Small Nodules Research Articles

Development and external validation of a multimodal integrated feature neural network (MIFNN) for the diagnosis of malignancy in small pulmonary nodules (≤10 mm)

Objectives. Current lung cancer screening protocols primarily evaluate pulmonary nodules, yet often neglect the malignancy risk associated with small nodules (≤10 mm). This study endeavors to optimize the management of pulmonary nodules in this population by devising and externally validating a Multimodal Integrated Feature Neural Network (MIFNN). We hypothesize that the fusion of deep learning algorithms with morphological nodule features will significantly enhance diagnostic accuracy. Materials and Methods. Data were retrospectively collected from the Lung Nodule Analysis 2016 (LUNA16) dataset and four local centers in Beijing, China. The study includes patients with small pulmonary nodules (≤10 mm). We developed a neural network, termed MIFNN, that synergistically combines computed tomography (CT) images and morphological characteristics of pulmonary nodules. The network is designed to acquire clinically relevant deep learning features, thereby elevating the diagnostic accuracy of existing models. Importantly, the network’s simple architecture and use of standard screening variables enable seamless integration into standard lung cancer screening protocols. Results. In summary, the study analyzed a total of 382 small pulmonary nodules (85 malignant) from the LUNA16 dataset and 101 small pulmonary nodules (33 malignant) obtained from four specialized centers in Beijing, China, for model training and external validation. Both internal and external validation metrics indicate that the MIFNN significantly surpasses extant state-of-the-art models, achieving an internal area under the curve (AUC) of 0.890 (95% CI: 0.848–0.932) and an external AUC of 0.843 (95% CI: 0.784–0.891). Conclusion. The MIFNN model significantly enhances the diagnostic accuracy of small pulmonary nodules, outperforming existing benchmarks by Zhang et al with a 6.34% improvement for nodules less than 10 mm. Leveraging advanced integration techniques for imaging and clinical data, MIFNN increases the efficiency of lung cancer screenings and optimizes nodule management, potentially reducing false positives and unnecessary biopsies. Clinical relevance statement. The MIFNN enhances lung cancer screening efficiency and patient management for small pulmonary nodules, while seamlessly integrating into existing workflows due to its reliance on standard screening variables.

A novel entity of HIPK2::YAP1 pulmonary fibromatosis

BackgroundPulmonary fibromatosis (PF) is a specific variant of fibromatosis, which is rarely reported occurring in the lung. PF with HIPK2-YAP1 fusion was a novel entity.Case presentationIn this report, a 66-year-old male with PF had been smoking over 40 years. Multiple cords and small nodules in both lungs had been detected in a health examination two years earlier at our hospital. But approximately twofold enlarged in the lingual segment of the upper lobe in the left lung were disclosed in this year. Immunohistochemical analysis demonstrated that the vimentin and β-Catenin were positive in the largest nodule. After underwent a DNA/RNA panel next-generation sequencing (NGS), missense mutations and HIPK2-YAP1 fusion were found in this sample. Ultimately, the case diagnosis as PF with HIPK2-YAP1 fusion after multidisciplinary treatment. Currently, the patient is doing well and recurrence-free at 14 months post-surgery.ConclusionsIt’s difficult for patients with complex morphology to make accurate diagnosis solely based on morphology and immunohistochemistry. But molecular detection is an effective method for further determining pathological subtypes.

Oesophageal haematoma in a Cairn terrier presenting for impaired swallowing, retching and cervical pain

AbstractA 13‐year‐old spayed female Cairn terrier was referred for surgical resection of a large oesophageal mass. The dog was initially presented to the primary care veterinarian for several days of gagging. The mass was initially diagnosed on thoracic radiographs and confirmed via computed tomography and oesophagoscopy. Endoscopic biopsies were performed that were consistent with oesophagitis. The dog was then referred to The Ohio State University Veterinary Medical Center for surgical resection of the mass. On surgical approach, a small nodule was palpable in the oesophagus; however, a large mass was not found. Oesophagoscopy was repeated intraoperatively, which revealed a small nodule in the same region of the previously described mass. The small nodule was removed, and histopathology was consistent with lymphohistiocytic inflammation and previous haemorrhage, consistent with an oesophageal haematoma. The dog made a full recovery post‐operatively, with continued resolution of clinical signs reported 5 months after surgery.

