There are several possible explanations for the far superior prognosis of symptomatic patients presenting with cough (either simple, associated with haemoptysis or with purulent sputum), with a median survival approximately twice as long as that seen after any other symptomatic presentation. Most obviously these symptoms were associated with earlier stage and consequent higher radical treatment rates. It is therefore possible that these symptoms may correspond to discovery at an earlier stage in the natural history of the cancer when patients are still amenable to curative treatment.
A retrospective, descriptive analysis on resource use and a direct medical cost analysis were carried out. Resource utilisation data were collected by means of hospital ad- ministrative databases and patient files. From a hospital budget impact perspective, the aggregate and mean costs per patient were assessed in the three years following diagnosis or up to death. Both aggregate and mean costs per patient were analysed by stage at diagnosis and cost type. Mean cost per patient was also analysed by sex, age group and survival at one year from diagnosis. The categories of cost considered included (a) diagnosis (diagnostic tests, ambulatory and emergency visits, in- patient nights), (b) surgery (operating room and inpatient nights), (c) chemotherapy (day hospital and cytotoxic drugs), (d) radiotherapy (number of fractions), (e) other inpatient care (not related to diagnosis, surgery, chemo- therapy or radiotherapy treatments for lung cancer, e.g., hospital admissions related to COPD or other comor- bidities and palliative care), and (f ) continuing care (ambulatory and emergency visits, tests, scans, biopsies, etc., made in the continuing phase). The mean costs of surgical interventions as well as chemotherapy and radio- therapy treatments were also assessed by histology and stage at diagnosis.
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Lung cancer is the second most common cancer in both men and women and is by far the leading cause of death in both man and women, each year more people is die of lung cancer than colon, breast, and prostate cancers combined . The best way to protect from this danger disease is to detect it early, in this paper we proposed diagnosis system for lung cancer disease based on fuzzy logic system and neural network, several techniques are used to enhance the lung image and segment it in order to get more information about the characteristic of the CT lung image , then GLCM method is used to extract the features of the image that is used as input to classify stage , neural network is used in classification ,at this stage the image is defined normal or abnormal, the result of neural network is combined with fuzzy inference system that is used to determine the stage of the cancer depending on the symptom of the patient, different image of lung was used and good result have been satisfied. References
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Metastatic neoplasms to the ovary often cause diagnostic problems, in particular those large ovarian masses mimicking primary tumors. Most of these tumors arise from digestive system or breast, while 37-year-old woman diagnosed as right adnexal complex mass, with a subpleural nodule in the apical part of the left lower lobe, at preoperative chest computed tomography scan. The patient underwent total abdominal hysterectomy with right salpingo-oophorectomy (ovarian mass 220 × 200 mm), total omentectomy, left ovarian biopsy, peritoneal random biopsies, and peritoneal washings for cytology. Pathologic and immunohistochemical examination of ovarian specimen suggested morphology and expression of metastatic lung adenocarcinoma with an intense positivity for Thyroid Transcriptional Factor-1 (TTF-1) and Cytokeratin 7 (CK7) staining. Fine needle biopsy of the lung nodule found epithelioid like malignant cells, confirming the diagnosis of an ovarian metastasis from a primary lung cancer. This report focused on the clinical and pathologic diagnostic challenge of distinguishing secondary from primary ovarian neoplasms. Issues on useful immunohistochemical stains are also discussed.
than in patients with a ﬁ rst high VTE-risk cancer type (ie a ﬁ rst lung and colorectal cancer). In patients with a ﬁ rst prostate or breast cancer, second cancer lead to markedly higher IRs of VTE than in patients with only prostate or breast cancer regardless of the timing of diagnosis of the second cancer (Table 3). Contrarily, similar 0 – 6 month IRs of VTE was observed for patients with only lung or color- ectal cancer and those who were diagnosed with a second cancer within the ﬁ rst six months after the lung cancer diagnosis. For those with a ﬁ rst lung cancer even if diag- nosed with high/very high VTE-risk second cancer types (0 – 6 month IR of VTE: 55.0, 95% CI, 27.5 – 110.0). If a second cancer was diagnosed more than one year after a ﬁ rst lung or colorectal cancer diagnosis; however, the IR was higher than in patients free of second cancer (Table 3). The impact of a second cancer on the risk of VTE in cancer patients was surpassed by exposure to lower extremity fractures (IRR of VTE in exposed period compared with unexposed 12.3, 95% CI, 9.7 – 15.6), arthroplasties (IRR of VTE in exposed period compared with unexposed 13.8, 95% CI, 10.2 – 18.5), and a history of VTE (IRR of VTE in patients with a history of VTE compared with no VTE before ﬁ rst cancer 10.8, 95% CI 9.4 – 12.5) in the multivariate analysis (Supplementary Figure 2).
