Comparison of Differential Diagnosis of Lung Cancer by Diffuse Weighted Imaging and Sagittal Imaging with Short Inversion Recovery Sequence

2021 ◽  
Vol 11 (3) ◽  
pp. 822-826
Author(s):  
Wei Zhang ◽  
Qingyu Cai ◽  
Guoli Wei
Keyword(s):  
Lung Cancer ◽  
Differential Diagnosis ◽  
Squamous Cell ◽  
Lung Carcinoma ◽  
Small Cell Lung Carcinoma ◽  
Small Cell ◽  
Small Cell Lung ◽  
Recovery Sequence ◽  
Cell Lung Carcinoma ◽  
Diagnosis Of Lung Cancer

The differential diagnosis of advanced lung cancer is difficult in clinical practice. Our study aims to compare the value of diffusion weighted imaging (DWI) with short-term inversion recovery sequence (STIR) for sagittal imaging in the differential diagnosis of lung cancer. 149 patients with non-small cell lung carcinoma (NSCLC) were enrolled and underwent DWI and STIR sagittal imaging. To quantify cancer types, we evaluated the apparent diffusion coefficient (ADC) value on DWI and the contrast ratio (CRs) on sagittal imaging. The ADC values of subclasses in NSCLC were significantly higher than small cell lung carcinoma (SCLC) (p <0.01). The mean CRs were 1.59 for SCLC and 1.30 for NSCLC with a significant difference (p < 0.01). Large cell carcinomas (LCC) and adenocarcinomas have significant differences compared to small cell carcinomas (SCC) without difference between squamous cell carcinomas (p > 0.05); this is also the case for CRs. Squamous cell carcinoma and adenocarcinoma have significant differences compared to SCC without difference in LCC (p > 0.05). Qualitative evaluation of the feasible thresholds DWI and STIR showed that the thresholds were 0.9810−3 mm2/s and 1.37 respectively. The specificity and accuracy was 78.5% is 85.3% for DWI, which was significantly higher than STIR (56.3% and 61.0%). The combination of DWI and STIR sequences was superior to DWI alone with an accuracy rate of 94.3%. DWI is more helpful than STIR in differentiating SCLC and NSCLC, and their combined use can significantly improve diagnosis accuracy.

Detection Of Lung Cancer On Computed Tomography Using Artificial Intelligence Applications Developed By Deep Learning Methods And The Contribution Of Deep Learning To The Classification Of Lung Carcinoma

2021 ◽  
Vol 17 ◽  
Author(s):  
Nevin Aydin ◽  
Özer Çelik ◽  
Ahmet Faruk Aslan ◽  
Alper Odabaş ◽  
Emine Dündar ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Deep Learning ◽  
Squamous Cell ◽  
Lung Carcinoma ◽  
Small Cell Lung Carcinoma ◽  
Small Cell ◽  
Small Cell Lung ◽  
Learning Methods ◽  
Cell Lung Carcinoma ◽  
Non Invasive

Background: In every year, lung cancer is an important cause of deaths in the world. Early detection of lung cancer is important for treatment, and non-invasive rapid methods are needed for diagnosis. Introduction: In this study, we aimed to detect lung cancer using deep learning methods and determine the contribution of deep learning to the classification of lung carcinoma using a convolutional neural network (CNN). Method: A total of 301 patients with diagnosed with lung carcinoma pathologies in our hospital were included in the study. In the thorax computed tomography (CT) performed for diagnostic purposes prior to treatment. After tagging the section images, tumor detection, small-non-small cell lung carcinoma differentiation, adenocarcinoma-squamous cell lung carcinoma differentiation, and adenocarcinoma-squamous cell-small cell lung carcinoma differentiation were sequentially performed using deep CNN methods. Result: : In total, 301 lung carcinoma images were used to detect tumors, and the model obtained with the deep CNN system had 0.93 sensitivity, 0.82 precision, and 0.87 F1 score in detecting lung carcinoma. In the differentiation of small cell-non-small cell lung carcinoma, the sensitivity, precision and F1 score of the CNN model at the test stage were 0.92, 0.65, and 0.76, respectively. In the adenocarcinoma-squamous cancer differentiation, the sensitivity, precision, and F1 score were 0.95, 0.80, and 0.86, respectively. The patients were finally grouped as small cell lung carcinoma, adenocarcinoma, and squamous cell lung carcinoma, and the CNN model was used to determine whether it could differentiate these groups. The sensitivity, specificity, and F1 score of this model were 0.90, 0.44, and 0.59, respectively for this differentiation. Conclusion.: In this study, we successfully detected tumors and differentiated between adenocarcinoma-squamous cell carcinoma groups with the deep learning method using the CNN model. Due to their non-invasive nature and success of the deep learning methods, they should be integrated into radiology to diagnose lung carcinoma.

