Advanced Techniques for Image Quality Assessment of Modern X-ray Computed Tomography Systems

X-ray computed tomography (CT) imaging constitutes one of the most widely used diagnostic tools in radiology today with nearly 85 million CT examinations performed in the U.S in 2011. CT imparts a relatively high amount of radiation dose to the patient compared to other x-ray imaging modalities and as a result of this fact, coupled with its popularity, CT is currently the single largest source of medical radiation exposure to the U.S. population. For this reason, there is a critical need to optimize CT examinations such that the dose is minimized while the quality of the CT images is not degraded. This optimization can be difficult to achieve due to the relationship between dose and image quality. All things being held equal, reducing the dose degrades image quality and can impact the diagnostic value of the CT examination.

A recent push from the medical and scientific community towards using lower doses has spawned new dose reduction technologies such as automatic exposure control (i.e., tube current modulation) and iterative reconstruction algorithms. In theory, these technologies could allow for scanning at reduced doses while maintaining the image quality of the exam at an acceptable level. Therefore, there is a scientific need to establish the dose reduction potential of these new technologies in an objective and rigorous manner. Establishing these dose reduction potentials requires precise and clinically relevant metrics of CT image quality, as well as practical and efficient methodologies to measure such metrics on real CT systems. The currently established methodologies for assessing CT image quality are not appropriate to assess modern CT scanners that have implemented those aforementioned dose reduction technologies.

Thus the purpose of this doctoral project was to develop, assess, and implement new phantoms, image quality metrics, analysis techniques, and modeling tools that are appropriate for image quality assessment of modern clinical CT systems. The project developed image quality assessment methods in the context of three distinct paradigms, (a) uniform phantoms, (b) textured phantoms, and (c) clinical images.

The work in this dissertation used the “task-based” definition of image quality. That is, image quality was broadly defined as the effectiveness by which an image can be used for its intended task. Under this definition, any assessment of image quality requires three components: (1) A well defined imaging task (e.g., detection of subtle lesions), (2) an “observer” to perform the task (e.g., a radiologists or a detection algorithm), and (3) a way to measure the observer’s performance in completing the task at hand (e.g., detection sensitivity/specificity).

First, this task-based image quality paradigm was implemented using a novel multi-sized phantom platform (with uniform background) developed specifically to assess modern CT systems (Mercury Phantom, v3.0, Duke University). A comprehensive evaluation was performed on a state-of-the-art CT system (SOMATOM Definition Force, Siemens Healthcare) in terms of noise, resolution, and detectability as a function of patient size, dose, tube energy (i.e., kVp), automatic exposure control, and reconstruction algorithm (i.e., Filtered Back-Projection– FPB vs Advanced Modeled Iterative Reconstruction– ADMIRE). A mathematical observer model (i.e., computer detection algorithm) was implemented and used as the basis of image quality comparisons. It was found that image quality increased with increasing dose and decreasing phantom size. The CT system exhibited nonlinear noise and resolution properties, especially at very low-doses, large phantom sizes, and for low-contrast objects. Objective image quality metrics generally increased with increasing dose and ADMIRE strength, and with decreasing phantom size. The ADMIRE algorithm could offer comparable image quality at reduced doses or improved image quality at the same dose (increase in detectability index by up to 163% depending on iterative strength). The use of automatic exposure control resulted in more consistent image quality with changing phantom size.

Based on those results, the dose reduction potential of ADMIRE was further assessed specifically for the task of detecting small (<=6 mm) low-contrast (<=20 HU) lesions. A new low-contrast detectability phantom (with uniform background) was designed and fabricated using a multi-material 3D printer. The phantom was imaged at multiple dose levels and images were reconstructed with FBP and ADMIRE. Human perception experiments were performed to measure the detection accuracy from FBP and ADMIRE images. It was found that ADMIRE had equivalent performance to FBP at 56% less dose.

Using the same image data as the previous study, a number of different mathematical observer models were implemented to assess which models would result in image quality metrics that best correlated with human detection performance. The models included naïve simple metrics of image quality such as contrast-to-noise ratio (CNR) and more sophisticated observer models such as the non-prewhitening matched filter observer model family and the channelized Hotelling observer model family. It was found that non-prewhitening matched filter observers and the channelized Hotelling observers both correlated strongly with human performance. Conversely, CNR was found to not correlate strongly with human performance, especially when comparing different reconstruction algorithms.

