily based on findings from uncontrolled studies of diagnostic accuracy). The primary aims of lung nodule management are to minimize harms of diagnostic evaluations while expediting the evaluation, diagnosis, and treatment of lung cancer. Potentially useful tools such as lung cancer probability calculators, automated methods to identify patients with nodules in the electronic health record, and multidisciplinary team evaluation are often underused due to limited availability, accessibility, and/or provider knowledge. Finally, relatively little attention has been paid to identifying and reducing disparities among individuals with screening-detected or incidentally detected lung nodules. This contribution to the American Cancer Society National Lung Cancer Roundtable Strategic Plan aims to identify and describe these knowledge gaps in lung nodule management and propose recommendations to advance clinical practice and research. Major themes that are addressed include improving the quality of evidence supporting lung nodule evaluation guidelines, strategically leveraging information technology, and placing emphasis on equitable approaches to nodule management. The recommendations outlined in this strategic plan, when carried out through interdisciplinary efforts with a focus on health equity, ultimately aim to improve early detection and reduce the morbidity and mortality of lung cancer. PLAIN LANGUAGE SUMMARY: Lung nodules may be identified on chest scans of individuals who undergo lung cancer screening (screening-detected nodules) or among patients for whom a scan was performed for another reason (incidental nodules). Although the vast majority of lung nodules are not lung cancer, it is important to have evidence-based, standardized approaches to the evaluation and management of a lung nodule. The primary aims of lung nodule management are to diagnose lung cancer while it is still in an early stage and to avoid unnecessary procedures and other harms.

Enhancing the differential diagnosis of small pulmonary nodules: a comprehensive model integrating plasma methylation, protein biomarkers, and LDCT imaging features.

BACKGROUND: Accurate differentiation between malignant and benign pulmonary nodules, especially those measuring 5-10 mm in diameter, continues to pose a significant diagnostic challenge. This study introduces a novel, precise approach by integrating circulating cell-free DNA (cfDNA) methylation patterns, protein profiling, and computed tomography (CT) imaging features to enhance the classification of pulmonary nodules. METHODS: Blood samples were collected from 419 participants diagnosed with pulmonary nodules ranging from 5 to 30 mm in size, before any disease-altering procedures such as treatment or surgical intervention. High-throughput bisulfite sequencing was used to conduct DNA methylation profiling, while protein profiling was performed utilizing the Olink proximity extension assay. The dataset was divided into a training set and an independent test set. The training set included 162 matched cases of benign and malignant nodules, balanced for sex and age. In contrast, the test set consisted of 46 benign and 49 malignant nodules. By effectively integrating both molecular (DNA methylation and protein profiling) and CT imaging parameters, a sophisticated deep learning-based classifier was developed to accurately distinguish between benign and malignant pulmonary nodules. RESULTS: Our results demonstrate that the integrated model is both accurate and robust in distinguishing between benign and malignant pulmonary nodules. It achieved an AUC score 0.925 (sensitivity = 83.7%, specificity = 82.6%) in classifying test set. The performance of the integrated model was significantly higher than that of individual methylation (AUC = 0.799, P = 0.004), protein (AUC = 0.846, P = 0.009), and imaging models (AUC = 0.866, P = 0.01). Importantly, the integrated model achieved a higher AUC of 0.951 (sensitivity = 83.9%, specificity = 89.7%) in 5-10 mm small nodules. These results collectively confirm the accuracy and robustness of our model in detecting malignant nodules from benign ones. CONCLUSIONS: Our study presents a promising noninvasive approach to distinguish the malignancy of pulmonary nodules using multiple molecular and imaging features, which has the potential to assist in clinical decision-making. TRIAL REGISTRATION: This study was registered on ClinicalTrials.gov on 01/01/2020 (NCT05432128). https://classic. CLINICALTRIALS: gov/ct2/show/NCT05432128 .

Comparison of lung cancer occurring in fibrotic versus non-fibrotic lung on chest CT.