Augmented fluoroscopy-guided dye localization for small pulmonary nodules in hybrid operating room: intrathoracic stamping versus transbronchial marking.

We developed a novel augmented fluoroscopy-guided intrathoracic stamping technique for localizing small pulmonary nodules in the hybrid operating room. We conducted an observational study to investigate the feasibility of this technique and retrospectively compared two augmented fluoroscopy-guided approaches: intrathoracic and transbronchial. From August 2020 to March 2023, consecutive patients underwent single-stage augmented fluoroscopy-guided localization under general anaesthesia. This included intrathoracic stamping and bronchoscopic lung marking, followed by thoracoscopic resection in a hybrid operating room. Comparative analyses were performed between the two groups. The data of 50 patients in the intrathoracic stamping and 67 patients in the bronchoscopic lung marking groups were analysed. No significant difference was noted in demographic data between the groups, except a larger lesion depth in the bronchoscopic lung marking group (14.7 ± 11.7 vs 11.0 ± 5.8mm, p = 0.029). Dye localization was successfully performed in 49 intrathoracic stamping group patients (98.0%) and 67 bronchoscopic lung marking group patients (100%). No major procedure-related complications occurred in either group; however, the time flow (total anaesthesia time/global operating room time) was longer, and the radiation exposure (fluoroscopy duration/total dose area product) was larger in the bronchoscopic lung marking group. Augmented fluoroscopic stamping localization under intubated general anaesthesia is feasible and safe, providing an alternative with less global operating room time and lower radiation exposure for image-guided thoracoscopic surgery in the hybrid operating room.

Robot-Assisted Bronchoscopy for Identification of Lung Nodules During Minimally Invasive Pulmonary Resection.

Small pulmonary nodules can be difficult to identify during minimally invasive surgical (MIS) resection. Previous investigators have reported using standard bronchoscopy with electromagnetic navigation to identify small pulmonary nodules. Robot-assisted bronchoscopy has been introduced into clinical practice and has shown utility for the biopsy of small lesions. We report our experience using robot-assisted bronchoscopy with dye marking to aid in minimally invasive pulmonary resection. Patients with peripheral pulmonary nodules underwent robot-assisted bronchoscopy before a planned minimally invasive resection. Indocyanine green or methylene blue was injected directly into the targeted lesion. Surgical resection was then immediately performed. Success was defined as dye visualization leading to sublobar resection of the target nodule without the need for lobectomy or thoracotomy. Thirty patients with a single targeted nodule underwent robot-assisted bronchoscopy followed by MIS resection. The median lesion size was 9 mm (4 to 25 mm), and the median distance from the pleura was 5 mm (1 to 32 mm). The success rate was 83.3% (25 of 30). There were 3 cases in which the dye was not visualized, and in 2 cases there was free extravasation of dye. The targeted nodule was identified in these 5 patients without the need for thoracotomy or lobectomy. Pathology revealed non-small cell lung cancer (n = 13, 43.3%), metastatic disease (n = 11, 36.7%), and benign disease (n = 6, 20%). There were no complications related to the use of robot-assisted bronchoscopy. Robot-assisted bronchoscopy with dye marking is safe and effective for guiding minimally invasive resection of small peripheral pulmonary nodules.

Inverted Follicular Keratosis in the Post-Auricular Region: A Case Report

Inverted Follicular Keratosis in the Post-Auricular Region: A Case Report

Camper’s and Scarpa’s fasciae: Anatomic landmark to differentiate between lymph node and abdominal wall involvement in a case of lymphoma

Cutaneous involvement of MALT lymphoma can either be primary or secondary, Secondary spread to the skin is considered disseminated extra-nodal disease involvement, which is classifies as a stage IV disease. We described a case of a 44-year-old woman with MALT lymphoma of the lacrimal glands with biopsy-proven lymphoma involvement in the subcutaneous tissue of the anterior abdominal wall. This involvement is manifested as multiple small discrete solid enhancing subcutaneous nodules. Although such findings on conventional CT scans are usually non-specific and may present in various systemic conditions, the knowledge of the patient’s prior clinical history should alert interpreting radiologists to be aware of cutaneous and subcutaneous involvement of lymphoma. This awareness can help plan the use of imaging-guided tissue biopsy for a minimally-invasive and safe acquisition of tissue specimen for histopathological diagnosis.