The uniform background phantoms used in the previous studies provided a good first-order approximation of image quality. However, due to their simplicity and due to the complexity of iterative reconstruction algorithms, it is possible that such phantoms are not fully adequate to assess the clinical impact of iterative algorithms because patient images obviously do not have smooth uniform backgrounds. To test this hypothesis, two textured phantoms (classified as gross texture and fine texture) and a uniform phantom of similar size were built and imaged on a SOMATOM Flash scanner (Siemens Healthcare). Images were reconstructed using FBP and a Sinogram Affirmed Iterative Reconstruction (SAFIRE). Using an image subtraction technique, quantum noise was measured in all images of each phantom. It was found that in FBP, the noise was independent of the background (textured vs uniform). However, for SAFIRE, noise increased by up to 44% in the textured phantoms compared to the uniform phantom. As a result, the noise reduction from SAFIRE was found to be up to 66% in the uniform phantom but as low as 29% in the textured phantoms. Based on this result, it clear that further investigation was needed into to understand the impact that background texture has on image quality when iterative reconstruction algorithms are used.

To further investigate this phenomenon with more realistic textures, two anthropomorphic textured phantoms were designed to mimic lung vasculature and fatty soft tissue texture. The phantoms (along with a corresponding uniform phantom) were fabricated with a multi-material 3D printer and imaged on the SOMATOM Flash scanner. Scans were repeated a total of 50 times in order to get ensemble statistics of the noise. A novel method of estimating the noise power spectrum (NPS) from irregularly shaped ROIs was developed. It was found that SAFIRE images had highly locally non-stationary noise patterns with pixels near edges having higher noise than pixels in more uniform regions. Compared to FBP, SAFIRE images had 60% less noise on average in uniform regions for edge pixels, noise was between 20% higher and 40% lower. The noise texture (i.e., NPS) was also highly dependent on the background texture for SAFIRE. Therefore, it was concluded that quantum noise properties in the uniform phantoms are not representative of those in patients for iterative reconstruction algorithms and texture should be considered when assessing image quality of iterative algorithms.

The move beyond just assessing noise properties in textured phantoms towards assessing detectability, a series of new phantoms were designed specifically to measure low-contrast detectability in the presence of background texture. The textures used were optimized to match the texture in the liver regions actual patient CT images using a genetic algorithm. The so called “Clustured Lumpy Background” texture synthesis framework was used to generate the modeled texture. Three textured phantoms and a corresponding uniform phantom were fabricated with a multi-material 3D printer and imaged on the SOMATOM Flash scanner. Images were reconstructed with FBP and SAFIRE and analyzed using a multi-slice channelized Hotelling observer to measure detectability and the dose reduction potential of SAFIRE based on the uniform and textured phantoms. It was found that at the same dose, the improvement in detectability from SAFIRE (compared to FBP) was higher when measured in a uniform phantom compared to textured phantoms.

The final trajectory of this project aimed at developing methods to mathematically model lesions, as a means to help assess image quality directly from patient images. The mathematical modeling framework is first presented. The models describe a lesion’s morphology in terms of size, shape, contrast, and edge profile as an analytical equation. The models can be voxelized and inserted into patient images to create so-called “hybrid” images. These hybrid images can then be used to assess detectability or estimability with the advantage that the ground truth of the lesion morphology and location is known exactly. Based on this framework, a series of liver lesions, lung nodules, and kidney stones were modeled based on images of real lesions. The lesion models were virtually inserted into patient images to create a database of hybrid images to go along with the original database of real lesion images. ROI images from each database were assessed by radiologists in a blinded fashion to determine the realism of the hybrid images. It was found that the radiologists could not readily distinguish between real and virtual lesion images (area under the ROC curve was 0.55). This study provided evidence that the proposed mathematical lesion modeling framework could produce reasonably realistic lesion images.