PURPOSE: Evaluate the behavior of lung nodules occurring in areas of pulmonary fibrosis and compare them to pulmonary nodules occurring in the non-fibrotic lung parenchyma. METHODS: This retrospective review of chest CT scans and electronic medical records received expedited IRB approval and a waiver of informed consent. 4500 consecutive patients with a chest CT scan report containing the word fibrosis or a specific type of fibrosis were identified using the system M*Model Catalyst (Maplewood, Minnesota, U.S.). The largest nodule was measured in the longest dimension and re-evaluated, in the same way, on the follow-up exam if multiple time points were available. The nodule doubling time was calculated. If the patient developed cancer, the histologic diagnosis was documented. RESULTS: Six hundred and nine patients were found to have at least one pulmonary nodule on either the first or the second CT scan. 274 of the largest pulmonary nodules were in the fibrotic tissue and 335 were in the non-fibrotic lung parenchyma. Pathology proven cancer was more common in nodules occurring in areas of pulmonary fibrosis compared to nodules occurring in areas of non-fibrotic lung (34% vs 15%, p < 0.01). Adenocarcinoma was the most common cell type in both groups but more frequent in cancers occurring in non-fibrotic tissue. In the non-fibrotic lung, 1 of 126 (0.8%) of nodules measuring 1 to 6 mm were cancer. In contrast, 5 of 49 (10.2%) of nodules in fibrosis measuring 1 to 6 mm represented biopsy-proven cancer (p < 0.01). The doubling time for squamous cell cancer was shorter in the fibrotic lung compared to non-fibrotic lung, however, the difference was not statistically significant (p = 0.24). 15 incident lung nodules on second CT obtained ≤ 18 months after first CT scan was found in fibrotic lung and eight (53%) were diagnosed as cancer. CONCLUSIONS: Nodules occurring in fibrotic lung tissue are more likely to be cancer than nodules in the nonfibrotic lung. Incident pulmonary nodules in pulmonary fibrosis have a high likelihood of being cancer.

Diagnostic Nomogram Model for ACR TI-RADS 4 Nodules Based on Clinical, Biochemical Data and Sonographic Patterns.

OBJECTIVES: The objective of this study was to develop and validate a nomogram model integrating clinical, biochemical and ultrasound features to predict the malignancy rates of Thyroid Imaging Reporting and Data System 4 (TR4) thyroid nodules. METHODS: A total of 1557 cases with confirmed pathological diagnoses via fine-needle aspiration (FNA) were retrospectively included. Univariate and multivariate logistic regression analyses were conducted to identify independent predictors of malignancy. These predictors were incorporated into the nomogram model, and its predictive performance was evaluated using receiver-operating characteristic curve (AUC), calibration plots, net reclassification improvement (NRI), integrated discrimination improvement (IDI) and decision curve analysis (DCA). RESULTS: Eight out of 22 variables-age, margin, extrathyroidal extension, halo, calcification, suspicious lymph node metastasis, aspect ratio and thyroid peroxidase antibody-were identified as independent predictors of malignancy. The calibration curve demonstrated excellent performance, and DCA indicated favourable clinical utility. Additionally, our nomogram exhibited superior predictive ability compared to the current American College of Radiology (ACR) score model, as indicated by higher AUC, NRI, IDI, negative likelihood ratio (NLR) and positive likelihood ratio (PLR) values. CONCLUSIONS: The developed nomogram model effectively predicts the malignancy rate of TR4 thyroid nodules, demonstrating promising clinical applicability.

Overview of crosstalk between stromal and epithelial cells in the pathogenesis of adenomyosis and shared features with deep endometriotic nodules.

Since the first description of adenomyosis more than 150 years ago, multiple hypotheses have attempted to explain its pathogenesis. Indeed, research over recent years has greatly enhanced our knowledge of the underlying causes. This has opened up avenues for the development of strategies for both disease prevention and treatment of its main symptoms, such as pelvic pain, heavy menstrual bleeding, and infertility. However, the current means are still largely ineffective, so it is vital that we shed light on the pathways involved. Dysregulated mechanisms and aberrant protein expression have been identified as contributing factors in interactions between endometrial epithelial and stromal cells, ultimately leading to the growth of adenomyotic lesions. These include collective cell migration, epithelial-to-mesenchymal transition, hormonal influence, and signaling from non-coding RNAs and extracellular vesicles. We provide a concise summary of the latest insights into the crosstalk between glands and stroma in ectopic adenomyotic lesion formation. While there is an abundance of literature on similarities between adenomyosis and deep endometriosis, there are insufficient data on the cytochemical, molecular, and pathogenetic mechanisms of these two disorders. However, various shared features, including alterations of cell adhesion molecules, abnormal hormone regulation, and the presence of cancer-driving mutations and epigenetic modifications, have been identified. Nevertheless, the pathogenic mechanisms that contribute to the cause and development of these enigmatic diseases have not been fully elucidated yet.

