Reply to Moran-Mendoza and Khalil: Are Ground-Glass Opacities on Chest High-Resolution Computed Tomography a Manifestation of Airway Disease?
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ABSTRACT:
SUBMITTER: Remy-Jardin M
PROVIDER: S-EPMC7958512 | biostudies-literature | 2021 Mar
REPOSITORIES: biostudies-literature
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Reply to Morán-Mendoza and Khalil: Are Ground-Glass Opacities on Chest High-Resolution Computed Tomography a Manifestation of Airway Disease?
Remy-Jardin Martine M Wilson Kevin C KC Raghu Ganesh G
American journal of respiratory and critical care medicine 20210301 6
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Project description: Not available
| S-EPMC7958520 | biostudies-literature
Project description:ObjectiveTo explore the correlation between radiomic features and the pathology of pure ground-glass opacities (pGGOs), we established a radiomics model for predicting the pathological subtypes of minimally invasive adenocarcinoma (MIA) and precursor lesions.MethodsCT images of 1521 patients with lung adenocarcinoma or precursor lesions appearing as pGGOs on CT in our hospital (The Third Affiliated Hospital of Sun Yat-sen University) from January 2015 to March 2021 were analyzed retrospectively and selected based on inclusion and exclusion criteria. pGGOs were divided into an atypical adenomatous hyperplasia (AAH)/adenocarcinoma in situ (AIS) group and an MIA group. Radiomic features were extracted from the original and preprocessed images of the region of interest. ANOVA and least absolute shrinkage and selection operator feature selection algorithm were used for feature selection. Logistic regression algorithm was used to construct radiomics prediction model. Receiver operating characteristic curves were used to evaluate the classification efficiency.Results129 pGGOs were included. 2107 radiomic features were extracted from each region of interest. 18 radiomic features were eventually selected for model construction. The area under the curve of the radiomics model was 0.884 [95% confidence interval (CI), 0.818-0.949] in the training set and 0.872 (95% CI, 0.756-0.988) in the test set, with a sensitivity of 72.73%, specificity of 88.24% and accuracy of 79.47%. The decision curve indicated that the model had a high net benefit rate.ConclusionThe prediction model for pathological subtypes of MIA and precursor lesions in pGGOs demonstrated a high diagnostic accuracy.Advances in knowledgeWe focused on lesions appearing as pGGOs on CT and revealed the differences in radiomic features between MIA and precursor lesions. We constructed a radiomics prediction model and improved the diagnostic accuracy for the pathology of MIA and precursor lesions.
| S-EPMC10996418 | biostudies-literature
Project description:Objective: Pure ground-glass opacity (GGO) nodules have been detected with increasing frequency using computed tomography (CT). We performed a retrospective study to clarify whether lung cancer patient prognoses correlated with pure GGO nodules. We also analyzed the clinical characters of patients with pure GGO nodules to provide diagnostic guidance on lung cancer identification and treatment of patients in clinical practice. Methods: We enrolled 39 of 1422 patients with pure GGO nodules who accepted surgical treatment of the lung cancer nodules, and reviewed materials from 404 patients to verify our conclusions. To discover which factors were prognostically significant, we used the Kaplan-Meier method to estimate the overall survival (OS) and progression-free survival (PFS) curves. Age, gender, smoking history, histology, tumor size, and stage were the factors examined in our study. We also performed subgroup and matching group analyses to clarify the correlation between the presence of pure GGO nodules and prognoses. Results: Pure GGO nodules were associated with non-smoking females that had adenocarcinoma. The prognoses of patients in the pure GGO nodule group was better than those in the non-pure GGO nodule group (p = 0.046). Age, grade, and stage (including tumor size and lymph node metastases) were had prognostic significance. In the matching group stage assessments, although patient prognoses were not significantly different among patients of the GGO group compared with thoses of the other group in long-term, while in the short term, patients with pure GGO nodules had longer PFS. Non-smoking female patients with lung cancer were more likely to have adenocarcinoma. Conclusions: As a subgroup of GGO nodules, pure GGO nodules predict a better prognosis in all lung cancer patients. Wheras our study showed that lung patients with pure GGO nodules in similar stages were not significantly different in long-term prognoses, in the short term; patients with pure GGO nodules had longer PFS.
