A Importância de estudos dinâmicos em PET/CT para avaliação de doenças oncológicas

A Medicina Nuclear (MN) permite investigar o estado fisiológico dos tecidos de forma minimamente invasiva, usando radiofármacos (rf’s), moléculas compostas por um análogo biológico específico desses processos fisiológicos e um marcador radioativo (radionuclídeo). PET/CT (do acrónimo inglês Positron Emission Tomography/Computed Tomography), uma das modalidades de imagem em MN, está a expandir-se rapidamente em muitos Países. As imagens obtidas revelam a biodistribuição dos rf’s usados e permitem conhecer a sua distribuição precisa no organismo. 18F-Fluorodesoxiglicose (FDG), um análogo da glicose, é o rf mais comumente utilizado, isto porque em neoplasias as células são geralmente caracterizadas pelo aumento do metabolismo da glicose. A quantificação realizada em imagens de PET, tem por base uma estimativa quantitativa do metabolismo da glicose no tumor, utilizando o índice de captação estandardizado, SUV (do acrónimo inglês Standard Uptake Value). A realização de estudos dinâmicos em PET/CT, isto é, realizados em sequência temporal imediatamente após a administração endovenosa do rf e, durante um período de tempo pré-determinado (por exemplo, 15 minutos) permite que o registo da cinética inicial dos rf’s seja estudado. A análise dos dados obtidos com o estudo dinâmico permite compreender o grau e a perfusão tumoral. Habitualmente, quanto maior a captação de 18F-FDG num tumor, maior é a sua atividade metabólica glicolítica, o que tem sido traduzido em maior agressividade tumoral. Nesta investigação, realizaram-se estudos dinâmicos num grupo restrito de patologias oncológicas, nomeadamente: carcinoma da bexiga, carcinoma do colo do útero, carcinoma colorretal, carcinoma do endométrio, metástases hepáticas e adenocarcinoma pancreático. Realizaram-se estudos dinâmicos durante cerca de 10/15 minutos, com 1minuto por frame. O objetivo desta Investigação é tentar compreender se, tumores com maior perfusão respondem melhor à Radioterapia (RT), ou se, a resposta é independente da perfusão. Para avaliar os valores de SUV’s ao longo tempo, realizaram-se ROI’s (do acrónimo inglês Region of Interest), nas artérias femorais ou aorta e na lesão tumoral. Com estes dados, criaram-se gráficos de atividade/tempo onde, no eixo das abcissas é representado o tempo e no eixo das ordenadas os valores de SUV. A partir destes gráficos e dos dados neles contidos, calculou-se o Índice de Perfusão Tumoral através de 2 métodos: A, Método Trapezoidal de Aproximação que relaciona a razão entre a área perfusional do tumor e a área de fluxo arterial, até ao momento do cruzamento das curvas; B, mais simples, calculando o Índice de Perfusão do Tumor através da razão entre o valor de SUV máximo da curva tumoral e da curva arterial até ao momento do cruzamento das curvas. O Método de Comparação de Métodos de Altman&Bland, revelou que tanto o método A como o método B são semelhantes para o cálculo do Índice de Perfusão Tumoral. Em conclusão, apesar do número reduzido de indivíduos estudados, os dados apresentados indicam que existe uma tendência para que haja melhor resposta à RT por parte dos tumores com maior índice metabólico e maior índice de perfusão. Os tumores com menor índice metabólico e menor grau perfusional parece que respondem pior à RT.

Submucosal Hemangioma of the Trachea in an Infant: Diagnosis and Follow-Up with 3D-CT/Bronchoscopy

Introduction: Infantile hemangiomas of the airway are diagnosed at bronchoscopy as part of the investigation of stridor or other respiratory symptoms. Here, we present three-dimensional computed tomography (3D-CT)/bronchoscopy findings of submucosal subglottic hemangioma missed at bronchoscopy. Case Presentation: We report on the clinical usefulness of 3D-CT/bronchoscopy as the primary diagnostic tool and follow-up method in the evaluation of suspected airway infantile hemangiomas, especially when the hemangioma is the submucosal type. Conclusions: 3D-CT/bronchoscopy will reduce the need for invasive laryngoscopic studies and help to diagnose submucosal hemangiomas undetected on laryngoscope. Additionally, 3D-CT/bronchoscopy will help evaluating the extent of the lesion, degree of airway narrowing, and treatment response.