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diagnosis. At present, CEA, CA125, and ProGRP are commonly used as lung cancer serum tu- mor markers. Carcinoembryonic antigen (CEA) contains human embryonic antigen specificity determinant and overexpresses in a wide vari- ety of tumors that lack specificity. CA125 has a certain value for lung cancer auxiliary diagnosis and differential diagnosis. ProGRP is mainly used for SCLC and NSCLC identification, and it is also used for metastatic lung cancer detec- tion [19, 20]. All of these three markers showed low specificity and sensitivity for lung cancer in single use. Thus, it is needed to find serum markers with higher specificity and sensitivity for lung cancer diagnosis. This study confirmed that CA125 had the highest sensitivity of the three, but only at 65.1%. Furthermore, the three markers combined failed to elevate the sensitivity significantly (82.2%). MiRNAs regu- late genes expression at the post-transcription- al level. Circulating miRNAs can be used as bio- markers of disease, though the expression and mechanisms have not been fully elucidated. Studies showed that micro-vesicles can active- ly secrete miRNAs. In vitro experiments re- vealed that apoptotic bodies in endothelial cells can secrete miRNAs in serum-free medi- um. MiRNAs finish their integration in a micro- vesicle, apoptotic body, or exosome and then are secreted to the recipient cells to form miRNA complexes, which guarantee that RN- Aase cannot effectively degrade the circulating miRNAs. Circulating miRNA levels can reflect tumor progression and even evaluate the tumor size . MiR-34a is confirmed to be a tumor marker that plays a role in lung cancer occur- rence and development [15, 22]. This study confirmed that miR-34a expression was signifi- cantly decreased in lung cancer patients and in the high-risk group. Its level was clearly lower in lung cancer patients compared with the high- risk group, and significantly decreased follow- ing TNM upstage. Moreover, it showed no cor- relation with pathologic classification, suggest- ing that serum miR-34a could be treated as a new type of lung cancer marker. Our study fur- ther proved that although the sensitivity and specificity of miR-34a detection alone, in lung cancer was not high, the detection of the four serum markers combined presented the high- est sensitivity. Following miR-34a, CEA and CA125 combined presented the highest sensi- tivity (71.6%) among the two markers detec- tion. On the specificity aspect, detection of all four markers combined showed the highest Figure 4. ROC curve analysis of each marker in the
An automatic pathological diagnosis procedure named Neural Ensemble-based Detection (NED) has been described and realized in an early stage Lung Cancer Diagnosis System (LCDS)  is which utilizes artificial neural network ensemble to identify lung cancer cells in images of the specimens of needle biopsies. The core of NED is a two-level ensemble architecture that is composed of heterogeneous ensembles that not only comprises individual networks with different number of output units, but also employs different methods to combine individual predictions. For improving the accuracy of false negative identification, full voting scheme is used in the first-level ensemble. NED achieves not only high rate of overall identification and low rate of false negative identification. The drawbacks with this NED are at each phase a neural network is used, hence it will delay the output, the system will not deal with overlapped cells. This is fully automated one, which is conflicting with the requirements of the user.