Based on that result, two studies were conducted which demonstrated the utility of the lesion models. The first study used the modeling framework as a measurement tool to determine how dose and reconstruction algorithm affected the quantitative analysis of liver lesions, lung nodules, and renal stones in terms of their size, shape, attenuation, edge profile, and texture features. The same database of real lesion images used in the previous study was used for this study. That database contained images of the same patient at 2 dose levels (50% and 100%) along with 3 reconstruction algorithms from a GE 750HD CT system (GE Healthcare). The algorithms in question were FBP, Adaptive Statistical Iterative Reconstruction (ASiR), and Model-Based Iterative Reconstruction (MBIR). A total of 23 quantitative features were extracted from the lesions under each condition. It was found that both dose and reconstruction algorithm had a statistically significant effect on the feature measurements. In particular, radiation dose affected five, three, and four of the 23 features (related to lesion size, conspicuity, and pixel-value distribution) for liver lesions, lung nodules, and renal stones, respectively. MBIR significantly affected 9, 11, and 15 of the 23 features (including size, attenuation, and texture features) for liver lesions, lung nodules, and renal stones, respectively. Lesion texture was not significantly affected by radiation dose.

The second study demonstrating the utility of the lesion modeling framework focused on assessing detectability of very low-contrast liver lesions in abdominal imaging. Specifically, detectability was assessed as a function of dose and reconstruction algorithm. As part of a parallel clinical trial, images from 21 patients were collected at 6 dose levels per patient on a SOMATOM Flash scanner. Subtle liver lesion models (contrast = -15 HU) were inserted into the raw projection data from the patient scans. The projections were then reconstructed with FBP and SAFIRE (strength 5). Also, lesion-less images were reconstructed. Noise, contrast, CNR, and detectability index of an observer model (non-prewhitening matched filter) were assessed. It was found that SAFIRE reduced noise by 52%, reduced contrast by 12%, increased CNR by 87%. and increased detectability index by 65% compared to FBP. Further, a 2AFC human perception experiment was performed to assess the dose reduction potential of SAFIRE, which was found to be 22% compared to the standard of care dose.

In conclusion, this dissertation provides to the scientific community a series of new methodologies, phantoms, analysis techniques, and modeling tools that can be used to rigorously assess image quality from modern CT systems. Specifically, methods to properly evaluate iterative reconstruction have been developed and are expected to aid in the safe clinical implementation of dose reduction technologies.

Multi-purpose utility of circulating plasma DNA testing in patients with advanced cancers.

Tumor genomic instability and selective treatment pressures result in clonal disease evolution; molecular stratification for molecularly targeted drug administration requires repeated access to tumor DNA. We hypothesized that circulating plasma DNA (cpDNA) in advanced cancer patients is largely derived from tumor, has prognostic utility, and can be utilized for multiplex tumor mutation sequencing when repeat biopsy is not feasible. We utilized the Sequenom MassArray System and OncoCarta panel for somatic mutation profiling. Matched samples, acquired from the same patient but at different time points were evaluated; these comprised formalin-fixed paraffin-embedded (FFPE) archival tumor tissue (primary and/or metastatic) and cpDNA. The feasibility, sensitivity, and specificity of this high-throughput, multiplex mutation detection approach was tested utilizing specimens acquired from 105 patients with solid tumors referred for participation in Phase I trials of molecularly targeted drugs. The median cpDNA concentration was 17 ng/ml (range: 0.5-1600); this was 3-fold higher than in healthy volunteers. Moreover, higher cpDNA concentrations associated with worse overall survival; there was an overall survival (OS) hazard ratio of 2.4 (95% CI 1.4, 4.2) for each 10-fold increase in cpDNA concentration and in multivariate analyses, cpDNA concentration, albumin, and performance status remained independent predictors of OS. These data suggest that plasma DNA in these cancer patients is largely derived from tumor. We also observed high detection concordance for critical 'hot-spot' mutations (KRAS, BRAF, PIK3CA) in matched cpDNA and archival tumor tissue, and important differences between archival tumor and cpDNA. This multiplex sequencing assay can be utilized to detect somatic mutations from plasma in advanced cancer patients, when safe repeat tumor biopsy is not feasible and genomic analysis of archival tumor is deemed insufficient. Overall, circulating nucleic acid biomarker studies have clinically important multi-purpose utility in advanced cancer patients and further studies to pursue their incorporation into the standard of care are warranted.

