A Novel Approach of Lung Tumor Segmentation Using a 3D Deep Convolutional Neural Network

Cancer is one of the most life-threatening diseases in the world, and lung cancer is the leading cause of death worldwide. If not detected at an early stage, the survival rate of lung cancer patients can be very low. To treat patients in later stages, one needs to analyze the tumour region. For accurate diagnosis of lung cancer, the first step is to detect and segment the tumor. In this chapter, an approach for segmentation of a lung tumour is presented. For pre-processing of lung CT images, simple image processing like morphological operations is used, and for tumour segmentation task, a 3D convolutional neural network (CNN) is used. The CNN architecture consists of a 3D encoder block followed by 3D decoder block just like U-Net but with deformable convolution blocks. For this study, two datasets have been used; one is the online-available NSCLC Radiomics dataset, and the other is collected from an Indian local hospital. The approach proposed in this chapter is evaluated in terms of dice coefficient. This approach is able to give significant results with a dice coefficient of 77.23%.

Computer-aided diagnosis of lung malignity using multidimensional analysis of tumour marker data

The aim of this work is assessing diagnostic performance of lung tumour markers. Three clinical laboratory tests were used for indicating lung malignancy in order to verify or predict the patient’s diagnosis. The data set of 182 patients was examined and two main groups of the patient samples were created – 86 with diagnosed malignancy (confirmed by histology) and 96 with diagnosed benign tumours or tuberculosis. The following tumour markers were analyzed: carcinoembryonic antigen and cytokeratin 19 fragment, which were sampled in the pleural exudates, and the same tumour markers in serum. In addition, the patient’s age and the gender of the corresponding individual were used as further variables in the original data matrix. Three laboratory tests were used for indicating lung malignancy in order to verify or predict the patient’s diagnosis not only by using the results of the chosen individual laboratory test but also applying multivariate statistical approach, which jointly utilizes all performed tests in the form of their optimal linear combination.

Toxicity and efficacy of stereotactic body radiotherapy for ultra-central lung tumours: a single institution real life experience

Objectives: The use of stereotactic body radiotherapy (SBRT) to treat ultra-central lung tumours remains more controversial than for peripheral and central tumours. Our objective was to assess toxicities, local control (LC) rate and survival data in patients with ultra-central lung tumours treated with SBRT. Methods: We conducted a retrospective and monocentric study about 74 patients with an ultra-central lung tumour, consecutively treated between 2012 and 2018. Ultra-central tumours were defined as tumours whose PTV (planning target volume) overlapped one of the following organs at risk (OAR): the trachea, right and left main bronchi, intermediate bronchus, lobe bronchi, oesophagus, heart. Results: Median follow-up was 25 months. Two patients (2.7%) showed Grade three toxicity. No Grade four or five toxicity was observed. 11% of patients experienced primary local relapse. Local control rate was 96.7% at 1 year and 87.6% at 2 years. Median progression free survival (PFS) was 12 months. Median overall survival (OS) was 31 months. Conclusions: SBRT for ultra-central tumours remains safe and effective as long as protecting organs at risk is treatment-planning priority. Advances in knowledge: The present study is one of the rare to describe exclusively ultra-central tumours through real-life observational case reports. Globally, literature analysis reveals a large heterogeneity in ultra-central lung tumours definition, prescribed dose, number of fractions. In our study, patients treated with SBRT for ultra-central lung tumours experienced few Grade three toxicities (2.7%) and no Grade four or five toxicities, due to the highest compliance with dose constraints to OARs. LC remained efficient.

Lung Cancer Detection using Image Processing Techniques and its Classification

Lung cancer has been a major contribution to mortality rates world-wide for many years now. There is a need for early diagnosis of lung cancer which if implemented, will help in reducing mortality rates. Recently, image processing techniques have been widely applied in various medical facilities for accurate detection and diagnosis of abnormality in the body images like in various cancers such as brain tumour, breast tumour and lung tumour. This paper is a development of an algorithm based on medical image processing to segment the lung tumour in CT images due to the lack of such algorithms and approaches used to detect tumours. The work involves the application of different image processing tools in order to arrive at the desired result when combined and successively applied. The segmentation system comprises different steps along the process. First, Image preprocessing is done where some enhancement is done to enhance and reduce noise in images. In the next step, the different parts in the images are separated to be able to segment the tumour. In this phase threshold value was selected automatically. Then morphological operation (Area opening) is implemented on the thresholded image. Finally, the lung tumour is accurately segmented by subtracting the opened image from the thresholded image. Support Vector Machine (SVM) classifier is used to classify the lung tumour into 4 different types: Adenocarcinoma(AC), Large Cell Carcinoma(LCC) Squamous Cell Carcinoma(SCC), and No tumour (NT). Keywords: Lung tumour; image processing techniques; segmentation; thresholding; image enhancement; Support Vector Machine; Machine learning;