Folate receptor (FR), a membrane glycoprotein that shows a high positivity in a range of cancer types, has emerged as a potential drug target for lung cancers. 7 In the peripheral blood, only a few FR-expressing cells are present, including CTCs and a rare subtype of activated monocytes which are seldom detected in nonmalignant individuals (note that the α -isoform of FR which is the target of the CTC detection platform used in our study is absent from all hematopoietic cells). 8,9 In contrast, FR expression was reported to be upregulated in over 75% of non-small cell lung cancer. 10 Thus, FR is theoretically an effective target for labeling CTCs, especially for lung can- cers. Several studies had demonstrated the diagnostic ef ﬁ - ciency of folate receptor-positive CTCs (FR+CTC) in lung cancers and bladder cancers, as well as for predicting patient ’ s prognosis and chemotherapy sensitivity in small- cell lung cancer. 11–16 The related FR+CTC detection kit has been approved by the CFDA for clinical use. For lung cancer diagnosis, the sensitivity and speci ﬁ city of FR +CTC were reported to be 72.5 – 81.8% and 82.4 – 93.2%, respectively. 11–14 FR+CTC may also be suitable for other cancer types such as pancreatic cancer, breast cancer, ovar- ian cancer, and so on, which are accompanied by a high expression of FR. 17,18
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Available Online at www.ijpret.com 851 Disha Sharma et.al  developed an automatic CAD system for early detection of lung cancer by analyzing LUNG CT images. First, extracting the lung regions from the CT image using several image processing techniques, including bit image slicing, erosion, and Weiner filter. To convert the CT image into a binary image, Bit plane slicing techniques is used in the extraction process. After extraction, the extracted lung regions are segmented using region growing segmentation algorithm. To classify cancer nodules rule based technique was used. From the extracted features, set of rules were generated and diagnostic indicator achieved accuracy of 80%
Periodic examinations, including physiologic and radiographic examinations, are usually performed to detect recurrence after curative-intent treatment, and these examinations are commonly referred to as follow-up surveillance. However, the efficacy of 2-deoxy-2-[fluorine-18]fluoro- d -glucose positron emission tomography/ computed tomography (FDG-PET/CT) in a follow-up surveillance setting following curative-intent treatments for lung cancer has not yet been established. In this review, we survey previous papers and evaluate the potential efficacy of FDG-PET/CT in the setting of long-term follow-up surveillance. We first briefly summarize the current
Several potential limitations still exist in this meta-analysis. First, the number of included patients and cancer types was relatively small. Second, the cut-off definition of high and low XIST expression was inconsistent in these stud- ies, which may be one source of heterogeneity. Third, some studies did not provide HRs, which require the calculation or extraction of HRs and 95% CIs from the available data or from Kaplan- Meier curves. Furthermore, most of the patients included in this meta-analysis were from China. For this reason, the results we obtained may just be representative of the Chinese. Thus, more studies with larger sample sizes, high quality, different ethnic backgrounds and a uni- form cut-off value are necessary to solidify the results in this study.
B. Patil et al.  proposed an approaches to predict the probability of lung cancer presence. First approach is Binarization and the second is masking. The images used in analysis were in standard JPEG format hence for converting them in Grey level ‘Otsu’s’ method was used. Marker-controlled watershed segmentation was used and it gave accuracy of 85.27%. For prediction of lung cancer Binarization approach which is depends on the fact that the number of black pixels is much greater than white pixels in normal lung images is used. So the counting starts the black pixels for normal and abnormal images to get an average that can be used later as a threshold, if the number of the black pixels of a new image is greater than the threshold, then it indicates that the image is normal, otherwise, if the number of the black pixels is less than the threshold, it indicates that the image is abnormal. Another method for prediction is masking which depends on the fact that the masses are appeared as white linked areas inside ROI (lungs), as they increase the percent of cancer presence increase. Out of these two methods Binarization gives better results.
Of all lung cancers, Small cell carcinoma constitutes about 10-20% of them. Mostly found to arise in male patients and in that more than 85% are in smokers. Small cell carcinoma of lung is an highly aggressive malignant tumour. Most commonly it appears as lesion in the central portion of lung , but it may also seen in peripheral regions. Macroscopilly it appears as greyish white to tan, soft, friable and extensively necrotic. Microscopically it appears as solid pattern, but there are other growth patterns like ribbon and streams, or ductules and tubules, rosettes and pseudo rosettes may also be seen .(28,29) according to betticher et al (30)
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We are extremely grateful to the people who took part in this research in all three countries, and to the study advisory panel, including patient and public representatives, who helped design the study and provided comments on an earlier draft of this manuscript. We also acknowledge the support of the National Institute for Health Research, through the Clinical Research Network, who helped recruit patients into the English arm of the study. We would also like to thank all those who helped to recruit participants: In England we would like to thank the NHS Hospital Trusts that assisted with this study and Patients Active in Research: Thames Valley, along with the following charities who posted links or circulated our details on social media: Beating Bowel Cancer, Bowel Cancer UK, Roy Castle Lung Cancer Foundation, British Lung Foundation, and healthtalk.org. In Denmark we want to thank the Lung Cancer Patient organisation, as well as the Colon Cancer Patient organisation for assisting us in recruiting patients. We also wish to thank the local support groups of the national Danish Cancer Society, as well as the local oncology departments in various regions of Denmark. In Sweden we would like to thank the nurses and physicians who helped with recruitment.