A phase I pharmacokinetic and pharmacodynamic study of the oral mitogen-activated protein kinase kinase (MEK) inhibitor, WX-554, in patients with advanced solid tumours

Purpose: We performed a multi-centre phase I study to assess the safety, pharmacokinetics (PK) and pharmacodynamics (PD) of the orally available small molecule mitogen-activated protein kinase kinase (MEK) 1/2 inhibitor, WX-554, and to determine the optimal biological dose for subsequent trials.
Experimental design: Patients with treatment-refractory, advanced solid tumours, with adequate performance status and organ function were recruited to a dose-escalation study in a standard 3 + 3 design. The starting dose was 25 mg orally once weekly with toxicity, PK and PD guided dose-escalation with potential to explore alternative schedules.
Results: Forty-one patients with advanced solid tumours refractory to standard therapies and with adequate organ function were recruited in eight cohorts up to doses of 150 mg once weekly and 75 mg twice weekly. No dose-limiting toxicities were observed during the study, and a maximum tolerated dose (MTD) was not established. The highest dose cohorts demonstrated sustained inhibition of extracellular signal-regulated kinase (ERK) phosphorylation in peripheral blood mononuclear cells following ex-vivo phorbol 12-myristate 13-acetate stimulation. There was a decrease of 70 ± 26% in mean phosphorylated (p)ERK in C1 day 8 tumour biopsies when compared with pre-treatment tumour levels in the 75 mg twice a week cohort. Prolonged stable disease (>6 months) was seen in two patients, one with cervical cancer and one with ampullary carcinoma.
Conclusions: WX-554 was well tolerated, and an optimal biological dose was established for further investigation in either a once or twice weekly regimens. The recommended phase 2 dose is 75 mg twice weekly.

3531: Neoadjuvant radiotherapy (RT) combined with capecitabine (Cape) and sorafenib (Sor) in patients (pts) with locally advanced, k-ras-mutated rectal cancer (LARC): A phase I/II trial SAKK 41/08

Background: K-ras mutation is found in up to 40% of LARC. Sor is a multitarget tyrosine kinase inhibitor including raf and VEGFR and has demonstrated radiosensitizing effects. Sor might improve outcome of standard preoperative radio-chemotherapy in patients with k-ras mutated LARC. Methods: Pts with k-ras mutated T3-4 and/or N+, M0 disease by MRI were included. Recommended doses from phase I part consisted of RT 1.8 Gy/day x25 with Cape 825mg/m2bid x 33 in combination with Sor 400mg/d. The primary endpoint for the phase II part was pathological complete response (pCR) prospectively defined as grade 3 (near complete regression) or 4 (complete regression) in the histological grading system according to Dworak (DC). A pCR rate of 8% or lower was considered uninteresting and of 22% or higher was promising. Secondary endpoints included sphincter preservation, R0 resection, downstaging and safety. Results: 54 pts were treated in 18 centers in Switzerland und Hungary, 40 pts were included into the single arm phase II part. Median dose intensity per day was 100.0% for RT, 98.6% for Cape and 100.0% for Sor respectively. pCR rate was 60.0% (95%CI: 43.3%, 75.1%) by central independent pathological review (15.0% DC grade 4; 45.0% DC grade 3). Sphincter preservation was achieved in 89.5%, R0 resection in 94.7% and downstaging in 81.6% of the pts. The most common grade 3 toxicities included diarrhea (15.0%), skin toxicity outside of the RT field (12.5%), pain (7.5%), skin toxicity in RT field, proctitis, fatigue and cardiac ischemia (each 5.0%). Laboratory AEs grade 3/4 were neutropenia (1 pt grade 4; 1 grade 3), creatinine elevation (1 pt grade 3). Conclusions: The combination of Sor to standard RCT with Cape in k-ras mutated LARC tumors is highly active with acceptable toxicity and deserves further investigation.