Evaluation of tumor recurrences after radical prostatectomy using 18F-Choline PET/CT and 3T multiparametric MRI without endorectal coil: a single center experience

The aim os this study is to evaluate and compare the utility of 18F-fluorocholine (18F-CH) PET/CT versus 3-Tesla multiparametric MRI (mpMRI) without endorectal coil to detect tumor recurrences in patients with biochemical relapse following radical prostatectomy (RP). Secondarily, to identify possible prognostic variables associated with mpMRI and 18F-CH PET/CT findings. Retrospective study of 38 patients who developed biochemical recurrence after RP between the years 2011 and 2015 at our institution. PET/CT and mpMRI were both performed within 30 days of each other in all patients. The PET/CT was reviewed by a nuclear medicine specialist while the mpMRI was assessed by a radiologist, both of whom were blinded to outcomes. The median prostate-specific antigen (PSA) value pre-MRI/PET-CT was 0.9 ng/mL (interquartile range 0.4–2.2 ng/mL). There were no differences in the detection rate between 18F-CH PET/CT and mpMRI for local recurrence (LR), lymph node recurrence (LNR) and bone metastases (BM). Separately, mpMRI and 18F-CH PET/CT were positive for recurrence in 55.2% and 52.6% of cases, respectively, and in 65.7% of cases when findings from both modalities were considered together. The detection of LR was better with combined mpMRI and choline PET/CT versus choline PET/CT alone (34.2% vs 18.4%, p = 0.04). Salvage treatment was modified in 22 patients (57.8%) based on the imaging findings. PSA values on the day of biochemical failure were significantly associated with mpMRI positivity (adjusted odds ratio (OR): 30.9; 95% confidence interval (CI): 1.5–635.8). Gleason score > 7 was significantly associated with PET/CT positivity (OR: 13.9; 95% CI: 1.5–125.6). A significant association was found between PSA doubling time (PSADT) (OR: 1.3; 95% CI: 1.0–1.7), T stage (OR: 21.1; 95% CI: 1.6–272.1), and LR. Multiparametric MRI and 18F-CH PET/CT yield similar detection rates for LR, LNR and pelvic BM. The combination of both imaging techniques provides a better LR detection versus choline PET/CT alone. The initially planned salvage treatment was modified in 57.8% of patients due to imaging findings. In addition to PSA values, Gleason score, T stage, and PSADT may provide valuable data to identify those patients that are most likely to benefit from undergoing both imaging procedures.

Prediction Nomogram for 68Ga-PSMA-11 PET/CT in different clinical settings of PSA failure after radical treatment for Prostate Cancer

Objective The objective of this study was to develop a clinical nomogram to predict gallium-68 prostate-specific membrane antigen positron emission tomography/computed tomography (68Ga-PSMA-11-PET/CT) positivity in different clinical settings of PSA failure. Materials and methods Seven hundred three (n = 703) prostate cancer (PCa) patients with confirmed PSA failure after radical therapy were enrolled. Patients were stratified according to different clinical settings (first-time biochemical recurrence [BCR]: group 1; BCR after salvage therapy: group 2; biochemical persistence after radical prostatectomy [BCP]: group 3; advanced stage PCa before second-line systemic therapies: group 4). First, we assessed 68Ga-PSMA-11-PET/CT positivity rate. Second, multivariable logistic regression analyses were used to determine predictors of positive scan. Third, regression-based coefficients were used to develop a nomogram predicting positive 68Ga-PSMA-11-PET/CT result and 200 bootstrap resamples were used for internal validation. Fourth, receiver operating characteristic (ROC) analysis was used to identify the most informative nomogram’s derived cut-off. Decision curve analysis (DCA) was implemented to quantify nomogram’s clinical benefit. Results 68Ga-PSMA-11-PET/CT overall positivity rate was 51.2%, while it was 40.3% in group 1, 54% in group 2, 60.5% in group 3, and 86.9% in group 4 (p < 0.001). At multivariable analyses, ISUP grade, PSA, PSA doubling time, and clinical setting were independent predictors of a positive scan (all p ≤ 0.04). A nomogram based on covariates included in the multivariate model demonstrated a bootstrap-corrected accuracy of 82%. The nomogram-derived best cut-off value was 40%. In DCA, the nomogram revealed clinical net benefit of > 10%. Conclusions This novel nomogram proved its good accuracy in predicting a positive scan, with values ≥ 40% providing the most informative cut-off in counselling patients to 68Ga-PSMA-11-PET/CT. This tool might be important as a guide to clinicians in the best use of PSMA-based PET imaging.

