INTRODUCTION: Despite the use of modern minimally invasive surgical techniques, post-operative complications following lung cancer resection remain common and challenging to predict. Pulmonary ventilation imaging modalities offer detailed regional assessment of airflow obstruction and are highly sensitive to subclinical airway and/or parenchymal disease. Nevertheless, ventilation imaging is seldom integrated into pre-operative lung function assessment and risk stratification procedures. Therefore, the objective of this thesis was to quantify the burden of ventilation defects observed by Technegas SPECT and 129Xe MRI before lung cancer resection and establish their association with the occurrence and clinical impact of post-operative complications. METHODS: Patients undergoing lung cancer resection at St. Joseph’s Healthcare Hamilton were recruited into a prospective, proof-of-concept, six-week observational study. Participants were evaluated prior to resection surgery to document baseline demographics and clinical characteristics, performed standard pulmonary function tests and sputum induction, and underwent Technegas SPECT and 129Xe MRI to assess ventilation. Abnormal ventilation was quantified as the ventilation defect percent (VDP) and was considered abnormal if VDP was ≥mean+2 standard deviations of a healthy population. Following surgery, participants were followed for 4 weeks to document the incidence of post-operative complications, as specified by the Ottawa TM&M categorization system, and the length of hospital stay. RESULTS: One hundred and twenty-three participants were enrolled, of whom 103 were evaluated pre-operatively and followed for post-operative outcomes. Of the 103 participants (69±8 years, 58% female), 89% (92/103) underwent minimally invasive surgery, and 74% (76/103) underwent lobectomy. Abnormal ventilation was observed pre-operatively by Technegas SPECT and 129Xe MRI for 59% (58/99) and 84% (82/98) of participants, respectively. In a subset of 69 participants in whom sputum was collected, 51% (35/69) had intraluminal inflammation. A total of 64 post-operative complications occurred; 16 (25%) were pulmonary, and 48 (75%) were pleural complications. A post-operative complication occurred in 42% (41/103) of participants. Pre-operative Technegas SPECT and 129Xe MRI VDP were higher for participants with post-operative complications compared to those without (Technegas SPECT: 26±17% vs 19±7%, p=0.02; 129Xe MRI: 13±12% vs 7±6% p=0.003) and were positively correlated with post-operative length of hospital stay (Technegas SPECT: r=0.43, p<0.0001; 129Xe MRI: r=0.49, p<0.0001). Multivariable regression models revealed that preoperative Technegas SPECT and 129Xe MRI VDP were predictors of post-operative complications (Technegas SPECT: Odds ratio=1.08, p=0.005; 129Xe MRI: Odds ratio=1.16, p=0.002) and post-operative length of hospital stay (Technegas SPECT: unstandardized β=0.13, p<0.001; 129Xe MRI: unstandardized β=0.24, p<0.001). CONCLUSIONS: Abnormal ventilation, quantified by Technegas SPECT and 129Xe MRI VDP, is prevalent prior to lung cancer resection and a predictor of post-operative complications and length of hospital stay. / Thesis / Master of Science (MSc) / Post-operative complications are frequent adverse events following lung cancer resection, resulting in substantial patient morbidity and mortality that have a significant clinical and economic impact. Despite this, post-operative complications remain inadequately predicted, and limited research has been dedicated to reducing the risk of pulmonary complications after lung cancer resection. Standard clinical screening tools, such as pulmonary function tests, are used for patient selection in lung cancer resection surgery; however, they provide a global estimate of a complex multicompartment organ and may lack the sensitivity to detect subclinical lung pathology that influences post-operative outcomes. Thus, using high-resolution medical imaging modalities such as single photon emission computed tomography (SPECT) and magnetic resonance imaging (MRI), we investigated the prevalence and clinical relevance of abnormal ventilation, a functional consequence of airway and/or parenchymal disease. One hundred and three participants were enrolled in a six-week prospective, proof-of-concept observational study. Participants performed pre-operative imaging and were followed for four weeks post-operatively to document post-operative complications and relevant clinical outcomes. Pre-operative SPECT and MRI revealed a high prevalence of abnormal ventilation. The pre-operative ventilation defect burden was greater in participants who developed one or more complications during the four-week post-operative period and was an independent predictor of both the incidence of post-operative complications and the length of hospital stay. These observations provide proof-of-concept evidence that abnormal ventilation, assessed by two ventilation imaging modalities, is prevalent and clinically relevant prior to lung cancer resection. Taken together, this thesis establishes that ventilation imaging may have implications for risk stratification and risk modification in patients scheduled to undergo lung cancer resection.