Histologic correlates of "Choroidal abnormalities" in Neurofibromatosis type 1 (NF1).

Neurofibromatosis type 1 (NF1) is a rare autosomal dominant disorder characterized by proliferation of cells from neural crest origin. The most common manifestations are cutaneous, neurologic, skeletal and ocular. The distinction of NF1 from other syndromes with multiple café-au-lait macules may be difficult in the pediatric age group, and ocular findings, especially Lisch nodules (i.e., melanocytic hamartomas on the irides), are a useful, early diagnostic tool. In recent years, novel ocular manifestations descriptively referred to as "choroidal abnormalities", choroidal "hyperpigmented spots" and "retinal vascular abnormalities" have been recognized in NF1. Choroidal abnormalities (CA) appear as bright patchy nodules that can be best detected with near-infrared ocular coherence tomography imaging (NIR-OCT). Because of their high specificity and sensitivity for NF1, CA have been added as an ocular diagnostic criterion of NF1 as an alternative to Lisch nodules. Although CA are important ocular diagnostic criteria for NF1, the histologic correlates are controversial. We present the postmortem ocular pathology findings of an NF1 patient for whom clinical notes and ocular imaging were available. Findings in this patient included choroidal hyperpigmented spots on funduscopy and retinal vascular abnormalities, both of which have been reported to be closely associated with CA. Histologic examination of the eyes showed multiple clusters of melanocytes of varying sizes in the choroid. Pathologic review of 12 additional postmortem eyes from 6 NF1 patients showed multiple, bilateral choroidal melanocytic aggregates in all eyes. These findings suggest that the CA seen on NIR-OCT and the hyperpigmented spots seen clinically in NF1 patients are manifestations of multifocal choroidal melanocytic clusters, consistent with choroidal melanocytic hamartomas. Lisch nodules, often multiple, were present in all eyes with morphology that differed from the choroidal hamartomas. As such, although CA and Lisch nodules are melanocytic hamartomas, there are clear phenotypical differences in their morphologies.

Differential diagnosis of small hepatocellular nodules in cirrhosis: surrogate histological criteria of TERT promoter mutations.

AIMS: The differential diagnosis of small hepatocellular nodules in cirrhosis between dysplastic nodules and hepatocellular carcinoma (HCC) remains challenging on biopsy. As TERT promoter (pTERT) mutations may indicate the nodules already engaged in the malignant process, the aim of this study was to identify histological criteria associated with pTERT mutations by detecting these mutations by ddPCR in small formalin-fixed paraffin-embedded (FFPE) hepatocellular nodules arising in cirrhosis. METHODS AND RESULTS: We built a bicentric cohort data set of 339 hepatocellular nodules < 2 cm from cirrhotic samples, divided into a test cohort of 299 resected samples and a validation cohort of 40 biopsies. Pathological review, based on the evaluation of 14 histological criteria, classified all nodules. pTERT mutations were identified by ddPCR in FFPE samples. Among the 339 nodules, ddPCR revealed pTERT mutations in 105 cases (31%), including 90 and 15 cases in the test and validation cohorts, respectively. On multivariate analysis, three histological criteria were associated with pTERT mutations in the test cohort: increased cell density (P = 0.003), stromal invasion (P = 0.036) and plate-thickening anomalies (P < 0.001). With the combination of at least two of these major criteria, the AUC for predicting pTERT mutations was 0.84 in the test cohort (sensitivity: 86%, specificity: 83%) and 0.81 in the validation cohort (sensitivity: 87%, specificity: 76%). CONCLUSIONS: We identified three histological criteria as surrogate markers of pTERT mutations that may be used in routine biopsy to more clearly classify small hepatocellular nodules arising in cirrhosis.