Houttuynia cordata Thunb: An Ethnopharmacological Review

Houttuynia cordata Thunb (H. cordata; Saururaceae) is widely distributed in Asian regions. It plays an important role in traditional health care and disease treatment, as its aboveground stems and leaves have a long medicinal history in China and are used in the treatment of pneumonia and lung abscess. In clinical treatment, it can usually be combined with other drugs to treat dysentery, cold, fever, and mumps; additionally, H. cordata is an edible plant. This review summarizes detailed information on the phytochemistry and pharmacological effects of H. cordata. By searching the keywords “H. cordata and lung”, “H. cordata and heart”, “H. cordata and liver”, and “H. cordata and inflammation” in PubMed, Web of Science and ScienceDirect, we screened out articles with high correlation in the past ten years, sorted out the research contents, disease models and research methods of the articles, and provided a new perspective on the therapeutic effects of H. cordata. A variety of its chemical constituents are characteristic of medicinal plants, the chemical constituents were isolated from H. cordata, including volatile oils, alkaloids, flavonoids, and phenolic acids. Flavonoids and volatile oils are the main active components. In pharmacological studies, H. cordata showed organ protective activity, such as reducing the release of inflammatory factors to alleviate lung injury. Moreover, H. cordata regulates immunity, enhances the immune barriers of the vagina, oral cavity, and intestinal tract, and combined with the antibacterial and antiviral activity of its extract, effectively reduces pathogen infection. Furthermore, experiments in vivo and in vitro showed significant anti-inflammatory activity, and its chemical derivatives exert potential therapeutic activity against rheumatoid arthritis. Antitumour action is also an important pharmacological activity of H. cordata, and studies have shown that H. cordata has a notable effect on lung tumour, liver tumour, colon tumour, and breast tumour. This review categorizes the biological activities of H. cordata according to modern research papers, and provides insights into disease prevention and treatment of H. cordata.

Image Processing Based Various Strategies of Lung Cancer Diagnosis

Medical imaging represents the utilization of technology in biology for the purpose of noninvasively revealing the internal structure of the organs of the human body. It is a way to improve the quality of the patient’s life through a more precise and rapid diagnosis and with limited side-effects, leading to an effective overall treatment procedure. The main objective of this work is to study the tumour discrimination techniques that cover both micro and macro-scale textures encountered in computed tomography (CT) and digital microscopy (DM) modalities, respectively. Image texture can provide significant information on the (ab) normality of tissue and this work expands this idea to tumour texture grading and classification. The fractal dimension (FD) as a texture measure was applied to contrast enhanced CT lung tumour images in an aim to improve tumour grading accuracy from conventional CT modality, and quantitative performance analysis showed an accuracy of in distinguishing between advanced (aggressive) and early stage (non-aggressive) malignant tumours. A different approach was adopted for subtype discrimination of brain tumour DM images via a set of statistical and model-based texture analysis algorithms.

Outcomes of 27 Non-Small Cell Lung Cancer Patients Receiving Resections of Paired Primary Pulmonary and Brain Metastatic Tumours: Is EGFR Negative Mutation of Brain Metastasis Bring More Benefit?

Background: To analyze the heterogeneity and clinical outcomes of epidermal growth factor receptor (EGFR) gene mutation in primary tumour and corresponding brain metastasis(BM) in non-small cell lung cancer (NSCLC).Methods: Primary pulmonary tumours and paired metastatic brain tumours were surgically removed from twenty-seven NSCLC patients from July 1999 to November 2013 in our hospital. All brain lesions were confirmed as metastases stemming from NSCLC by pathological examination. EGFR gene (exons 18-21) mutant status was detected in matched tumour by using amplification refraction mutation system (ARMS). If inconsistency was detected, the paired tumour was evaluated again. The McNemar test was performed to compare the consistency of the paired tumour, and the Kappa test was used to quantify the agreement of both methods.Progression free survival(PFS) and overall survival(OS) were exhibited by the Kaplan-Meier.Results: In this study, of the 27 patients, nine (33.3%) cases were found to have EGFR mutations in BMs, and ten (37.0%) patients were detected positive EGFR status in primary lung tumour tissue. The rate of consistency of the matched tumour was 24/27 (88.9%, P≤0.001), and the Kappa coefficient was 0.757. Among the three cases presenting EGFR mutational heterogeneity, two patients harbored EGFR mutation in primary tumors but was negative in BMs, meanwhile, the other patient had the opposite pattern. Comparing to patients with consistent EGFR mutations(both mutant or wild),patients with inconsistent EGFR mutations tended to have better outcomes, including PFS(37.2months vs 25.0months vs 16.5months,P=0.159) and OS(53.6months vs 27.5months vs 26.8months,P=0.380), further analysis showed that two patients whose EGFR mutant-type primary tumor progressing to wild-type cerebral metastastic tumor might have longer overall survival(53.6months,37.8months) than one patient harboring reverse mutant difference(EGFR wild-type primary tumor progressing to mutant-type brain metastastic tumor) (16.7months). Also we found that patients with wild type in brain metastatic tumour had longer overall survival (OS)(mOS, 36.3 months vs 29.1months, P = 0.944).Conclusions: EGFR mutation status in NSCLC patients between primary lung tumour and paired BM was heterogeneous, patients harbored wild type EGFR mutation in BM might have better outcomes, especially for positive status transferred to wild.