scholarly journals Histopathologic Analysis of Lung Cancer Incidence Associated with Radon Exposure among Ontario Uranium Miners

2018 ◽  
Vol 15 (11) ◽  
pp. 2413 ◽  
Author(s):  
Avinash Ramkissoon ◽  
Garthika Navaranjan ◽  
Colin Berriault ◽  
Paul Villeneuve ◽  
Paul Demers ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Squamous Cell ◽  
Lung Carcinoma ◽  
Small Cell Lung Carcinoma ◽  
Small Cell ◽  
Small Cell Lung ◽  
Cell Lung Carcinoma ◽  
Uranium Miners ◽  
Decay Products ◽  
Radon Decay

Although radon is a well-established contributor to lung cancer mortality among uranium miners, the effects of radon decay products on different histopathologies of lung carcinoma are not well established. Using a retrospective cohort design, this study aims to examine the risks of lung cancer by histological subtypes associated with exposure to radon decay products among the Ontario Uranium Miners cohort. Cases were stratified by histological groups, and associated risks were estimated for cumulative radon exposure after adjustment for attained age and calendar period. Between 1969 and 2005, 1274 incident cases of primary lung cancer were identified. Of these, 1256 diagnoses (99%) contained information on histology. Squamous cell carcinoma was most common (31%), followed by adenocarcinoma (20%), large cells (18%), small cell lung carcinoma (14%), and other or unspecified cell types (17%). Of the histological sub-groups, small cell lung carcinoma had the strongest association with cumulative radon exposure; compared to the reference group (<1 cumulative working level months (WLM)), the highest exposure category (>60 cumulative WLM) had a relative risk (RR) of 2.76 (95% CI: 1.67–4.57). Adenocarcinoma had the lowest risk and was not significantly associated with exposure to radon decay products (RR = 1.49, 95% CI: 0.96–2.31). An increasing, linear trend in relative risk was noted with increasing cumulative WLM across small cell, squamous cell, and large cell lung carcinomas (Ptrend < 0.05). Similarly, the excess relative risk (ERR) per WLM was highest for small cell lung carcinoma (ERR/WLM = 0.15, p < 0.01), followed by squamous cell carcinoma (ERR/WLM = 0.12, p < 0.01). Non-statistically significant excess risk was observed for adenocarcinoma (ERR/WLM = 0.004, p = 0.07). Our analysis of the Ontario Uranium Miners cohort data shows differences in the magnitude of the risks across four histological subtypes of lung carcinoma; the strongest association was noted for small cell lung carcinoma, followed by squamous cell, large cell, and lastly adenocarcinoma, which showed no significant associations with exposure to radon decay products.

scholarly journals Ras gene mutations in patients with non-small cell lung carcinoma

2004 ◽  
Vol 12 (2) ◽  
pp. 95-99
Author(s):  
Vesna Minic ◽  
Gordana Andjelic ◽  
Vojkan Stanic ◽  
Zvonko Magic
Keyword(s):  
Lung Cancer ◽  
Squamous Cell ◽  
Lung Carcinoma ◽  
Small Cell Lung Carcinoma ◽  
Small Cell ◽  
Squamous Cell Carcinomas ◽  
Small Cell Lung ◽  
Ras Gene ◽  
Cell Lung Carcinoma ◽  
Ras Mutations

BACKGROUND: Lung cancer is the leading cause of cancer mortality in most countries, with every year's increasing incidence. At present, surgical resection of early stage disease presents the only treatment associated with a high likelihood of 5-year survival. On the other hand, patients with advanced disease have 5-year survival less than 5%. This poor prognosis is attributable largely to lack of efficient diagnostic methods for early detection and the inability to cure metastatic disease. Therefore, efforts aimed at early identification and interventions in lung cancer are of the highest importance. Mutations in ras oncogenes appear to play a significant role in the development of non-small cell lung carcinoma (NSCLC). Thus, the aim of our study was to determine the incidence of H-ras and K-ras mutations in patients with NSCLC of different histological subtypes: adenocarcinomas (AC), squamous cell carcinomas (SCC), large cell carcinomas (LCC), and adenosquamous carcinomas (AC-SCC). METHODS: We analyzed 41 patients with stage I, II and III of histologically confirmed NSCLC (histological grade 2 and 3). DNA was isolated from frozen tumors by standard phenol-chloroform extraction. Mutations in exon 1 H-ras and K-ras gene were detected by PCR-SSCP method. RESULTS: Mutations in the H-ras gene were found in only 2 of 41 analyzed tumors (4.9%). The both mutations were found in SCC making the overall incidence in this histological subtype 10.5% (2 of 19). K-ras mutations were detected in 31.7% (13 out of 41) of tumors, with higher incidence in tumors of clinical stage I - 45% (9 out of 20). CONCLUSION: Our results indicate that H-ras mutations apparently play an inferior role in lung carcinogenesis. However, mutations in K-ras gene probably present an early event in genesis of NSCLC, and not only in adenocarcinomas, as the majority of previous reports indicate, but also in squamous cell carcinomas as well.