New methodologies in CT perfusion and MRI analysis to develop cancer imaging biomarkers

Quantitative imaging in oncology aims at developing imaging biomarkers for diagnosis and prediction of cancer aggressiveness and therapy response before any morphological change become visible. This Thesis exploits Computed Tomography perfusion (CTp) and multiparametric Magnetic Resonance Imaging (mpMRI) for investigating diverse cancer features on different organs. I developed a voxel-based image analysis methodology in CTp and extended its use to mpMRI, for performing precise and accurate analyses at single-voxel level. This is expected to improve reproducibility of measurements and cancer mechanisms’ comprehension and clinical interpretability. CTp has not entered the clinical routine yet, although its usefulness in the monitoring of cancer angiogenesis, due to different perfusion computing methods yielding unreproducible results. Instead, machine learning applications in mpMRI, useful to detect imaging features representative of cancer heterogeneity, are mostly limited to clinical research, because of results’ variability and difficult interpretability, which make clinicians not confident in clinical applications. In hepatic CTp, I investigated whether, and under what conditions, two widely adopted perfusion methods, Maximum Slope (MS) and Deconvolution (DV), could yield reproducible parameters. To this end, I developed signal processing methods to model the first pass kinetics and remove any numerical cause hampering the reproducibility. In mpMRI, I proposed a new approach to extract local first-order features, aiming at preserving spatial reference and making their interpretation easier. In CTp, I found out the cause of MS and DV non-reproducibility: MS and DV represent two different states of the system. Transport delays invalidate MS assumptions and, by correcting MS formulation, I have obtained the voxel-based equivalence of the two methods. In mpMRI, the developed predictive models allowed (i) detecting rectal cancers responding to neoadjuvant chemoradiation showing, at pre-therapy, sparse coarse subregions with altered density, and (ii) predicting clinically significant prostate cancers stemming from the disproportion between high- and low- diffusivity gland components.

Automatic detection of the inferior alveolar nerve in CT scans with CenterNet

The inferior alveolar nerve (IAN) lies within the mandibular canal, named inferior alveolar canal in literature. The detection of this nerve is important during maxillofacial surgeries or for creating dental implants. The poor quality of cone-beam computed tomography (CBCT) and computed tomography (CT) scans and/or bone gaps within the mandible increase the difficulty of this task, posing a challenge to human experts who are going to manually detect it and resulting in a time-consuming task.Therefore this thesis investigates two methods to automatically detect the IAN: a non-data driven technique and a deep-learning method. The latter tracks the IAN position at each frame leveraging detections obtained with the deep neural network CenterNet, fined-tuned for our task, and temporal and spatial information.

Longitudinal Micro CT-driven biomarkers as a tool to evaluate lung fibrosis progression and antifibrotic efficacy in a refined Bleomycin mouse model

Idiopathic pulmonary fibrosis (IPF) is a chronic progressive disease with no curative pharmacological treatment. Animal models play an essential role in revealing molecular mechanisms involved in the pathogenesis of the disease. Bleomycin (BLM)-induced lung fibrosis is the most widely used and characterized model for anti-fibrotic drugs screening. However, several issues have been reported, such as the identification of an optimal BLM dose and administration scheme as well as gender-specificity. Moreover, the balance between disease resolution, an appropriate time window for therapeutic intervention and animal welfare remains critical aspects yet to be fully elucidated. In this thesis, Micro CT imaging has been used as a tool to identify the ideal BLM dose regimen to induce sustained lung fibrosis in mice as well as to assess the anti-fibrotic effect of Nintedanib (NINT) treatment upon this BLM administration regimen. In order to select the optimal BLM dose scheme, C57bl/6 male mice were treated with BLM via oropharyngeal aspiration (OA), following either double or triple BLM administration. The triple BLM administration resulted in the most promising scheme, able to balance disease resolution, appropriate time-window for therapeutic intervention and animal welfare. The fibrosis progression was longitudinally assessed by micro-CT every 7 days for 5 weeks after BLM administration and 5 animals were sacrificed at each timepoint for the BALF and histological evaluation. The antifibrotic effect of NINT was assessed following different treatment regimens in this model. Herein, we have developed an optimized mouse model of pulmonary fibrosis, enabling three weeks of the therapeutic window to screen putative anti-fibrotic drugs. micro-CT scanning, allowed us to monitor the progression of lung fibrosis and the therapeutical response longitudinally in the same subject, drastically reducing the number of animals involved in the experiment.