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All ENB procedures require careful planning. Data from a recent chest CT scan with specific slice thickness and intervals are saved on a disc and introduced in the planning software module of a laptop computer. During planning, the software generates a virtual bronchoscopic reconstruction of the patient’s airways and axial, coronal, and sagittal images of the patient’s chest which the operator must navigate in order to generate a number of reference points and targets. Once planning is complete, a file containing all necessary information is saved on a USB stick which is then inserted in the bronchoscopy suite’s hardware in order to download its contents and perform the ENB procedure. virtual ref- erence points selected during planning will be registered either manually or automatically during ENB by advancing the steerable probe (Figure 1). Generally, well-known refer- ence points such as the main and lobar carinas are chosen and although the risk of pneumothorax is quite low, usually only targets in one lung are selected for a given procedure. Mediastinal lymph nodes may also be selected, and these may be located on either side of the mediastinum.
cells suggesting it may play a role in the progression of disease 54. It has been 55 demonstrated a subpopulation of CD44+ NSCLC cells were cisplatin-resistant and capable of spheroid body formation, in vivo tumor initiation. Collectively, CD44 is poised to be a key player in identifying CSCs due to its innate ability to regulate adhesion, differentiation, homing, and migration. A study established a panel of lung cancer cell lines from primary tumors and characterized a small subpopulation strongly positive for CD44 (CD44high), with the main population being weakly positive or negative for CD44. Co-expression of CD90 (CD90+) further narrowed down the putative stem cell population. This CD44 and CD90 positive subpopulation showed mesenchymal morphology, increased expression of the mesenchymal markers vimentin and N-cadherin, increased Mrna levels of the embryonic stem cell-related genes Nanog and Oct4, and resistance to irradiation compared with other subpopulations. The CD44high CD90+ subpopulation is therefore a good candidate for a CSC marker (56)Some scientists have also studied the stem cell marker and cell adhesion molecule CD44 in different histological subtypes of lung cancer, analyzing 195 lung tumor samples, including 37 SCLC samples, by immunochemistry (IHC). Univariate analysis demonstrated that CD44 expression was higher in NSCLC compared to SCLC. In NSCLC, a higher level of CD44 expression was found in squamous cell carcinomas (SCC) compared to ADC. Higher CD44 expression correlated with higher grade tumors which in turn correspond to poor prognosis in SCC, and the lower level of CD44 expression was more often found in well differentiated ADCs. Also, high CD44 expression was associated with decreased levels of the proliferative marker Ki67 (49). Urokinase plasminogen activator (uPA) and its receptor uPAR play an integral role in regulating pathways important in cell migration and invasion.57 A study done on subpopulation of SCLC cells from multiple cell lines demonstrated multidrug resistance, clonogenicity, and co-expressed the putative CSC marker CD44.58
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This system is useful to the physician as well as the user for determining the type of lung cancer and the stage of the cancer. This system is based on a simple algorithm and hence the accuracy is low. The accuracy can be increased by implementing more analysis techniques on the same database used in this system along with the current algorithm. The capability of this system for easy modification and continuous up gradation of the database is a plus point and increases the scope and life of the software.
Li et al (2008) described a computerized detection of lung nodules in thin-section CT images by selective enhancement filters and an automatic rule-based classifier. Their database has nodules of different sizes (4-28 mm, mean 10.2 mm), shapes, and patterns. This CAD scheme has five steps: lung segmentation, selective nodule enhancement, initial nodule detection, feature extraction, and classification. The key technique of their method is selective nodule enhancement filter for the significant enrichment of nodules and suppression of normal anatomic structures (blood vessels), which are the major sources of FP. Another key technique of their method is an automated rule-based classifier for reduction of FP. The experimental results indicated that their CAD scheme with its two key techniques minimizes overtraining effect and improved classification performance for nodules presenting large variations in size, shape, and pattern. Their CAD scheme achieved an overall sensitivity of 86% with 6.6 FP/patient.
PZ would like to thank all the senior members and staff of CytoViva, Inc (Auburn, AL, USA) (http://www.cytoviva. com) for their kind assistance, which enabled this proj- ect to be accomplished. LF developed the bronchoscope probe that creates the spectral library; Department of Interventional Pneumology, Ruhrlandklinik, West German Lung Center, University Hospital, University Duisburg- Essen, Essen, Germany. The authors thank PZ (http://www. bizjournals.com/phoenix/news/2011/10/20/visiongate-lands- 2-million-in.html) and KZ (http://www.visiongate3d.com/ about/collaborators) who are collaborators of Visiongate Cor- poration in the project for early detection of lung cancer.
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Nodal staging is key in the management of early-stage lung cancer. The prognosis and primary operability of a patient is influenced by the presence of mediastinal lymph node metastasis. Nodal staging is usually initiated using noninvasive radiological modalities such as chest computed tomography (CT) and integrated positron emission tomography (PET)-CT. According to the third American College of Chest Physicians guideline on nodal staging, further invasive staging can be waived in patients with a small-sized peripheral primary tumor (,3 cm) and a radiologically normal mediastinum. 1 In other