Localized multisystem inflammatory syndrome in children (mis-c), faster recovery outcome: a case report

Backgrounds: MIS-C cases emerged approximately 4–5 weeks on average after the peak prevalence of COVID-19. The symptoms could be asymptomatic or mildly symptomatic with fever and cough. It was unknown if these infants’ exhibited symptoms of Kawasaki disease (KD) or toxic shock syndrome (TSS), or whether they represented a condition associated with the continuing COVID-19 epidemic. Objective: To describe clinical outcome and examination results of localized multisystem inflammatory syndrome in children. Case presentation: A 23-month-old boy was brought to the pediatric allergy immunology clinic as a referral from a pediatrician with complaints of lump on right preauricular region, which was redden and painful, feels warm, and difficulty opening mouth. There were also multiple small nodules in peri anal area. There was fever for 1 week before admitted, accompanied by a runny nose with clear secretions with no cough. Fever already resolved at presentation. Tonsils are enlarged to T3/T4 without hyperemic nor injection. The presence of fever, conjunctivitis and cracked lips mimicking Kawasaki disease, but electrocardiography and echocardiography were normal. The MISC panel was shown support for MISC, wherein CBC showed presence of lymphopenia, anemia, neutrophilia, and thrombocytosis. Other panel MISC like the erythrocytes sedimentation rate, quantitative CRP, D-dimer, and quantitative IgG SARS-COV-2 antibodies it was reported to be increased. The patient was treated with intravenous high doses methylprednisolone pulse 10 mg/kg, then tapered off before stopped. The lump was disappeared after the second dose of HDMP, and patient was discharged after 7 days of admission. Conclusion: We reported a localized Multisystem Inflammatory Syndrome (MIS-C) treated with high dose methylprednisolone resulting in fast recovery.

The application of Raman spectroscopy for the diagnosis and monitoring of lung tumors.

Raman spectroscopy is an optical technique that uses inelastic light scattering in response to vibrating molecules to produce chemical fingerprints of tissues, cells, and biofluids. Raman spectroscopy strategies produce high levels of chemical specificity without requiring extensive sample preparation, allowing for the use of advanced optical tools such as microscopes, fiber optics, and lasers that operate in the visible and near-infrared spectral range, making them increasingly suitable for a wide range of medical diagnostic applications. Metal nanoparticles and nonlinear optical effects can improve Raman signals, and optimized fiber optic Raman probes can make real-time, in vivo, single-point observations. Furthermore, diagnostic speed and spatial accuracy can be improved through the multimodal integration of Raman measurements and other technologies. Recent studies have significantly contributed to the improvement of diagnostic speed and accuracy, making them suitable for clinical application. Lung cancer is a prevalent type of respiratory malignancy. However, the use of computed tomography for detection and screening frequently reveals numerous smaller lung nodules, which makes the diagnostic process more challenging from a clinical perspective. While the majority of small nodules detected are benign, there are currently no direct methods for identifying which nodules represent very early-stage lung cancer. Positron emission tomography and other auxiliary diagnostic methods for non-surgical biopsy samples from these small nodules yield low detection rates, which might result in significant expenses and the possibility of complications for patients. While certain subsets of patients can undergo curative treatment, other individuals have a less favorable prognosis and need alternative therapeutic interventions. With the emergence of new methods for treating cancer, such as immunotherapies, which can potentially extend patient survival and even lead to a complete cure in certain instances, it is crucial to determine the most suitable biomarkers and metrics for assessing the effectiveness of these novel compounds. This will ensure that significant treatment outcomes are accurately measured. This review provides a comprehensive overview of the prospects of Raman spectroscopy and its applications in the diagnosis and analysis of lung tumors.