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.

Assessing model credibility of CT-Based finite element model to predict bone strength

Osteoporosis is one of the major causes of mortality among the elderly. Nowadays, areal bone mineral density (aBMD) is used as diagnostic criteria for osteoporosis; however, this is a moderate predictor of the femur fracture risk and does not capture the effect of some anatomical and physiological properties on the bone strength estimation. Data from past research suggest that most fragility femur fractures occur in patients with aBMD values outside the pathological range. Subject-specific finite element models derived from computed tomography data are considered better tools to non-invasively assess hip fracture risk. In particular, the Bologna Biomechanical Computed Tomography (BBCT) is an In Silico methodology that uses a subject specific FE model to predict bone strength. Different studies demonstrated that the modeling pipeline can increase predictive accuracy of osteoporosis detection and assess the efficacy of new antiresorptive drugs. However, one critical aspect that must be properly addressed before using the technology in the clinical practice, is the assessment of the model credibility. The aim of this study was to define and perform verification and uncertainty quantification analyses on the BBCT methodology following the risk-based credibility assessment framework recently proposed in the VV-40 standard. The analyses focused on the main verification tests used in computational solid mechanics: force and moment equilibrium check, mesh convergence analyses, mesh quality metrics study, evaluation of the uncertainties associated to the definition of the boundary conditions and material properties mapping. Results of these analyses showed that the FE model is correctly implemented and solved. The operation that mostly affect the model results is the material properties mapping step. This work represents an important step that, together with the ongoing clinical validation activities, will contribute to demonstrate the credibility of the BBCT methodology.

Dosimetric optimization of CT protocols for the preoperative planning of hip arthroplasty

Radiation dose in x-ray computed tomography (CT) has become a topic of great interest due to the increasing number of CT examinations performed worldwide. In fact, CT scans are responsible of significant doses delivered to the patients, much larger than the doses due to the most common radiographic procedures. This thesis work, carried out at the Laboratory of Medical Technology (LTM) of the Rizzoli Orthopaedic Institute (IOR, Bologna), focuses on two primary objectives: the dosimetric characterization of the tomograph present at the IOR and the optimization of the clinical protocol for hip arthroplasty. In particular, after having verified the reliability of the dose estimates provided by the system, we compared the estimates of the doses delivered to 10 patients undergoing CT examination for the pre-operative planning of hip replacement with the Diagnostic Reference Level (DRL) for an osseous pelvis examination. Out of 10 patients considered, only for 3 of them the doses were lower than the DRL. Therefore, the necessity to optimize the clinical protocol emerged. This optimization was investigated using a human femur from a cadaver. Quantitative analysis and comparison of 3D reconstructions were made, after having performed manual segmentation of the femur from different CT acquisitions. Dosimetric simulations of the CT acquisitions on the femur were also made and associated to the accuracy of the 3D reconstructions, to analyse the optimal combination of CT acquisition parameters. The study showed that protocol optimization both in terms of Hausdorff distance and in terms of effective dose (ED) to the patient may be realized simply by modifying the value of the pitch in the protocol, by choosing between 0.98 and 1.37.

Graphene And Carbon Nanotube Nanocomposite For Gene Transfection.

Graphene and carbon nanotube nanocomposite (GCN) was synthesised and applied in gene transfection of pIRES plasmid conjugated with green fluorescent protein (GFP) in NIH-3T3 and NG97 cell lines. The tips of the multi-walled carbon nanotubes (MWCNTs) were exfoliated by oxygen plasma etching, which is also known to attach oxygen content groups on the MWCNT surfaces, changing their hydrophobicity. The nanocomposite was characterised by high resolution scanning electron microscopy; energy-dispersive X-ray, Fourier transform infrared and Raman spectroscopies, as well as zeta potential and particle size analyses using dynamic light scattering. BET adsorption isotherms showed the GCN to have an effective surface area of 38.5m(2)/g. The GCN and pIRES plasmid conjugated with the GFP gene, forming π-stacking when dispersed in water by magnetic stirring, resulting in a helical wrap. The measured zeta potential confirmed that the plasmid was connected to the nanocomposite. The NIH-3T3 and NG97 cell lines could phagocytize this wrap. The gene transfection was characterised by fluorescent protein produced in the cells and pictured by fluorescent microscopy. Before application, we studied GCN cell viability in NIH-3T3 and NG97 line cells using both MTT and Neutral Red uptake assays. Our results suggest that GCN has moderate stability behaviour as colloid solution and has great potential as a gene carrier agent in non-viral based therapy, with low cytotoxicity and good transfection efficiency.