Radiosurgery for patients with recurrent small cell lung carcinoma metastatic to the brain: outcomes and prognostic factors

2005 ◽  
Vol 102 (Special_Supplement) ◽  
pp. 247-254 ◽  
Author(s):  
Jason Sheehan ◽  
Douglas Kondziolka ◽  
John Flickinger ◽  
L. Dade Lunsford
Keyword(s):  
Lung Cancer ◽  
Brain Metastases ◽  
Lung Carcinoma ◽  
Small Cell Lung Carcinoma ◽  
Small Cell ◽  
Small Cell Lung ◽  
Cell Lung Carcinoma ◽  
Content Type ◽  
The Brain ◽  
Fine Print

Object. Lung carcinoma is the leading cause of death from cancer. More than 50% of those with small cell lung cancer develop a brain metastasis. Corticosteroid agents, radiotherapy, and resection have been the mainstays of treatment. Nonetheless, median survival for patients with small cell lung carcinoma metastasis is approximately 4 to 5 months after cranial irradiation. In this study the authors examine the efficacy of gamma knife surgery for treating recurrent small cell lung carcinoma metastases to the brain following tumor growth in patients who have previously undergone radiation therapy, and they evaluate factors affecting survival. Methods. A retrospective review of 27 patients (47 recurrent small cell lung cancer brain metastases) undergoing radiosurgery was performed. Clinical and radiographic data obtained during a 14-year treatment period were collected. Multivariate analysis was utilized to determine significant prognostic factors influencing survival. The overall median survival was 18 months after the diagnosis of brain metastases. In multivariate analysis, factors significantly affecting survival included: 1) tumor volume (p = 0.0042); 2) preoperative Karnofsky Performance Scale score (p = 0.0035); and 3) time between initial lung cancer diagnosis and development of brain metastasis (p = 0.0127). Postradiosurgical imaging of the brain metastases revealed that 62% decreased, 19% remained stable, and 19% eventually increased in size. One patient later underwent a craniotomy and tumor resection for a tumor refractory to radiosurgery and radiation therapy. In three patients new brain metastases were demonstrating on follow-up imaging. Conclusions. Stereotactic radiosurgery for recurrent small cell lung carcinoma metastases provided effective local tumor control in the majority of patients. Early detection of brain metastases, aggressive treatment of systemic disease, and a therapeutic strategy including radiosurgery can extend survival.

New lung cancer treatment strategy with molecular target of PKCeta

Impact ◽  
2019 ◽  
Vol 2019 (8) ◽  
pp. 56-58
Author(s):  
Motoi Ohba
Keyword(s):  
Lung Cancer ◽  
Cancer Treatment ◽  
Lung Carcinoma ◽  
Small Cell Lung Carcinoma ◽  
Growth Factor Receptor ◽  
Small Cell ◽  
Surgical Removal ◽  
Small Cell Lung ◽  
Cell Lung Carcinoma ◽  
Nucleotide Mutation

Lung cancer is one of the most prevalent and lethal forms of the disease accounting for almost 20 per cent of all deaths from cancer. It is therefore the leading cause of cancer death in men and second most fatal in women. There are between 1.5 and 2 million new cases of cancer globally every year. A similar number die from the disease annually. There are two forms of lung cancer – small-cell lung carcinoma (SCLC) and non-small-cell lung carcinoma (NSCLC). SCLC is the more aggressive form being faster growing and more metastatic, however it also responds more effectively to treatments such as chemotherapy. NSCLC is the more common form of the disease, accounting for 85 per cent of cases. They develop more slowly than SCLCs, however they are largely unresponsive to chemotherapy and require precise surgical removal. Both present a huge medical problem in terms of diagnosis and treatment. Due to its far higher prevalence, NSCLC is the most studied of the two forms. A chemotherapeutic treatment has been developed that targets the epidermal growth factor receptor (EGFR). EGFR is majorly upregulated in most cases and plays a key role in the tumour's growth and survival. The treatment blocks the receptor and is usually very effective in the first instances. However, it is typically unable to clear the cancer as a single nucleotide mutation is capable of rendering the inhibitor unable to act on the receptor. Therefore, the cancer returns and continues to develop. New treatments are also required. This is the work of Dr Motoi Ohba of the Advanced Cancer Translational Research Institute, Showa University, Japan. His work is aimed at both uncovering novel targets for cancer treatment and finding and developing molecules that could effectively manipulate these targets.

