[Vier-Tages-Schlacht 1666] : [mit Porträtmedaillons von] Michiel Adriaensz De Ruyter L. Admiral von Holland, Ct. ; Ad. C . Tromp

Aus: [Relationis historicae semestralis continuatio ; 1666, Herbst]

Fragm. lat. I 20 - In Cantica canticorum explicatio mystica (Ct 4,9 - 5,6)

Trägerband: Ms. Barth. 42; Vorbesitzer: Bartholomaeusstift Frankfurt am Main

Vue de'l Hermitage à côté de l'entrée

Signatur des Originals: S 36/G02679

Vue de'l Hermitage à côté de l'entrée

Signatur des Originals: S 36/G02680

Vue de'l Hermitage du côté du jardin

Signatur des Originals: S 36/G02681

Assessment of cone beam computed tomography techniques for imaging lung damage in mice in vivo

Lung damage is a common side effect of chemotherapeutic drugs such as bleomycin. This study used a bleomycin mouse model which simulates the lung damage observed in humans. Noninvasive, in vivo cone-beam computed tomography (CBCT) was used to visualize and quantify fibrotic and inflammatory damage over the entire lung volume of mice. Bleomycin was used to induce pulmonary damage in vivo and the results from two CBCT systems, a micro-CT and flat panel CT (fpCT), were compared to histologic measurements, the standard method of murine lung damage quantification. Twenty C57BL/6 mice were given either 3 U/kg of bleomycin or saline intratracheally. The mice were scanned at baseline, before the administration of bleomycin, and then 10, 14, and 21 days afterward. At each time point, a subset of mice was sacrificed for histologic analysis. The resulting CT images were used to assess lung volume. Percent lung damage (PLD) was calculated for each mouse on both the fpCT (PLDfpcT) and the micro-CT (PLDμCT). Histologic PLD (PLDH) was calculated for each histologic section at each time point (day 10, n = 4; day 14, n = 4; day 21, n = 5; control group, n = 5). A linear regression was applied to the PLDfpCT vs. PLDH, PLDμCT vs. PLDH and PLDfpCT vs. PLDμCT distributions. This study did not demonstrate strong correlations between PLDCT and PLDH. The coefficient of determination, R, was 0.68 for PLDμCT vs. PLDH and 0.75 for the PLD fpCT vs. PLDH. The experimental issues identified from this study were: (1) inconsistent inflation of the lungs from scan to scan, (2) variable distribution of damage (one histologic section not representative of overall lung damage), (3) control mice not scanned with each group of bleomycin mice, (4) two CT systems caused long anesthesia time for the mice, and (5) respiratory gating did not hold the volume of lung constant throughout the scan. Addressing these issues might allow for further improvement of the correlation between PLDCT and PLDH. ^

Role of stress myocardial perfusion scan in pre-operative evaluation of cancer patients undergoing non-cardiac surgery

Background. Cardiac risk assessment in cancer patients has not extensively been studied. We evaluated the role of stress myocardial perfusion imaging (MPI) in predicting cardiovascular outcomes in cancer patients undergoing non-cardiac surgery. ^ Methods. A retrospective chart review was performed on 507 patients who had a MPI from 01/2002 - 03/2003 and underwent non-cardiac surgery. Median follow-up duration was 1.5 years. Cox proportional hazard model was used to determine the time-to-first event. End points included total cardiac events (cardiac death, myocardial infarction (MI) and coronary revascularization), cardiac death, and all cause mortality. ^ Results. Of all 507 MPI studies 146 (29%) were abnormal. There were significant differences in risk factors between normal and abnormal MPI groups. Mean age was 66±11 years, with 60% males and a median follow-up duration of 1.8 years (25th quartile=0.8 years, 75th quartile=2.2 years). The majority of patients had an adenosine stress study (53%), with fewer exercise (28%) and dobutamine stress (16%) studies. In the total group there were 39 total cardiac events, 31 cardiac deaths, and 223 all cause mortality events during the study. Univariate predictors of total cardiac events included CAD (p=0.005), previous MI (p=0.005), use of beta blockers (p=0.002), and not receiving chemotherapy (p=0.012). Similarly, the univariate predictors of cardiac death included previous MI (p=0.019) and use of beta blockers (p=0.003). In the multivariate model for total cardiac events, age at surgery (HR 1.04, p=0.030), use of beta blockers (HR 2.46; p=0.011), dobutamine MPI (HR 3.08; p=0.018) and low EF (HR 0.97; p=0.02) were significant predictors of worse outcomes. In the multivariate model for predictors of cardiac death, beta blocker use (HR=2.74; p=0.017) and low EF (HR=0.95; p<0.003) were predictors of cardiac death. The only univariate MPI predictor of total cardiac events was scar severity (p=0.005). While MPI predictors of cardiac death were scar severity (p= 0.001) and ischemia severity (p=0.02). ^ Conclusions. Stress MPI is a useful tool in predicting long term outcomes in cancer patients undergoing surgery. Ejection fraction and severity of myocardial scar are important factors determining long term outcomes in this group.^