Introduction Lung cancer is the most common cause of cancer-related death in the United States (US). Tobacco smoking is a well-recognized cause of lung cancer. About 2% of the United States (US) population lives in Tennessee (TN). Nearly 21 % of TN adults are current smokers as per 2019 data, compared to 14% across the US. The percentage of smokers has historically been high in TN and its surroundings. This can be attributed to the area's socio-economic and cultural characteristics, along with large areas of tobacco farming in the region. This increases the risk of lung cancer in the TN population. Surveillance Epidemiology and End Results Program (SEER) is a collection of cancer registries across the US, covering about 35% of the US population (TN cancer registry is not a part of SEER). Our study compares lung cancer incidence and characteristics in the TN cancer registry with the SEER 18 registry. Materials and Methods Data were collected from the TN cancer registry and SEER separately for lung and bronchial cancer. Data was analyzed for different histological subtypes, age groups, gender, stage at diagnosis, and rural/urban residence. Stata and Microsoft Excel were used in data analysis. A Chi-square test was used to calculate the statistical significance. Results From 2008 to 2017, 58644 cases of lung cancer were reported in the Tennessee cancer registry. During the same period, 519112 cases were reported in the SEER registry. The most frequent histological subtype of lung cancer in TN and SEER was adenocarcinoma (frequency of 17,503 Vs. 182346), followed by squamous cell carcinoma and small cell carcinoma. Most cancers in TN and SEER were diagnosed at stage of distant metastasis (46% vs. 52% ), followed by regional metastasis, localized, and in situ (Image1). The frequency of lung cancer diagnosis was high among those older than 65 in TN and SEER (64% vs. 69%). Males had a higher incidence of lung cancer in both registries. Most lung cancers were reported in the urban area in both registries. Chronic obstructive pulmonary disease was the most commonly reported secondary diagnosis (3,099), followed by pleural effusion in the TN database; the comparable data were not available in SEER. Relative survival at 12 months and five years for lung cancer in TN were 46.6 % and 19.5 % (Vs. 46.4% and 19.9% in SEER) Discussion and Conclusion If both registries were perfect, then lung and bronchial cancer incidence will be 9241 and 6048 per million in ten years in TN and SEER, respectively. But after careful analysis, we conclude that such analysis will be erroneous. The proportion of different histological types, stage at diagnosis, age groups, and gender were in the same order in both groups. Although chi-square test values are significant for all the variables, we infer no conclusion considering the data's inherent bias. Further in-depth analysis of the data is required.

Lung cancer is the number one cause of cancer related deaths in Ontario and throughout Canada. The 5-year survival rate for those diagnosed with lung cancer in 2020 was approximately 22.2%. Poor screening techniques is the main cause of low survival rates and late detection. Recent advancements in screening for lung cancer have led researchers to look at the benefits of using low-dose CT (LDCT) scanning to screen patients at high risk for lung cancer in order to detect the cancer in its earlier stages. There is strong evidence that using this new method of testing in lung cancer screening can reduce lung cancer related mortality by increasing the chance that the disease is detected in an earlier stage and in turn improving the patient’s chance at life saving treatment. Lung cancer screening requires LDCT resources and, based on the current recommendations, there is a concern that the new demand for imaging may exceed existing capacity of the imaging centers. This research evaluates impact of the Lung Cancer Screening Pilot for People at High Risk on the imaging resources and aims to answer the question: What would be the system performance for different imaging policies assuming a fixed imaging capacity? Administrative data from the Ottawa Hospital (TOH) as well as data from other research projects were used in order to develop and populate a simulation model. The policies that were assessed include: using biannual screening for patients who receive a negative baseline scan, using annual screening for patients with a negative baseline scan with all suspicious patients returning for a follow-up scan in six months, using annual screening for patients with a negative baseline scan with all suspicious patients returning for a follow-up scan in three months, using biannual screening for patients with a negative baseline scan with all suspicious patients returning for a follow-up scan in six months and using biannual screening for patients with a negative baseline scan with all suspicious patients returning for a follow-up scan in three months. These policies were assessed by looking at wait times for patients to be screened. Possible shift between lung cancer stages was also considered. The impact of this study is to look at system performances for different screening policies that could be used assuming a fixed imaging capacity. It represents a first step for further research should the data that is needed become available.