Serum exosomal small nucleolar RNA (snoRNA) signatures as a predictive biomarker for benign and malignant pulmonary nodules.

Low-dose CT (LDCT) is increasingly recognized as the preferred method for detecting pulmonary nodules. However, distinguishing whether a nodule is benign or malignant often necessitates repeated scans or invasive tissue sampling procedures. Therefore, there is a pressing need for non-invasive techniques to minimize unnecessary interventions. This study aim to investigate the expression profile of exosomal snoRNA in the serum of patients with benign and malignant pulmonary nodules. We identified a total of 278 snoRNAs in serum exosomes, revealing significant differences in snoRNA levels between patients with malignant and benign nodules. Specifically, the upregulated snoRNAs U78 and U37 were validated through qRT-PCR and were found significantly elevated in the serum of patients with malignant pulmonary nodules, positioning them as promising biomarkers for the early detection of lung cancer. This study underscores the potential of serum exosomal U78 and U37 as critical tools for assessing the risk of pulmonary nodules identified through CT screening.

Radioiodine versus radiofrequency ablation to treat autonomously functioning thyroid nodules: a systematic review and comparative meta-analysis.

PURPOSE: Radioiodine (RAI) is a well-established first-line therapy for autonomously functioning thyroid nodules (AFTN). Radiofrequency ablation (RFA) is a minimally invasive procedure that has been proposed as an alternative treatment option for hyperthyroidism caused by AFTN. Although RFA has been shown to be useful for reducing nodule volume and improving TSH levels in AFTN, no comprehensive comparative clinical studies have been proposed to evaluate the overall response to RFA treatment. The aim of this comparative systematic review and meta-analysis was to evaluate the response of RAI and RFA treatments in AFTN. METHODS: A systematic search strategy was applied in PubMed, Web of Science, Scopus, Cochrane Library, and ClinicalTrials.gov until July 2023 without time or language restrictions. Studies investigating the response to RAI and/or RFA treatment in AFTN patients 6 and/or 12 months after treatment were included. The risk of bias was assessed based on the study design. Random-effect models were used for the meta-analysis. RESULTS: Twenty-three articles (28 reports) met the inclusion criteria and were included in the study. Overall, RAI therapy was found to have a significantly higher treatment response (94%) than RFA (59%), although the volume of AFTNs was reduced to a similar extent. In the direct comparison (n = 3 studies), RFA showed a higher risk of non-response than RAI (RR, 1.24; 95% CI, 0.94-1.63; z = 1.55; p = 0.12). CONCLUSIONS: Our results demonstrate the superiority of RAI over RFA in terms of success rates and safety profile and confirm RAI as the first choice for the treatment of AFTNs.

Thirty years of active surveillance for low-risk thyroid cancer, lessons learned and future directions.

Active Surveillance is a non-invasive strategy designed to identify a minority of patients with low-risk papillary thyroid carcinoma who might experience clinical progression and benefit from additional definitive treatments. Global experience suggests that these tumors typically show minimal changes in size during active surveillance, often demonstrating very slow growth or even size reduction. Moreover, the rate of lymph node metastases is low and can be effectively managed through rescue surgery, without impacting cancer-related mortality. However, despite 30 years of experience demonstrating the safety and feasibility of active surveillance for appropriately selected patients, this approach seems to have limited adoption in specific contexts. This limitation can be attributed to various barriers, including disparities in access to accurate information about the indolent nature of this disease and the prevalence of a maximalist mindset among certain patients and medical settings. This review aims to revisit the experience from the last three decades, provide current insights into the clinical outcomes of active surveillance trials, and propose a systematic approach for its implementation. Furthermore, it intends to emphasize the importance of precise patient selection and provides new perspectives in the field.

Thyroid ultrasound and its ancillary techniques.