Extensive Frontoparietal Abscess: Complication Of Frontal Sinusitis (pott's Puffy Tumor).

First described in 1768, the Pott's puffy tumor is a subperiosteal abscess associated with frontal bone osteomyelitis, resulting from trauma or frontal sinusitis. The classic clinical presentation consists of purulent rhinorrhea, fever, headache, and frontal swelling. The diagnosis is confirmed by CT scan and treatment requires intravenous antibiotics, analgesia, and surgical intervention. Early diagnosis and aggressive medical and surgical approach are essential for a good outcome. It rare and the early diagnosis is important; we describe the case of a 14-year-old adolescent with Pott's puffy tumor who was initially treated inadequately, evolving with extensive frontoparietal abscess. The patient underwent surgical treatment with endoscopic endonasal and external approaches combined. Intravenous antibiotics were prescribed for a prolonged time, with good outcome and remission of the complaints.

Magnesium-deficient High-fat Diet: Effects On Adiposity, Lipid Profile And Insulin Sensitivity In Growing Rats.

To determine if magnesium deficiency aggravates the effects of a high-fat diet in growing rats in terms of obesity, lipid profile and insulin resistance. The study population comprised 48 newly weaned male Wistar Hannover rats distributed into four groups according to diet, namely, control group (CT; n = 8), control diet provided ad libitum; pair-feeding control group (PF; n = 16), control diet but in the same controlled amount as animals that received high-fat diets; high-fat diet group (HF; n = 12), and magnesium-deficient high-fat diet group (HFMg(-); n = 12). The parameters investigated were adiposity index, lipid profile, magnesium status, insulin sensitivity and the phosphorylation of proteins involved in the insulin-signaling pathway, i.e. insulin receptor β-subunit, insulin receptor substrate 1 and protein kinase B. The HF and HFMg(-) groups were similar regarding gain in body mass, adiposity index and lipid profile, but were significantly different from the PF group. The HFMg(-) group exhibited alterations in magnesium homeostasis as revealed by the reduction in urinary and bone concentrations of the mineral. No inter-group differences were observed regarding glucose homeostasis. Protein phosphorylation in the insulin-signaling pathway was significantly reduced in the high-fat groups compared with the control groups, demonstrating that the intake of fat-rich diets increased insulin resistance, a syndrome that was aggravated by magnesium deficiency. Under the experimental conditions tested, the intake of a magnesium-deficient high-fat diet led to alterations in the insulin-signaling pathway and, consequently, increased insulin resistance.

[adherence To Statin Treatment And Associated Factors In Female Users From The Unified Health System (sus)].

To identify the adherence rate of a statin treatment and possible related factors in female users from the Unified Health System. Seventy-one women were evaluated (64.2 ± 11.0 years) regarding the socio-economic level, comorbidities, current medications, level of physical activity, self-report of muscular pain, adherence to the medical prescription, body composition and biochemical profile. The data were analyzed as frequencies, Chi-Squared test, and Mann Whitney test (p<0.05). 15.5% of women did not adhere to the medical prescription for the statin treatment, whose had less comorbidities (p=0.01), consumed less quantities of medications (p=0.00), and tended to be younger (p=0.06). Those patients also presented higher values of lipid profile (CT: p=0.01; LDL-c: p=0.02). Musculoskeletal complains were not associated to the adherence rate to the medication. The associated factors to adherence of dyslipidemic women to statin medical prescription were age, quantity of comorbidities and quantity of current medication.

Development And Characterization Of 32 Microsatellite Loci In Genipa Americana (rubiaceae).

• Microsatellite primers were developed for the tree species Genipa americana (Rubiaceae) for further population genetic studies. • We identified 144 clones containing 65 repeat motifs from a genomic library enriched for (CT)8 and (GT)8 motifs. Primer pairs were developed for 32 microsatellite loci and validated in 40 individuals of two natural G. americana populations. Seventeen loci were polymorphic, revealing from three to seven alleles per locus. The observed and expected heterozygosities ranged from 0.24 to 1.00 and from 0.22 to 0.78, respectively. • The 17 primers identified as polymorphic loci are suitable to study the genetic diversity and structure, mating system, and gene flow in G. americana.