With the rising rates of heart disease incidents in the United States and the increase in lung cancer deaths as well, many individuals suffer and get their treatments compromised due to these diseases. Especially considering that many lung cancer and heart disease patients are over 70 years of age, treatment options and success rates drop significantly. Due to this, a great concern is raised for patients with co-existing heart disease and lung cancer. This was a case-control study that assessed lung cancer treatment options and success rates for patients with co-existing heart disease. We used research papers that discussed lung cancer treatment success in patients with heart disease to gather data on the subject. Furthermore, we used the 2020 NHIS to gather demographic data on the interviewed adults who answered the questions regarding lung cancer and heart disease. At the start, we hypothesized that there wasn’t going to be a high success rate for lung cancer treatment in patients with heart disease due to the invasive nature of the treatment available. We found that most patients with pre-existing heart disease that sought lung cancer treatment had their condition worsened due to severe invasive treatments such as chemotherapy and radiotherapy. In most surgical lung cancer treatment options, patients with pre-existing heart disease were more likely to die after the operation than patients without pre-existing heart disease. Currently and in future times, it’s more likely to find individuals with both diseases due to the rising culture which endorses poor habits in eating, alcohol consumption, smoking, and the utilization of drugs. Understanding the difficulty and dangers that are found in current treatment options for heart disease patients suffering from lung cancer will allow for innovation and improvement in treating such patients.

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The work in this thesis describes the approaches taken to advance the field of pulmonary optical molecular imaging for the diagnosis of unexplained pulmonary opacities in the critically ill patient where bacterial causes are suspected and the investigation of pulmonary nodules and masses where lung cancer is suspected. The bacterial work includes the development and assessment of a multivalent fluorescently labelled antimicrobial peptide fragment that allows for the in vivo in situ detection of bacteria in the distal lung. This Smartprobe (chapter 3), called NBD-UBIdend remains specific for bacteria and pathogenic pulmonary fungi (Aspergillus fumigatus) over mammalian cells, and has a clinically relevant limit of detection when it is imaged in an ex vivo whole lung ovine ventilated model using fibered confocal fluorescence microscopy (FCFM). Furthermore, NBD-UBIdend detects all bacteria assessed, including a panel that accounts for 70% of ventilator associated pneumonia causing organisms. Chapter 4, develops this further and describes the in vitro and ex vivo evaluation of another Smartprobe utilising a fluorescently labelled modified polymyxin B moiety, called NBD-PMX. This compound detects gram-negative but not gram-positive bacteria and is compatible with pulmonary FCFM. This combination of Smartprobes and FCFM could allow the immediate stratification of patient therapy in the assessment of pulmonary opacities where bacterial causes are suspected. The lung cancer work includes the use of label free FCFM in a clinical cohort to determine if autofluorescence patterns can differentiate benign and malignant pulmonary nodules. This work (chapter 5) demonstrates here there is no differentiation using FCFM alone and therefore, for this technology to be used in lung cancer diagnostics a Smartprobe strategy may be beneficial. Finally, chapter 6 demonstrates a Smartprobe based approach for interrogating lung cancer and discusses a matrix metalloproteinase (MMP) compound that detects MMPs in a whole ventilated lung utilising a modified spontaneous ovine pulmonary adenocarcinoma model.