A new age of fuel performance code criteria studied through advanced atomistic simulation techniques

A fundamental step in understanding the effects of irradiation on metallic uranium and uranium dioxide ceramic fuels, or any material, must start with the nature of radiation damage on the atomic level. The atomic damage displacement results in a multitude of defects that influence the fuel performance. Nuclear reactions are coupled, in that changing one variable will alter others through feedback. In the field of fuel performance modeling, these difficulties are addressed through the use of empirical models rather than models based on first principles. Empirical models can be used as a predictive code through the careful manipulation of input variables for the limited circumstances that are closely tied to the data used to create the model. While empirical models are efficient and give acceptable results, these results are only applicable within the range of the existing data. This narrow window prevents modeling changes in operating conditions that would invalidate the model as the new operating conditions would not be within the calibration data set. This work is part of a larger effort to correct for this modeling deficiency. Uranium dioxide and metallic uranium fuels are analyzed through a kinetic Monte Carlo code (kMC) as part of an overall effort to generate a stochastic and predictive fuel code. The kMC investigations include sensitivity analysis of point defect concentrations, thermal gradients implemented through a temperature variation mesh-grid, and migration energy values. In this work, fission damage is primarily represented through defects on the oxygen anion sublattice. Results were also compared between the various models. Past studies of kMC point defect migration have not adequately addressed non-standard migration events such as clustering and dissociation of vacancies. As such, the General Utility Lattice Program (GULP) code was utilized to generate new migration energies so that additional non-migration events could be included into kMC code in the future for more comprehensive studies. Defect energies were calculated to generate barrier heights for single vacancy migration, clustering and dissociation of two vacancies, and vacancy migration while under the influence of both an additional oxygen and uranium vacancy.

STATISTICAL METHODS FOR ADVANCED ECONOMETRIC MODELS WITH APPLICATIONS TO VEHICLE HOLDING AND SPEED QUANTILES DISTRIBUTION

This dissertation proposes statistical methods to formulate, estimate and apply complex transportation models. Two main problems are part of the analyses conducted and presented in this dissertation. The first method solves an econometric problem and is concerned with the joint estimation of models that contain both discrete and continuous decision variables. The use of ordered models along with a regression is proposed and their effectiveness is evaluated with respect to unordered models. Procedure to calculate and optimize the log-likelihood functions of both discrete-continuous approaches are derived, and difficulties associated with the estimation of unordered models explained. Numerical approximation methods based on the Genz algortithm are implemented in order to solve the multidimensional integral associated with the unordered modeling structure. The problems deriving from the lack of smoothness of the probit model around the maximum of the log-likelihood function, which makes the optimization and the calculation of standard deviations very difficult, are carefully analyzed. A methodology to perform out-of-sample validation in the context of a joint model is proposed. Comprehensive numerical experiments have been conducted on both simulated and real data. In particular, the discrete-continuous models are estimated and applied to vehicle ownership and use models on data extracted from the 2009 National Household Travel Survey. The second part of this work offers a comprehensive statistical analysis of free-flow speed distribution; the method is applied to data collected on a sample of roads in Italy. A linear mixed model that includes speed quantiles in its predictors is estimated. Results show that there is no road effect in the analysis of free-flow speeds, which is particularly important for model transferability. A very general framework to predict random effects with few observations and incomplete access to model covariates is formulated and applied to predict the distribution of free-flow speed quantiles. The speed distribution of most road sections is successfully predicted; jack-knife estimates are calculated and used to explain why some sections are poorly predicted. Eventually, this work contributes to the literature in transportation modeling by proposing econometric model formulations for discrete-continuous variables, more efficient methods for the calculation of multivariate normal probabilities, and random effects models for free-flow speed estimation that takes into account the survey design. All methods are rigorously validated on both real and simulated data.

Neoadjuvant chemotherapy in Albinos with locally advanced skin cancer at a Blantyre Hospital: - Case Series

Albinism in Africa remains a public health concern with increasing numbers of advanced skin cancer in this population at presentation. There are challenges with availability of Radiotherapy (RT) units in Africa which is an important modality for controlling loco-regional disease alone or in combination with surgery. Proposed chemotherapy regimens have not been well validated through Randomized Controlled Trials thus posing difficulties for standard of care for units that do not have access to functional RT facilities. Malawi is one such country without radiotherapy. Case summary Seven patients with locally advanced skin cancer were seen in the adult oncology unit at Queen Elizabeth Central Hospital in Blantyre (QECH), Malawi between 2010 and 2013. QECH is one of the teaching hospitals in the country. All were subjected to neo-adjuvant chemotherapy. The primary treatment aim was cyto-reduction followed by surgery whilst the secondary outcome was general symptom control. Three patients achieved complete responses of which two underwent resection and a pectoralis major myocutaneous flap. One had a near complete response and three showed partial responses. Conclusion Neo-adjuvant chemotherapy may be a possible.