MRUNet-3D: A multi-stride residual 3D UNet for lung nodule segmentation

Obtaining an accurate segmentation of the pulmonary nodules in computed tomography (CT) images is challenging. This is due to: (1) the heterogeneous nature of the lung nodules; (2) comparable visual characteristics between the nodules and their surroundings. A robust multi-scale feature extraction mechanism that can effectively obtain multi-scale representations at a granular level can improve segmentation accuracy. As the most commonly used network in lung nodule segmentation, UNet, its variants, and other image segmentation methods lack this robust feature extraction mechanism. In this study, we propose a multi-stride residual 3D UNet (MRUNet-3D) to improve the segmentation accuracy of lung nodules in CT images. It incorporates a multi-slide Res2Net block (MSR), which replaces the simple sequence of convolution layers in each encoder stage to effectively extract multi-scale features at a granular level from different receptive fields and resolutions while conserving the strengths of 3D UNet. The proposed method has been extensively evaluated on the publicly available LUNA16 dataset. Experimental results show that it achieves competitive segmentation performance with an average dice similarity coefficient of 83.47 % and an average surface distance of 0.35 mm on the dataset. More notably, our method has proven to be robust to the heterogeneity of lung nodules. It has also proven to perform better at segmenting small lung nodules. Ablation studies have shown that the proposed MSR and RFIA modules are fundamental to improving the performance of the proposed model.

Numerical Simulation of Cathode Nodule Local Effects

As one of the main factors decreasing current efficiency and product quality, the growth of nodules deserves attention in the copper electrorefining process. Three-dimensional (3D) Finite Element Method models combining tertiary current distribution and fluid flow were established in this study to investigate the details of the growth of columnar nodules, including the electrolyte flow around the nodule and its effects. Compared with an inert nodule, a significant impact of the electrochemical reaction of an active nodule has been observed on the fluid flow, which may be one of the reasons for the formation of small nodule clusters on the cathode. Furthermore, the local current density is not even on the nodule surface under the comprehensive influence of local electrolyte flow, local overvoltage, and the angle with the anode surface. Thus, the head of an active nodule grows faster than the root, and the upper parts grow faster than the lower parts, leading to asymmetric growth of the nodules.

YOLO-MSRF for lung nodule detection

(Aim) Aiming at the problem that there are a large number of small object nodules that are difficult to detect in lung images, detection methods based on improved YOLOv7 are proposed in this paper. (Method) First, a new small object detection layer (SODL) is proposed to solve the problem of the small size and irregular shape of lung nodules being difficult to detect accurately. Secondly, aiming at the problem that the characteristics of lung nodules are blurred and difficult to detect due to the continuous downsampling of the model, a multi-scale receptive field (MSRF) module is proposed and designed to improve the model's extraction of channel features. Finally, efficient omni-dimensional convolution (EODConv) is used to improve the ability of the network to extract the space, filters, and channels of the convolution kernel. (Results) Experiments were carried out on the public Luna16 dataset, and the results showed that our mAP, precision, and recall rate reached 95.26 %, 95.41 %, and 94.02 %, respectively, surpassing many state-of-the-art models. (Conclusion) In this study, a YOLOv7-based method is proposed for detecting lung nodules. Experimental results show that the proposed modification can significantly improve detection performance and is more suitable for clinical medical diagnosis.

The use of diagnostic complex robotic-assisted segmentectomy in the management of incidental and screen-detected pulmonary nodules.

Robotic-assisted thoracoscopic surgery (RATS) facilitates complex pulmonary segmentectomy which offers one-stage diagnostic and therapeutic management of small pulmonary nodules. We aimed to explore the potential advantages of a faster, simplified pathway and earlier diagnosis against the disadvantages of unnecessary morbidity in benign cases. In an observational study, patients with small, solitary pulmonary nodules deemed suspicious of malignancy by a multidisciplinary team were offered surgery without a pre or intraoperative biopsy. We report our initial experience with RATS complex segmentectomy (using >1 parenchymal staple line) to preserve as much functioning lung tissue as possible. Over a 4-year period, 245 RATS complex segmentectomies were performed; 140 right: 105 left. A median of 2 (1-4) segments was removed. There was no in-hospital mortality and no requirement for postoperative ventilation. Complications were reported in 63 (25.7%) cases, of which 36 (57.1%) were hospital-acquired pneumonia. A malignant diagnosis was found in 198 (81%) patients and a benign diagnosis in 47 (19%). The malignant diagnoses included: adenocarcinoma in 136, squamous carcinoma in 31 and carcinoid tumour in 15. The most frequent benign diagnosis was granulomatous inflammation in 18 cases. RATS complex segmentectomy offers a precise, safe and effective one-stop therapeutic biopsy in incidental and screen-detected pulmonary nodules.