Ultrasound (US) of the thyroid has been used as a diagnostic tool since the late 1960s. US is the most important imaging tool for diagnosing thyroid disease. In the majority of cases a correct diagnosis can already be made in synopsis of the sonographic together with clinical findings and basal thyroid hormone parameters. However, the characterization of thyroid nodules by US remains challenging. The introduction of Thyroid Imaging Reporting and Data Systems (TIRADSs) has improved diagnostic accuracy of thyroid cancer significantly. Newer techniques such as elastography, superb microvascular imaging (SMI), contrast enhanced ultrasound (CEUS) and multiparametric ultrasound (MPUS) expand diagnostic options and tools further. In addition, the use of artificial intelligence (AI) is a promising tool to improve and simplify diagnostics of thyroid nodules and there is evidence that AI can exceed the performance of humans. Combining different US techniques with the introduction of new software, the use of AI, FNB as well as molecular markers might pave the way for a completely new area of diagnostic accuracy in thyroid disease. Finally, interventional ultrasound using US-guided thermal ablation (TA) procedures are increasingly proposed as therapy options for benign as well as malignant thyroid diseases.

Humoral immune response to tumor-associated antigen Ubiquilin 1 (UBQLN1) and its tumor-promoting potential in lung cancer.

BACKGROUND: This study aims to investigate the expression of UBQLN1 in lung cancer (LC) tissue and the diagnostic capability of autoantibody to UBQLN1 (anti-UBQLN1) in the detection of LC and the discrimination of pulmonary nodules (PNs). METHODS: Sera from 798 participants were used to discover and validate the level of autoantibodies via HuProt microarray and Enzyme-linked immunosorbent assay (ELISA). Logistic regression analysis was applied to establish model. Receiver operating characteristic curve (ROC) analysis was performed to evaluate the diagnostic potential. Immunohistochemistry was performed to detect UBQLN1 expression in 88 LC tissues and 88 para-tumor tissues. qRT-PCR and western blotting were performed to detect the expression of UBQLN1 at the mRNA and protein levels, respectively. Trans-well assay and cell counting kit-8 (CCK-8) was used to investigate the function of UBQLN1. RESULTS: Anti-UBQLN1 was identified with the highest fold change by protein microarray. The level of anti-UBQLN1 in LC patients was obviously higher than that in NC or patients with benign lung disease of validation cohort 1 (P<0.05). The area under the curve (AUC) of anti-UBQLN1 was 0.610 (95%CI: 0.508-0.713) while reached at 0.822 (95%CI: 0.784-0.897) when combining anti-UBQLN1 with CEA, CYFRA21-1, CA125 and three CT indicators (vascular notch sign, lobulation sign and mediastinal lymph node enlargement) in the discrimination of PNs. UBQLN1 protein was overexpressed in lung adenocarcinoma (LUAD) tissues compared to para-tumor tissues. UBQLN1 knockdown remarkably inhibited the migration, invasion and proliferation of LUAD cell lines. CONCLUSIONS: Anti-UBQLN1 might be a potential biomarker for the diagnosis of LC and the discrimination of PNs.

Differentiation of granulomatous nodules with lobulation and spiculation signs from solid lung adenocarcinomas using a CT deep learning model.

BACKGROUND: The diagnosis of solitary pulmonary nodules has always been a difficult and important point in clinical research, especially granulomatous nodules (GNs) with lobulation and spiculation signs, which are easily misdiagnosed as malignant tumors. Therefore, in this study, we utilised a CT deep learning (DL) model to distinguish GNs with lobulation and spiculation signs from solid lung adenocarcinomas (LADCs), to improve the diagnostic accuracy of preoperative diagnosis. METHODS: 420 patients with pathologically confirmed GNs and LADCs from three medical institutions were retrospectively enrolled. The regions of interest in non-enhanced CT (NECT) and venous contrast-enhanced CT (VECT) were identified and labeled, and self-supervised labels were constructed. Cases from institution 1 were randomly divided into a training set (TS) and an internal validation set (IVS), and cases from institutions 2 and 3 were treated as an external validation set (EVS). Training and validation were performed using self-supervised transfer learning, and the results were compared with the radiologists' diagnoses. RESULTS: The DL model achieved good performance in distinguishing GNs and LADCs, with area under curve (AUC) values of 0.917, 0.876, and 0.896 in the IVS and 0.889, 0.879, and 0.881 in the EVS for NECT, VECT, and non-enhanced with venous contrast-enhanced CT (NEVECT) images, respectively. The AUCs of radiologists 1, 2, 3, and 4 were, respectively, 0.739, 0.783, 0.883, and 0.901 in the (IVS) and 0.760, 0.760, 0.841, and 0.844 in the EVS. CONCLUSIONS: A CT DL model showed great value for preoperative differentiation of GNs with lobulation and spiculation signs from solid LADCs, and its predictive performance was higher than that of radiologists.