Sensing parasites: proteomic and advanced bio-detection alternatives

[EN] Parasitic diseases have a great impact in human and animal health. The gold standard for the diagnosis of the majority of parasitic infections is still conventional microscopy, which presents important limitations in terms of sensitivity and specificity and commonly requires highly trained technicians. More accurate molecular-based diagnostic tools are needed for the implementation of early detection, effective treatments and massive screenings with high-throughput capacities. In this respect, sensitive and affordable devices could greatly impact on sustainable control programmes which exist against parasitic diseases, especially in low income settings. Proteomics and nanotechnology approaches are valuable tools for sensing pathogens and host alteration signatures within micro fluidic detection platforms. These new devices might provide novel solutions to fight parasitic diseases. Newly described specific parasite derived products with immune-modulatory properties have been postulated as the best candidates for the early and accurate detection of parasitic infections as well as for the blockage of parasite development. This review provides the most recent methodological and technological advances with great potential for biosensing parasites in their hosts, showing the newest opportunities offered by modern “-omics” and platforms for parasite detection and control.

Analysis of Outcome of Intraplueral Streptokinase in Pediatric Empyema Thoracis even in Advanced Stages: A Prospective Study

Background: Empyema thoracis in children causes significant morbidity. Standard treatment of Empyema thoracis includes tube drainage and antibiotics. But the tube drainage often fails. Intrapleural Streptokinase has been used in empyema thoracis with good success rate. Objectives: We evaluated the efficacy of intra-pleural Streptokinase in management of empyema thoracis even in advanced stages. Patients and Methods: A total of 28 patients with empyema thoracis requiring intercostal tube drainage aged zero to twelve years were included in the study who were admitted in Pediatric intensive care unit. 15,000 units/kg of Streptokinase was instilled into the pleural cavity. Response was assessed by clinical outcome, after unclamping and subsequent chest radiography and serial chest ultrasounds. Results: Streptokinase enhanced drainage in all patients with complete resolution of empyema thoracis in 26 patients. Two patients were referred for surgery. Only 7.2% required surgery. Streptokinase was equally effective if started before or after seven days. Conclusions: Intrapleural Streptokinase is the preferred treatment for treating pediatric empyema thoracis even in advanced stages and can avoid surgery.

Outcome analysis of predictors in locally advanced pancreatic cancer

Guidelines report a wide range of options in locally advanced pancreatic cancer (LAPC): definitive chemotherapy or chemoradiotherapy or the emerging stereotactic body radiotherapy (SBRT) (+/- chemotherapy). On behalf of the AIRO (Italian Association of Radiation Oncology and Clinical Oncology) Gastrointestinal Study Group, we collected retrospective clinical data on 419 LAPC from 15 Italian centers. The study protocol (PAULA-1: Pooled Analysis in Unresectable Locally Advanced pancreatic cancer) was approved by institutional review board of S. Orsola-Malpighi Hospital (201/2015/O/OssN). From this large database we performed tree different studies. The first was a retrospective study about 56 LAPC treated with SBRT at a median biologically equivalent dose of 48 Gy +/- chemotherapy. We demonstrated a statistically significant impact of biologically equivalent dose based on an α/β ratio of 10Gy ≥ 48Gy for local control (LC) (p: 0.045) and overall survival (p: 0.042) in LAPC. The second was a retrospective matched-cohort case-control study comparing SBRT (40 patients) and chemoradiation (40 patients) in LAPC in terms of different endpoints. Our findings suggested an equivalence in terms of most outcomes among the two treatments and an advantage of SBRT in terms of LC (p: 0.017). The third study was a retrospective comparison of definitive chemotherapy, chemoradiotherapy and SBRT (+/- chemotherapy) in terms of different outcomes in LAPC. A predictive model for LC in LAPC was also developed reaching an AUC of 68% (CI 58,7%-77,4%). SBRT treatment emerged as a positive predictive factor for improved LC. Findings deriving from our three studies suggest that SBRT is comparable to standard of care (definitive chemotherapy and chemoradiotherapy) in terms of outcomes. SBRT seems to be an emerging therapeutic option in LAPC significantly improving local control. Furthermore, we have shown the potential of a predictive model for LC. Randomized trials are needed to compare these different therapeutic options in LAPC.