Chemical Localization With Robotic Bronchoscopy: Can It Aid Resection of Subsolid Lung Nodules?

IntroductionSubsolid nodules or those located deep in lung parenchyma are difficult to localize using minimally invasive thoracic surgery. While image-guided percutaneous needle localization has been performed, it is inconvenient and has potential complications. In this study, the role of chemical localization using robotic bronchoscopy to facilitate resection was evaluated. MethodsConsecutive patients undergoing surgical resection for lung nodules between 8/2019-3/2022 were included. Patients with subsolid lung nodules, or small nodules deep in lung parenchyma that were deemed difficult to localize, were chemically localized (CL) using robotic bronchoscopy before resection. Clinico-demographic data were obtained retrospectively using a prospectively maintained database. ResultsLocalization of lung nodules before resection was performed in 139 patients while 110 patients were not localized. Daily activity score was higher for localized patients. Nodules in the localized group were smaller (P < 0.001) and had similar solid:ground glass ratio. In the localized group, larger margins were observed, and no re-resection of the parenchymal margin was required. Twenty patients in the non-localized group required re-resection intraoperatively due to close pathological margins or inability to locate the nodule in the resected specimen. Operative time was a median of 10-15 min longer for localized patients, P < 0.001. Length of stay was shorter in the localized group (P < 0.05). ConclusionsChemical localization of lung nodules using robotic bronchoscopy appears to be a safe and effective method of identifying the location of nodules with small size and less density and aids increased tumor margins intraoperatively.

Incidence and risk factors for pulmonary hemorrhage after percutaneous CT-guided pulmonary nodule biopsy: an observational study

To evaluate the current incidence of pulmonary hemorrhage and the potential factors contributing to its increased risk after percutaneous CT-guided pulmonary nodule biopsy and to summarize the technical recommendations for its treatment. In this observational study, patient data were collected from ten medical centers from April 2021 to April 2022. The incidence of pulmonary hemorrhage was as follows: grade 0, 36.1% (214/593); grade 1, 36.8% (218/593); grade 2, 18.9% (112/593); grade 3, 3.5% (21/593); and grade 4, 4.7% (28/593). High-grade hemorrhage (HGH) occurred in 27.2% (161/593) of the patients. The use of preoperative breathing exercises (PBE, p =0.000), semiautomatic cutting needles (SCN, p = 0.004), immediate contrast enhancement (ICE, p =0.021), and the coaxial technique (CoT, p = 0.000) were found to be protective factors for HGH. A greater length of puncture (p =0.021), the presence of hilar nodules (p = 0.001), the presence of intermediate nodules (p = 0.026), a main pulmonary artery diameter (mPAD) larger than 29 mm (p = 0.015), and a small nodule size (p = 0.014) were risk factors for high-grade hemorrhage. The area under the curve (AUC) was 0.783. These findings contribute to a deeper understanding of the risks associated with percutaneous CT-guided pulmonary nodule biopsy and provide valuable insights for developing strategies to minimize pulmonary hemorrhage.

The value of a neural network based on multi-scale feature fusion to ultrasound images for the differentiation in thyroid follicular neoplasms

ObjectiveThe objective of this research was to create a deep learning network that utilizes multiscale images for the classification of follicular thyroid carcinoma (FTC) and follicular thyroid adenoma (FTA) through preoperative US.MethodsThis retrospective study involved the collection of ultrasound images from 279 patients at two tertiary level hospitals. To address the issue of false positives caused by small nodules, we introduced a multi-rescale fusion network (MRF-Net). Four different deep learning models, namely MobileNet V3, ResNet50, DenseNet121 and MRF-Net, were studied based on the feature information extracted from ultrasound images. The performance of each model was evaluated using various metrics, including sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), accuracy, F1 value, receiver operating curve (ROC), area under the curve (AUC), decision curve analysis (DCA), and confusion matrix.ResultsOut of the total nodules examined, 193 were identified as FTA and 86 were confirmed as FTC. Among the deep learning models evaluated, MRF-Net exhibited the highest accuracy and area under the curve (AUC) with values of 85.3% and 84.8%, respectively. Additionally, MRF-Net demonstrated superior sensitivity and specificity compared to other models. Notably, MRF-Net achieved an impressive F1 value of 83.08%. The curve of DCA revealed that MRF-Net consistently outperformed the other models, yielding higher net benefits across various decision thresholds.ConclusionThe utilization of MRF-Net enables more precise discrimination between benign and malignant thyroid follicular tumors utilizing preoperative US.