scholarly journals Differential development of large-cell neuroendocrine or small-cell lung carcinoma upon inactivation of 4 tumor suppressor genes

2019 ◽  
Vol 116 (44) ◽  
pp. 22300-22306 ◽  
Author(s):  
Sara Lázaro ◽  
Miriam Pérez-Crespo ◽  
Corina Lorz ◽  
Alejandra Bernardini ◽  
Marta Oteo ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Lung Carcinoma ◽  
Small Cell Lung Carcinoma ◽  
Large Cell ◽  
Small Cell ◽  
Imaging Method ◽  
Cancer Type ◽  
High Grade ◽  
Small Cell Lung ◽  
Cell Lung Carcinoma

High-grade neuroendocrine lung malignancies (large-cell neuroendocrine cell carcinoma, LCNEC, and small-cell lung carcinoma, SCLC) are among the most deadly lung cancer conditions with no optimal clinical management. The biological relationships between SCLC and LCNEC are still largely unknown and a current matter of debate as growing molecular data reveal high heterogeneity with potential therapeutic consequences. Here we describe murine models of high-grade neuroendocrine lung carcinomas generated by the loss of 4 tumor suppressors. In an Rbl1-null background, deletion of Rb1, Pten, and Trp53 floxed alleles after Ad-CMVcre infection in a wide variety of lung epithelial cells produces LCNEC. Meanwhile, inactivation of these genes using Ad-K5cre in basal cells leads to the development of SCLC, thus differentially influencing the lung cancer type developed. So far, a defined model of LCNEC has not been reported. Molecular and transcriptomic analyses of both models revealed strong similarities to their human counterparts. In addition, a 68Ga-DOTATOC–based molecular-imaging method provides a tool for detection and monitoring the progression of the cancer. These data offer insight into the biology of SCLC and LCNEC, providing a useful framework for development of compounds and preclinical investigations in accurate immunocompetent models.

scholarly journals Immunocheckpoint Inhibitor- (Nivolumab-) Associated Hypereosinophilia in Non-Small-Cell Lung Carcinoma

2020 ◽  
Vol 2020 ◽  
pp. 1-5 ◽  
Author(s):  
Navdeep Singh ◽  
Sandeep Singh Lubana ◽  
George Constantinou ◽  
Andrea N. Leaf
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Lung Carcinoma ◽  
Cell Lung Cancer ◽  
Checkpoint Inhibitors ◽  
Small Cell Lung Carcinoma ◽  
Small Cell ◽  
Small Cell Lung ◽  
Cell Lung Carcinoma ◽  
Eosinophil Counts

Immunocheckpoint inhibitor (ICI) therapy has provided significant clinical improvements in the treatment of several malignancies. The purpose of this report is to increase awareness of hypereosinophilia associated with checkpoint inhibitors, a topic that has been rarely reported. Hypereosinophilia may need to be addressed especially if eosinophil counts increase to levels where hypereosinophilic visceral complications can occur. We are presenting a case of a 57-year-old male with hypereosinophilia that was seen in the setting of progression of metastatic non-small-cell lung cancer during and after nivolumab treatment.

Lung cancer (including management of an isolated lung lesion)

2018 ◽  
Author(s):  
Raman Verma ◽  
Sarah Deacon
Keyword(s):  
Lung Cancer ◽  
Lung Carcinoma ◽  
Small Cell Lung Carcinoma ◽  
Primary Lung Cancer ◽  
Small Cell ◽  
The Body ◽  
Small Cell Lung ◽  
Rare Type ◽  
Cell Lung Carcinoma ◽  
Isolated Lung

Lung cancer is the second most common type of cancer in the UK. It is termed ‘primary’ if it originates in the lungs. and ‘secondary’ if it manifests elsewhere in the body but then spreads to the lungs. The main types of primary lung cancer are small cell lung carcinoma and non-small cell lung carcinoma. Bronchial carcinoids account for up to 5% of lung cancer. These are generally small when diagnosed and occur most commonly in people under 40 years of age. Unrelated to cigarette smoking, carcinoid tumours can metastasize and a small proportion of these tumours secrete hormone-like substances that may cause specific symptoms related to the hormone being produced. Carcinoids generally grow and spread more slowly than bronchogenic cancers, and many are detected early enough to be amenable to surgical resection. Mesothelioma is a rare type of cancer that affects the pleura.

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