Advanced Mission Synthesis Algorithms for Vibration-based Accelerated Life-testing

In the field of vibration qualification testing, with the popular Random Control mode of shakers, the specimen is excited by random vibrations typically set in the form of a Power Spectral Density (PSD). The corresponding signals are stationary and Gaussian, i.e. featuring a normal distribution. Conversely, real-life excitations are frequently non-Gaussian, exhibiting high peaks and/or burst signals and/or deterministic harmonic components. The so-called kurtosis is a parameter often used to statistically describe the occurrence and significance of high peak values in a random process. Since the similarity between test input profiles and real-life excitations is fundamental for qualification test reliability, some methods of kurtosis-control can be implemented to synthesize realistic (non-Gaussian) input signals. Durability tests are performed to check the resistance of a component to vibration-based fatigue damage. A procedure to synthesize test excitations which starts from measured data and preserves both the damage potential and the characteristics of the reference signals is desirable. The Fatigue Damage Spectrum (FDS) is generally used to quantify the fatigue damage potential associated with the excitation. The signal synthesized for accelerated durability tests (i.e. with a limited duration) must feature the same FDS as the reference vibration computed for the component’s expected lifetime. Current standard procedures are efficient in synthesizing signals in the form of a PSD, but prove inaccurate if reference data are non-Gaussian. This work presents novel algorithms for the synthesis of accelerated durability test profiles with prescribed FDS and a non-Gaussian distribution. An experimental campaign is conducted to validate the algorithms, by testing their accuracy, robustness, and practical effectiveness. Moreover, an original procedure is proposed for the estimation of the fatigue damage potential, aiming to minimize the computational time. The research is thus supposed to improve both the effectiveness and the efficiency of excitation profile synthesis for accelerated durability tests.

Surgery after biological therapy in locally advanced NSCLC with molecular driver: feasibility and effectiveness of a new multidisciplinary approach

Introduction: Surgical outcomes after biological therapy have not been investigated yet and no information about timing, postoperative complications and survival have been recorded. Methods: This is a prospective study which compares a group of stage IIIA and IIIB NSCLC patients treated with biological therapy with patients undergoing standard induction chemotherapy. Data reported are preliminary results on the safety and effectiveness of surgery after target therapy. Results: We compared 22 patients treated with standard chemotherapy (Group 1) and 6 patients who received target therapy (Group 2). No differences were observed with an important bias due to the limited number of cases. The median time of resection was 159.8 ± 62.8 for group 1 and 201 ± 57.8 for group 2 (p=0.194). Complete resection was obtained in all Group 1-cases. Post-operative complication rate was 22% vs 16% (p=1). Pathologists reported necrosis >50% in 13% in group 1, Fibrosis >50% was presents respectively in 27% and 33% of patients (p=1). Residual vital tumor was >50% in 77% of patients undergone CT and in 66% of patients undergone TT (p=0.622). A total of 6 (31%) patients in the CT-group developed recurrence, 3 in the TT- group (64.2%), p was 0.634. No difference was observed both in terms of OS (P=0.29, Figure 3) and in term of DFS (P=0.106, Figure 4). Discussion: There is no consensus in the use of target therapy for advanced tumor in association with surgery. EGFR-tyrosine kinase inhibitors showed higher and more rapid response and our study wants to demonstrate that surgery after target therapy gives full access to the advantage of definitive local treatment. In our series, despite fibrosis, radical surgery has been achieved in all patients operated. The intraoperative blood loss, operation time, postoperative hospital stay and postoperative complication rate seems to be similar.