Abstract 3063: Defining oncogene-specific metabolic vulnerabilities in a mouse model of hepatocellular carcinoma

Abstract Despite the continued success of advanced cancer therapies, hepatocellular carcinoma (HCC) represents a substantial challenge to current treatment modalities that are not sufficiently effective for the management of advanced disease. Metabolic reprogramming is a hallmark of cancer and many oncogenic signaling pathways impact on cellular metabolism. Here, we are investigating changes in metabolism in different oncogene-driven mouse models of liver cancer to identify selective metabolic vulnerabilities associated with HCC that could be implicated in tumor initiation and progression to be exploited for cancer therapy. Transposon-based vectors coding for different combinations of oncogenes, either Myc and Akt1Myr (CaMIA) or Myc and NrasG12V (CaMIN), were transduced by hydrodynamic tail vein injected into C57BL/6 mice. The resulting liver tumors and control livers were subjected to a comprehensive profiling of polar metabolites (metabolomics) and lipids (lipidomics and total fatty acids) as well as changes in gene expression (transcriptomics). Despite similar overall survival, the two models display marked differences in the presentation of the tumors, with CaMIA showing larger aggressive tumors, while CaMIN livers contain numerous small tumor nodules. Both models also showed evidence for the deregulation of intermediate metabolism, indicating activation of aerobic glycolysis and deregulation of glutamine metabolism. Lipidomic analysis revealed substantial lipidome remodeling in both models. Oncogene-specific alterations included elevated levels of lysophosphatidylcholine (LPC) in CaMIN tumors, while CaMIA tumors displayed high levels of ether phospholipids compared to CaMIN and normal liver. Moreover, the fraction of polyunsaturated fatty acids (PUFAs) was enhanced in lipids from CaMIN tumors, while monounsaturated fatty acids (MUFAs) were enriched in CaMIA tumors. Furthermore, tumors from both genotypes produced higher levels of oxylipins, a class of lipid mediators involved in signaling and inflammation, compared to normal liver. Transcriptome analysis confirmed these metabolic alterations and revealed evidence for enhanced inflammatory signaling in CaMIN. In addition, analysis of tumor microenvironment composition disclosed specific differences in stromal components, indicative of immune evasion through checkpoint activation. Experiments in primary murine liver cancer cell lines confirmed oncogene-specific metabolic rearrangements and suggest elevated sensitivity towards inhibitors of lipid remodeling. Future experiments will investigate the role of altered lipid metabolism in tumor development and immune evasion in liver cancer. Citation Format: Kamal Al-Shami, Marteinn Snaebjornsson, Felix Vogel, Lisa Schlicker, Phillip Pöller, Daniel Dauch, Almut Schulze. Defining oncogene-specific metabolic vulnerabilities in a mouse model of hepatocellular carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3063.

Intelligent diagnosis of lung nodule images based on machine learning in the context of lung teaching.

The vast majority of intelligent diagnosis models have widespread problems, which seriously affect the medical staff judgment of patients' injuries. So depending on the situation, you need to use different algorithms, The study suggests a model for intelligent diagnosis of lung nodule images based on machine learning, and a support vector machine-based machine learning algorithm is selected. In order to improve the diagnostic accuracy of intelligent diagnosis of lung nodule images as well as the diagnostic model of lung nodule images. The objectives are broken down into algorithm determination and model construction, and the proposed optimized model is solved using machine learning techniques in order to achieve the original algorithm selected for intelligent diagnosis of lung nodule photos. The validation findings demonstrated that dimensionality reduction of the features produced 17 × 1120 and 17 × 2980 non-node matrices with 1216 nodes and 3407 non-nodes in 17 features. The support vector machine classification method has more benefits in terms of accuracy, sensitivity, and specificity when compared to other classification methods. Since there were some anomalies among both benign and malignant tumors and no discernible difference between them, the distribution of median values revealed that the data was symmetrical in terms of texture and gray scale. Non-small nodules can be identified from benign nodules, but more training is needed to separate them from the other 2 types. Pulmonary nodules are a common disease. MN are distinct from the other 2 types, non-small nodules and benign small nodules, which require further training to differentiate. This has great practical value in teaching practice. Therefore, building a machine learning-based intelligent diagnostic model for pulmonary nodules is of significant importance in helping to solve medical imaging diagnostic problems.