The value of CT shape quantification in predicting pathological classification of lung adenocarcinoma.

OBJECTIVE: To evaluate whether quantification of lung GGN shape is useful in predicting pathological categorization of lung adenocarcinoma and guiding the clinic. METHODS: 98 patients with primary lung adenocarcinoma were pathologically confirmed and CT was performed preoperatively, and all lesions were pathologically ≤ 30 mm in size. On CT images, we measured the maximum area of the lesion's cross-section (MA). The longest diameter of the tumor (LD) was marked with points A and B, and the perpendicular diameter (PD) was marked with points C and D, which was the longest diameter perpendicular to AB. and D, which was the longest diameter perpendicular to AB. We took angles A and B as big angle A (BiA) and small angle A (SmA). We measured the MA, LD, and PD, and for analysis we derived the LD/PD ratio and the BiA/SmA ratio. The data were analysed using the chi-square test, t-test, ROC analysis, and binary logistic regression analysis. RESULTS: Precursor glandular lesions (PGL) and microinvasive adenocarcinoma (MIA) were distinguished from invasive adenocarcinoma (IAC) by the BiA/SmA ratio and LD, two independent factors (p = 0.007, p = 0.018). Lung adenocarcinoma pathological categorization was indicated by the BiA/SmA ratio of 1.35 and the LD of 11.56 mm with sensitivity of 81.36% and 71.79%, respectively; specificity of 71.79% and 74.36%, respectively; and AUC of 0.8357 (95% CI: 0.7558-0.9157, p < 0.001), 0.8666 (95% CI: 0.7866-0.9465, p < 0.001), respectively. In predicting the pathological categorization of lung adenocarcinoma, the area under the ROC curve of the BiA/SmA ratio combined with LD was 0.9231 (95% CI: 0.8700-0.9762, p < 0.001), with a sensitivity of 81.36% and a specificity of 89.74%. CONCLUSIONS: Quantification of lung GGN morphology by the BiA/SmA ratio combined with LD could be helpful in predicting pathological classification of lung adenocarcinoma.

Protect the recurrent laryngeal nerves in US-guided microwave ablation of thyroid nodules at Zuckerkandl tubercle: a pilot study.

BACKGROUND: To evaluate the safety and efficacy of US-guided microwave ablation in patients with thyroid nodules at Zuckerkandl tubercle. METHODS: 103 consecutive patients with thyroid nodules at Zuckerkandl tubercle (ZTTN) were enrolled in this study from November 2017 to August 2021. Prior to the surgery or US-guided microwave ablation (MWA), preoperative ultrasound visualization of the recurrent laryngeal nerve (RLN) and ZTTN was performed, the size and the position relationship between them were observed. Patients were followed up at 1, 3, 6, and 12 months after MWA and the volume reduction rates (VRR) of the thyroid nodules were analyzed. RESULTS: All patients successfully had the RLN and ZTTN detected using ultrasound before surgery or ablation with a detection rate of 100%. For the 103 patients, the majority of ZTTN grades were categorized as grade 2, with the distance from the farthest outside of ZTTN to the outer edge of thyroid ranging between 6.0 and 10.0 mm. The position relationship between ZTTN and RLN was predominantly type A in 98 cases, with type D observed in 5 cases. After MWA, the median nodule volume had significantly decreased from 4.61 (2.34, 8.70) ml to 0.42 (0.15, 1.41) ml and the VRR achieved 84.36 ± 13.87% at 12 months. No nodules regrew throughout the 12-month follow-up period. Of the 11 patients experienced hoarseness due to RLN entrapment before ablation, 7 recovered immediately after separation of the RLN and ZTTN during MWA, 2 recovered after one week, and the other 2 recovered after two months. CONCLUSIONS: The RLN is closely related to ZTTN and mainly located at the back of ZTTN. The RLN can be separated from ZTTN by hydrodissection during MWA. US-guided MWA is a safe and effective treatment for ZTTN.