| S-EPMC6909955 | biostudies-literature
Project description:ObjectivesGround-glass opacity (GGO)-a hazy, gray appearing density on computed tomography (CT) of lungs-is one of the hallmark features of SARS-CoV-2 in COVID-19 patients. This AI-driven study is focused on segmentation, morphology, and distribution patterns of GGOs.MethodWe use an AI-driven unsupervised machine learning approach called PointNet++ to detect and quantify GGOs in CT scans of COVID-19 patients and to assess the severity of the disease. We have conducted our study on the "MosMedData", which contains CT lung scans of 1110 patients with or without COVID-19 infections. We quantify the morphologies of GGOs using Minkowski tensors and compute the abnormality score of individual regions of segmented lung and GGOs.ResultsPointNet++ detects GGOs with the highest evaluation accuracy (98%), average class accuracy (95%), and intersection over union (92%) using only a fraction of 3D data. On average, the shapes of GGOs in the COVID-19 datasets deviate from sphericity by 15% and anisotropies in GGOs are dominated by dipole and hexapole components. These anisotropies may help to quantitatively delineate GGOs of COVID-19 from other lung diseases.ConclusionThe PointNet++ and the Minkowski tensor based morphological approach together with abnormality analysis will provide radiologists and clinicians with a valuable set of tools when interpreting CT lung scans of COVID-19 patients. Implementation would be particularly useful in countries severely devastated by COVID-19 such as India, where the number of cases has outstripped available resources creating delays or even breakdowns in patient care. This AI-driven approach synthesizes both the unique GGO distribution pattern and severity of the disease to allow for more efficient diagnosis, triaging and conservation of limited resources.
| S-EPMC8920286 | biostudies-literature
Project description:BackgroundUnderstanding the genomic landscape of early-stage lung adenocarcinoma (LUAD) may provide new insights into the molecular evolution in the early stages of LUAD.MethodsThrough sequencing of 79 spatially distinct regions from 37 patients with ground glass opacities (GGOs), we provided a comprehensive mutational landscape of GGOs, highlighting the importance of ancestry differences.ResultsOur study had several interesting features. First, epidermal growth factor receptor (EGFR), BRAF (v-RAF murine sarcoma viral oncogene homologue B1), and ERBB2 (Erb-B2 Receptor Tyrosine Kinase 2, also known as HER2) were more frequently mutated in our study, which supports the notion that EGFR is considered to be a major driver and tends to drive the occurrence of LUAD. Second, Signature 1, Signature 3, and Signature 6 were identified in patients with GGOs. Our results further suggested that Signature 1 was more prominent among early mutations. Third, compared with LUADs, GGOs exhibited significantly lower levers of arm-level copy number variation (CNV)-which alter the diploid status of DNA, and lower focal CNVs.ConclusionsIn our study, 79 samples of patients were included to analyze the GGO gene profile, revealing the genetic heterogeneity of GGO in East Asian population, and providing guidance for prognosis analysis of GGO patients by comparison with LUAD. Our study revealed that GGOs had fewer genomic alterations and simpler genomic profiles than LUADs. The most commonly altered processes were related to the receptor tyrosine kinase (RTK)/Ras/phosphatidylinositol-3-kinase (PI3K) signaling pathways in GGOs, and EGFR alterations were the dominant genetic changes across all targetable somatic changes.
| S-EPMC8107556 | biostudies-literature
Project description:To explore the diagnostic method in assessing the malignancy of pulmonary adenocarcinoma characterized by ground glass opacities (GGO) on computed tomography (CT).Preoperative CT data for preinvasive and invasive lung adenocarcinomas were analyzed retrospectively. GGO lesions that were detected on lung windows but absent using the mediastinal window were subject to adjustment of the window width, which was reduced with the fixed interval of 100 HU until the lesions were no longer evident, with a fixed mediastinal window level of 40 HU. The shape, smoking habits, size of the lesion on the lung window, and window width at which lesions disappeared were compared and receiver operating characteristic curves were used to determine the optimal cut-off of the lesion size and window width to differentiate between these invasive and preinvasive lesions.Of the 209 lung adenocarcinomas, 102 were preinvasive (25 atypical adenomatous hyperplasia and 77 adenocarcinoma in situ), while 107 were invasive (78 minimally invasive adenocarcinoma and 29 invasive adenocarcinoma). The shape, lesion size, and window width at which lesions were no longer evident differed significantly between the two groups (P < 0.05). The size of 8.9 mm and a window width of 1250 HU were the optimal cut-off to differentiate between preinvasive and invasive lesions.The shape, size of the lesion, and window width on high-resolution CT may be useful in assessing the invasiveness of lung adenocarcinoma that manifests as GGO. Irregular lesions that disappear at window width <1250 HU, with a diameter of > 8.9 mm are more likely to be invasive.