Exploring the Diagnostic Dilemma of Indeterminate Pulmonary Nodules in Patients with Primary Sarcoma of Bone.

Bone sarcomas are known to have a predilection for pulmonary metastasis. Surveillance protocols are thus focused on periodic chest imaging, typically with CT scan. Pulmonary nodules can be easily identified with this modality, but smaller nodules are not readily biopsied and may not represent metastatic disease. These are called indeterminate. The natural history of indeterminate nodules in a bone sarcoma population and factors associated with progression to true metastatic disease are not clearly defined. All bone sarcoma patients treated at a single institution from 2010 to 2020 were eligible for inclusion. We treated 327 patients over this period; 119 were excluded for age less than 16 years, 31 were excluded for evident metastatic disease at presentation, and 60 were excluded for incomplete clinical follow-up or CT chest imaging either at staging or in surveillance. We assessed chest CT images for presence of pulmonary nodules and selected variables both at the staging and on surveillance images. Nodules were considered metastatic if proven histologically with a biopsy or by clinical interpretation by the multidisciplinary sarcoma team. Clinical and imaging factors were assessed for the association of indeterminate nodule progression to true metastatic disease. Seventy three of the 117 patients had indeterminate nodules on their staging CT scan; 41.1% of those patients progressed to metastatic disease compared to 43.2% of the patients that did not have indeterminate nodules on staging CT. Fifty eight of the 117 patients developed indeterminate nodules on surveillance chest CT, and 55.2% of those patients progressed to metastatic disease. There were no clinical or imaging factors that predicted the development of metastatic disease in the group that had indeterminate nodules at presentation; however, the number and size of nodules did correlate with progression to metastasis in those that developed indeterminate nodules on surveillance. Indeterminate pulmonary nodules are common on staging CT scans in patients with a bone sarcoma. The presence or absence of these indeterminate nodules was not predictive of progression to true metastatic disease in this cohort. However, the development of indeterminate nodules on surveillance imaging was associated with progression to metastatic disease with the size and number of nodules being important factors.

Clinical analysis of 4 children with cryptogenic organizing pneumonia

Objective: To analyze the clinical features of children with cryptogenic organizing pneumonia (COP) confirmed by pathology. Methods: The clinical manifestations, imaging, pathology, treatment and outcome data of 4 children with COP confirmed by thoracoscopic lung biopsy were retrospectively analyzed, who were hospitalized at Respiratory Department of Shenzhen Children's Hospital from January 2004 to December 2022. Results: All of the 4 patients were male, the age ranged from 1 year 3 months to 14 years. The time from onset to diagnosis was 3 months to 3 years. The follow-up duration was 6 months to 6 years. All the 4 cases had cough, 2 cases had tachypnea and wheezing, 1 case had expectoration, 1 case had chest pain, 1 case had decreased activity tolerance and weight loss. Rales in 2 cases and hypoxemia in 1 case. Pulmonary high resolution CT showed diffuse distribution, involvement of both lungs in 3 cases, and single lung combined migration in 1 case.Three cases showed ground-glass opacity, consolidation, patchy or fibrous strips, and 1 case presented air bronchogram and "reversed halo sign". All the 4 cases were performed thoracoscopic lung biopsy, and the pathological findings showed cellulose exudate or small nodules filled with granulation tissue or fibroblasts in the alveolar cavity and small airways, and 1 case was Masson corpuscle positive. Three patients achieved remission after glucocorticoid therapy. Spontaneous remission without treatment was seen in 1 patient.Two cases were followed up for 17 months and 6 years, respectively, who had excellent outcome. Conclusions: The manifestations of COP in children include cough, expectoration and chest pain. Infants and young children may have tachypnea and wheezing. The most common chest CT findings are diffuse distribution of ground-glass opacity, patchy and consolidation in both lungs. Diagnosis should depend on pathological examination. The effect of glucocorticoid therapy is good.