Assessment of Lung Nodule Detection and Lung CT Screening Reporting and Data System Classification Using Zero Echo Time Pulmonary MRI.

BACKGROUND: The detection rate of lung nodules has increased considerably with CT as the primary method of examination, and the repeated CT examinations at 3 months, 6 months or annually, based on nodule characteristics, have increased the radiation exposure of patients. So, it is urgent to explore a radiation-free MRI examination method that can effectively address the challenges posed by low proton density and magnetic field inhomogeneities. PURPOSE: To evaluate the potential of zero echo time (ZTE) MRI in lung nodule detection and lung CT screening reporting and data system (lung-RADS) classification, and to explore the value of ZTE-MRI in the assessment of lung nodules. STUDY TYPE: Prospective. POPULATION: 54 patients, including 21 men and 33 women. FIELD STRENGTH/SEQUENCE: Chest CT using a 16-slice scanner and ZTE-MRI at 3.0T based on fast gradient echo. ASSESSMENT: Nodule type (ground-glass nodules, part-solid nodules, and solid nodules), lung-RADS classification, and nodule diameter (manual measurement) on CT and ZTE-MRI images were recorded. STATISTICAL TESTS: The percent of concordant cases, Kappa value, intraclass correlation coefficient (ICC), Wilcoxon signed-rank test, Spearman's correlation, and Bland-Altman. The p-value <0.05 is considered significant. RESULTS: A total of 54 patients (age, 54.8 ± 11.9 years; 21 men) with 63 nodules were enrolled. Compared with CT, the total nodule detection rate of ZTE-MRI was 85.7%. The intermodality agreement of ZTE-MRI and CT lung nodules type evaluation was substantial (Kappa = 0.761), and the intermodality agreement of ZTE-MRI and CT lung-RADS classification was moderate (Kappa = 0.592). The diameter measurements between ZTE-MRI and CT showed no significant difference and demonstrated a high degree of interobserver (ICC = 0.997-0.999) and intermodality (ICC = 0.956-0.985) agreements. DATA CONCLUSION: The measurement of nodule diameter by pulmonary ZTE-MRI is similar to that by CT, but the ability of lung-RADS to classify nodes from MRI images still requires further research. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY: Stage 2.

Atypical placental site nodules: Clinicopathologic features, management and patient outcomes in an institutional series.

OBJECTIVE: To report the New England Trophoblastic Disease Center (NETDC) experience with atypical placental site nodules (APSN). METHODS: The NETDC registry was reviewed from 2005 to 2022 and clinical data abstracted. Expert pathologists in GTD reviewed available slides with concurrent immunohistochemical analysis. Targeted deep sequencing was performed for four cases. RESULTS: Among 35 cases of APSN identified, 29 had clinical and demographic data available. Abnormal uterine bleeding (59.3%) was the most common presenting symptom. Most women (79.3%) had an antecedent live birth. Two cases were incidentally diagnosed after hysterectomy for other indications, and one case lost to follow-up. Among the remaining 26 cases, 11 (42.3%) opted for hysterectomy and 15 for re-sampling (57.7%), among whom 3 later underwent hysterectomy for persistent APSN. Subsequent obstetrical outcomes included 3 spontaneous abortions, 1 therapeutic abortion, 1 ectopic pregnancy, 2 cesarean sections, 1 cesarean hysterectomy, and 1 spontaneous vaginal delivery. Subsequent pathology was available for 26 cases: 4 epithelioid trophoblastic tumors (15.4%), 9 APSN (34.6%), 3 PSN (11.5%), and 10 without abnormalities (38.4%). Histopathologic characteristics of APSN included moderate to severe cytologic atypia, median Ki-67 proliferation index of 8%, and typical immunohistochemical profiles (diffuse or multifocal positivity for p63 and GATA-3 and absent or focal CD146). No histopathologic feature predicted ETT. Among 4 sequenced cases, no recurrent genomic features were identified. CONCLUSIONS: APSN is a rare form of gestational trophoblastic proliferation with uncertain malignant potential. While normal obstetric outcomes are possible, the persistence rate is high, and definitive management remains hysterectomy.