| S-EPMC4718115 | biostudies-other
Project description:BackgroundPulmonary ground glass opacities (GGOs) are early-stage adenocarcinoma spectrum lesions that are not easily palpable. Challenges in localizing GGOs during intraoperative pathology can lead to imprecise diagnoses and additional time under anesthesia. To improve localization of GGOs during frozen section diagnosis, we evaluated a novel technique, 3-dimensional near-infrared specimen mapping (3D-NSM).MethodsFifty-five patients with a cT1 GGO were enrolled and received a fluorescent tracer preoperatively. After resection, specimens were inspected to identify lesions. Palpable and nonpalpable nodules underwent 3D-NSM and the area of highest fluorescence was marked with a suture. Time for 3D-NSM, time for frozen section diagnosis, and number of tissue sections examined were recorded. To compare 3D-NSM with standard-of-care techniques, a control cohort of 20 subjects with identical inclusion criteria were enrolled. Specimens did not undergo 3D-NSM and were sent directly to pathology.Results3D-NSM localized 54 of 55 lesions with 1 false negative. All 41 palpable lesions were identified by 3D-NSM. Thirteen (92.8%) of 14 nonpalpable lesions were located by 3D-NSM. Time to diagnosis for the 3D-NSM cohort was 23.5 minutes, compared with 26.0 minutes in the control cohort (P = .04). 3D-NSM did not affect time to diagnosis of palpable lesions (23.2 minutes vs 21.4 minutes; P = .10). 3D-NSM significantly reduced time to diagnosis for nonpalpable lesions (23.3 minutes vs 34.4 minutes; P < .0001). 3D-NSM also reduced the number of tissue sections analyzed in nonpalpable lesions (4.50 vs 11.00; P < .0001).Conclusions3D-NSM accurately localizes GGOs and expedites intraoperative diagnosis by reducing the number of tissue sections analyzed for nonpalpable GGOs.
| S-EPMC9188686 | biostudies-literature
Project description:PURPOSE:Intraoperative localization and resection of ill-defined pulmonary ground-glass opacities (GGOs) during minimally invasive pulmonary resection is technically challenging. Current preoperative techniques to facilitate localization of GGOs include microcoil and hook wire placement, both of which have logistic limitations, carry safety concerns, and do not help with margin assessment. In this clinical trial, we explored an alternative method involving near-infrared molecular imaging with a folate receptor-targeted agent, OTL38, to improve localization of GGOs and confirmation of resection margins. METHODS:In a human trial, 20 subjects with pulmonary GGOs who were eligible for video-assisted thoracoscopic surgery (VATS) resection received 0.025 mg/kg of OTL38 before the resection. The primary objectives were to (1) determine whether use of OTL38 allows safe localization of GGOs and assessment of margins during VATS and (2) determine patient, radiographic, and histopathologic variables that predict the amount of fluorescence during near-infrared imaging. RESULTS:We observed no toxicity. Of the 21 GGOs, 20 accumulated OTL38 and displayed fluorescence upon in situ or back table evaluation. Intraoperatively, near-infrared imaging localized 15 of 21 lesions whereas VATS alone localized 10 of 21 (p = 0.05). The addition of molecular imaging affected care of nine of 21 subjects by improving intraoperative localization (n = 6) and identifying close margins (n = 3). This approach was most effective for subpleural lesions measuring less than 2 cm. For lesions deeper than 1.5 cm from the pleural surface, intraoperative localization using fluorescent feedback was limited. CONCLUSIONS:This approach provides a safe alternative for intraoperative localization of small, peripherally located pulmonary lesions. In contrast to alternative localization techniques, use of OTL38 also allows confirmation of adequate margins. Future studies will compare this approach to alternative localization techniques in a clinical trial.
| S-EPMC6015787 | biostudies-literature
Project description: Not available
| S-EPMC8339874 | biostudies-literature
Project description:BackgroundThe management of ground-glass opacities (GGOs) depends mainly on personal experience. In clinical practice, benign GGOs are not rare in resected specimens, for which operations may be avoided. We retrospectively compared the clinical features of resected GGOs to identify differential diagnostic characteristics.MethodsAmong 1456 patients with suspected malignant GGOs who underwent surgical resection, 105 patients (35 with benign GGOs and 70 matched controls with malignant GGOs) were included. Clinical characteristics, including demographics and radiologic, surgical and pathologic characteristics, were collected.ResultsThe smoking index (P = 0.044), frequency of coughing (P = 0.026), GGO size (P = 0.003), size change during follow-up (P = 0.011), location (P = 0.022), presence of air bronchogram sign (P = 0.004), distance to the pleura (P = 0.021) and positron emission tomography/computed tomography (PET/CT) appearance (P = 0.003) showed significant differences between the benign and malignant groups. Pathologically, the resected benign GGOs included focal fibrosis (17), inflammation or infection (seven), lymphoproliferative disorder (one), hamartoma (three), inflammatory myofibroblastic tumor (two), hemangioma or vascular malformation (two), endometriosis (two) and pulmonary cyst (one).ConclusionsA higher smoking index, coughing, larger size, similar or increased size during follow-up, location in the upper and middle lobes, air bronchogram sign on CT, lesion margin to pleura distance over 1 cm, and malignant tendency on PET/CT reports were associated with malignant GGOs. Relatively active surgical interventions could be considered for GGOs highly suspected of malignancy.
| S-EPMC7529560 | biostudies-literature