Die vorliegende Arbeit beschäftigte sich mit der Frage, inwieweit zytologische Untersuchungsmaterialien von Patienten mit nichtkleinzelligen Lungenkarzinomen geeignet sind, zur molekularbiologischen Analyse möglicher Mutationen des k-ras-Genes verwendet zu werden. Dafür wurden vier spezifische Polymerasekettenreaktionen mit anschließenden Restriktionsfragmentlängenpolymorphismus-Analysen kreiert und optimiert. In der Folge wurden die k-ras-Mutationen in den verschiedenen Codons nach einer Agarose-Gelelektrophorese unter der UV-Kamera detektiert. Es wurden vergleichende Untersuchungen mit Materialien tumorfreien Gewebes durchgeführt. Ebenso wurden, um die Eignung des zytologischen Materiales zur k-ras-Mutationsdiagnostik nachzuweisen, Mutationsanalysen in histologischem Material durchgeführt und dieses mit den zytologischen Proben derselben Patienten verglichen. Weiterhin wurden bestimmte Korrelationen des k-ras-Mutationsstatus der Patienten mit individuellen und klinischen Parametern analysiert und mit aus der Literatur bekannten Aussagen verglichen. Es ist bekannt, dass k-ras-Mutationen im Tumor bei Patienten mit fortgeschrittenen nichtkleinzelligen Lungenkarzinomen negative Prädiktoren für einen möglichen Erfolg einer Rezeptortyrosinkinaseinhibitor-Therapie darstellen und die Prognose der Erkrankung verschlechtern. Neuartige Therapiekonzepte scheinen aber auch eine Möglichkeit zu bieten, Patienten mit nachgewiesener k-ras-Mutation eine Therapiealternative ermöglichen zu können. Die vorliegende Arbeit liefert einen wichtigen Beitrag um eine einfache Methode zur Analyse von k-ras-Mutationen bei Patienten mit nichtkleinzelligen Lungenkarzinomen zu finden und damit eine Entscheidung über etwaige weitere Therapieoptionen zu erleichtern.

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The diagnostic evaluation of ever smokers with pulmonary nodules represents a growing clinical challenge due to the implementation of lung cancer screening. The high false-positive rate of screening frequently results in the use of unnecessary invasive procedures in patients who are ultimately diagnosed as benign, clearly highlighting the need for additional diagnostic approaches. We previously derived and validated a bronchial epithelial gene-expression biomarker to detect lung cancer in ever smokers. However, bronchoscopy is not always chosen as a diagnostic modality. Given that bronchial and nasal epithelial gene-expression are similarly altered by cigarette smoke exposure, we sought to determine if cancer-associated gene-expression might also be detectable in the more readily accessible nasal epithelium. Nasal epithelial brushings were prospectively collected from ever smokers undergoing diagnostic evaluation for lung cancer in the AEGIS-1 (n=375) and AEGIS-2 (n=130) clinical trials and gene-expression profiled using microarrays. The computational framework used to discover biomarkers in these data was formalized and implemented in an open-source R-package. We identified 535 genes in the nasal epithelium of AEGIS-1 patients whose expression was associated with lung cancer status. Using matched bronchial gene-expression data from a subset of these patients, we found significantly concordant cancer-associated gene-expression alterations between the two airway sites. A nasal lung cancer classifier derived in the AEGIS-1 cohort that combined clinical factors and nasal gene-expression had significantly higher AUC (0.81) and sensitivity (0.91) than the clinical-factor model alone in independent samples from the AEGIS-2 cohort. These results support that the airway epithelial field of lung cancer-associated injury extends to the nose and demonstrates the potential of using nasal gene-expression as a non-invasive biomarker for lung cancer detection. The framework for deriving this biomarker was generalized and implemented in an open-source R-package. The package provides a computational pipeline to compare biomarker development strategies using microarray data. The results from this pipeline can be used to highlight the optimal model development parameters for a given dataset leading to more robust and accurate models. This package provides the community with a novel and powerful tool to facilitate biomarker discovery in microarray data.