Development of Advanced Combustions using Cylinder Pressure Signal

Zero-carbon powertrains development has become one of the main challenges for automotive industries around the world. Following this guideline, several approaches such as powertrain electrification, advanced combustions, and hydrogen internal combustion engines have been aimed to achieve the goal. Low Temperature Combustions, characterized by a simultaneous reduction of fuel consumption and emissions, represent one of the most studied solutions moving towards a sustainable mobility. Previous research demonstrate that Gasoline partially premixed Compression Ignition combustion is one of the most promising LTC. Mainly characterized by the high-pressure direct-injection of gasoline and the spontaneous ignition of the premixed air-fuel mixture, GCI combustion has shown a good potential to achieve the high thermal efficiency and low pollutants in compression ignited engines required by future emission regulations. Despite its potential, GCI combustion might suffer from low combustion controllability and stability, because gasoline spontaneous ignition is significantly affected by slight variations of the local in-cylinder thermal conditions. Therefore, to properly control GCI combustion assuring the maximum performance, a deep knowledge of the combustion process, i.e., gasoline auto-ignition and the effect of the control parameters on the combustion and pollutants, is mandatory. This PhD dissertation focuses on the study of GCI combustion in a light-duty compression ignited engine. Starting from a standard 1.3L diesel engine, this work describes the activities made moving toward the full conversion of the engine. A preliminary study of the GCI combustion was conducted in a “Single-Cylinder” engine configuration highlighting combustion characteristics and dependencies on the control parameters. Then, the full engine conversion was performed, and a wide experimental campaign allowed to confirm the benefits of this advanced combustion methodologies in terms of pollutants and thermal efficiency. The analysis of the in-cylinder pressure signal allowed to study in depth the GCI combustion and develop control-oriented models aimed to improve the combustion stability.

Inside standard and hyperspectral low-dose CT variational imaging: parameter identification and material decomposition

The main contribution of this thesis is the proposal of novel strategies for the selection of parameters arising in variational models employed for the solution of inverse problems with data corrupted by Poisson noise. In light of the importance of using a significantly small dose of X-rays in Computed Tomography (CT), and its need of using advanced techniques to reconstruct the objects due to the high level of noise in the data, we will focus on parameter selection principles especially for low photon-counts, i.e. low dose Computed Tomography. For completeness, since such strategies can be adopted for various scenarios where the noise in the data typically follows a Poisson distribution, we will show their performance for other applications such as photography, astronomical and microscopy imaging. More specifically, in the first part of the thesis we will focus on low dose CT data corrupted only by Poisson noise by extending automatic selection strategies designed for Gaussian noise and improving the few existing ones for Poisson. The new approaches will show to outperform the state-of-the-art competitors especially in the low-counting regime. Moreover, we will propose to extend the best performing strategy to the hard task of multi-parameter selection showing promising results. Finally, in the last part of the thesis, we will introduce the problem of material decomposition for hyperspectral CT, which data encodes information of how different materials in the target attenuate X-rays in different ways according to the specific energy. We will conduct a preliminary comparative study to obtain accurate material decomposition starting from few noisy projection data.

Advanced imaging study in cerebrovascular pathology for the personalization of therapy: from the capillary microcirculation to the vessel wall

Objectives: To investigate the use of intravascular optical coherence tomography (IVOCT) for carotid artery stenting (CAS) procedures in patients with atherosclerotic stenosis. Examine possible markers that might identify the onset of new cerebral ischemic lesions on MRI. Specifically, attention was drawn to the morphological features of the used dual layer stent, which could be underestimated during traditional CAS procedures. Secondary goals are to compare the safety and efficacy of different CAS techniques and the accuracy of the vessel analysis software’s on pre-operative CTA examination used to quantify ICA stenosis with the gold standard IVOCT. Material and Methods: Ten patients underwent CAS procedure with flow-arrest technique and IVOCT evaluations prior to and following stent deployment, while five matched patients underwent CAS procedure with distal embolic protection device (EPD) technique. All patients underwent 24-hours 3T MRI examination to check for ischemic lesions; all patients were treated with the same dual-layer stent. Results: Patients with new ischemic lesions demonstrated peculiar stent configuration in the distal end, and a strong Spearman’s rank order correlation was found among the volume of new DWI lesions and the stent configuration in its distal end (Rs: 0.81; p <0.001). No statistically significant differences were observed in the total burden of new ischemic lesions for each technique. The vessel analysis software's on CTA comparison demonstrated a higher diagnostic accuracy in the degree of ICA stenosis compared to the gold standard of IVOCT of the specialized software (ROC curve = 0.63; p = 0.06) compared to the general software (ROC curve = 0.57, p = 0.31). Conclusions: Study’s results support the use of IVOCT to allow recognition of potential features that can predict the onset of new cerebral ischemic lesions. Additionally, IVOCT made it possible to evaluate specialized software's increased accuracy in the pre-operative evaluation of ICA atherosclerotic stenosis.