USP12 downregulation orchestrates a protumourigenic microenvironment and enhances lung tumour resistance to PD-1 blockade

Oncogenic activation of KRAS and its surrogates is essential for tumour cell proliferation and survival, as well as for the development of protumourigenic microenvironments. Here, we show that the deubiquitinase USP12 is commonly downregulated in the KrasG12D-driven mouse lung tumour and human non-small cell lung cancer owing to the activation of AKT-mTOR signalling. Downregulation of USP12 promotes lung tumour growth and fosters an immunosuppressive microenvironment with increased macrophage recruitment, hypervascularization, and reduced T cell activation. Mechanistically, USP12 downregulation creates a tumour-promoting secretome resulting from insufficient PPM1B deubiquitination that causes NF-κB hyperactivation in tumour cells. Furthermore, USP12 inhibition desensitizes mouse lung tumour cells to anti-PD-1 immunotherapy. Thus, our findings propose a critical component downstream of the oncogenic signalling pathways in the modulation of tumour-immune cell interactions and tumour response to immune checkpoint blockade therapy.

Tumour Genome Characterization of a Rare Case of Pulmonary Enteric Adenocarcinoma and Prior Colon Adenocarcinoma

Pulmonary enteric adenocarcinoma (PEAC) is a rare variant of lung adenocarcinoma first described in the early 1990s in a lung tumour with overlapping lung and small intestine features. It is a rare tumour with fewer than 300 cases described in the published literature and was only formally classified in 2011. Given these characteristics the diagnosis is challenging, but even more so in a patient with prior gastrointestinal malignancy. A 68-year-old Caucasian female presented with a cough and was found to have a right upper lobe mass. Her history was significant for a pT3N1 colon adenocarcinoma. The resected lung tumour showed invasive lung adenocarcinoma but also features of colorectal origin. Immuno-stains were strongly and diffusely positive for lung and enteric markers. Multi-region, whole-exome sequencing of the mass and archival tissue from the prior colorectal cancer showed distinct genomic signatures with higher mutational burden in the PEAC and very minimal overlap in mutations between the two tumours. This case highlights the challenge of diagnosing rare lung tumours, but more specifically PEAC in a patient with prior gastro-intestinal cancer. Our use of multi-region, next-generation sequencing revealed distinct genomic signatures between the two tumours further supporting our diagnosis, and evidence of PEAC intra-tumour heterogeneity.

CT Imaging of Primary Lung Tumours with CT Guided Fine Needle Aspiration Cytology Correlation among Guwahati, Assam Population

BACKGROUND The primary lung masses (tumours) are those that originate from the lung tissue. Although most primary pulmonary tumours are carcinomas, a large histological spectrum of benign and malignant tumours of the lung exists. Although chest xray is still considered to be the primary imaging modality of lungs, computed tomography (CT) not only shows the segments that are involved but also the extent of involvement. We wanted to study the sensitivity and specificity of CT in the diagnosis of primary neoplastic lesions of lung, study the CT patterns of different histological variants of bronchogenic carcinoma, and correlate CT findings with CT guided fine needle aspiration and cytology (FNAC) findings. METHODS The present descriptive cross-sectional study was conducted among 34 patients suspected clinically of having lung neoplasms, in Gauhati Medical College and Hospital, Guwahati, Assam from December 2010 to November 2011. RESULTS Considering FNAC / histopathological examination (HPE) as the gold standard, the positive predictive value and false negative value of CT scan for diagnosis of neoplastic lesions of lung were 97 % and 3 % respectively, in our study. Among our study population, mean age with lung tumours was 61 years, highest number of cases was seen in the age group of 51 - 60 years (35 %); Males and females affected were 27 (79.41 %), and 7 in number (20.59 %), respectively. CONCLUSIONS CT is more sensitive in the detection of neoplastic lesions of the lung and associated hilar / mediastinal adenopathy than chest roentgenography. CT has a high efficacy in detecting neoplastic lesions of lung, delineating its lobar and segmental anatomy, thereby helping surgical resection of lung. In this study, CT guided FNAC and cytological findings correlated well with CT diagnosis of primary neoplastic lesions of lung. KEYWORDS Primary Lung Tumour, Contrast Enhanced Computed Tomography (CECT), Fine Needle Aspiration and Cytology (FNAC)