Trends in utilization of computer tomography (CT) scans for victims of motor vehicle collision (MVCs) in a level I trauma center from 1996 to 2006

Purpose. To evaluate trends in the utilization of head, abdominal, thoracic and other body regions CTs in the management of victims of MVC at a level I trauma center from 1996 to 2006.^ Method. From the trauma registry, I identified patients involved in MVC's in a level I trauma center and categorized them into three age groups of 13-18, 19-55 and ≥56. I used International Classification of Disease (ICD-9-CM) codes to find the type and number of CTs examinations performed for each patient. I plotted the mean number of CTs per patient against year of admission to find the crude estimate of change in utilization pattern for each type of CT. I used logistic regression to assess whether repetitive CTs (≥ 2) for head, abdomen, thorax and other body regions were associated with age group and year of admission for MVC patients. I adjusted the estimates for gender, ethnicity, insurance status, mechanism and severity of injury, intensive care unit admission status, patient disposition (dead or alive) and year of admission.^ Results. Utilization of head, abdominal, thoracic and other body regions CTs significantly increased over 11-year period. Utilization of head CT was greatest in the 13-18 age group, and increased from 0.58 CT/patient in 1996 to 1.37 CT/patient in 2006. Abdominal CTs were more common in the ≥56+ age group, and increased from 0.33 CT/patient in 1996 to 0.72 CT/patient in 2006. Utilization of thoracic CTs was higher in the 56+ age group, and increased from 0.01 CT/patient in 1996 to 0.42 CT/patient in 2006. Utilization of other CTs did not change materially during the study period for adolescents, adults or older adults. In the multivariable analysis, after adjustment for potential confounders, repetitive head CTs significantly increased in the 13-18 age group (95% CI: 1.29-1.87, p=<0.001) relative to the 19-55 age group. Repetitive thoracic CT use was lower in adolescents (95% CI: 0.22-0.70, p=<0.001) relative to the 19-55 age group.^ Conclusion. There has been a substantial increase in the utilization of head, abdominal, thoracic and other CTs in the management of MVC patients. Future studies need to identify if increased utilization of CTs have resulted in better health outcome for these patients. ^

Understanding the Influence of Photon Energy on 6MV Non Reference Dosimetry and CT Dosimetry using TLD and OSLD

Measurement of the absorbed dose from ionizing radiation in medical applications is an essential component to providing safe and reproducible patient care. There are a wide variety of tools available for measuring radiation dose; this work focuses on the characterization of two common, solid-state dosimeters in medical applications: thermoluminescent dosimeters (TLD) and optically stimulated luminescent dosimeters (OSLD). There were two main objectives to this work. The first objective was to evaluate the energy dependence of TLD and OSLD for non-reference measurement conditions in a radiotherapy environment. The second objective was to fully characterize the OSLD nanoDot in a CT environment, and to provide validated calibration procedures for CT dose measurement using OSLD. Current protocols for dose measurement using TLD and OSLD generally assume a constant photon energy spectrum within a nominal beam energy regardless of measurement location, tissue composition, or changes in beam parameters. Variations in the energy spectrum of therapeutic photon beams may impact the response of TLD and OSLD and could thereby result in an incorrect measure of dose unless these differences are accounted for. In this work, we used a Monte Carlo based model to simulate variations in the photon energy spectra of a Varian 6MV beam; then evaluated the impact of the perturbations in energy spectra on the response of both TLD and OSLD using Burlin Cavity Theory. Energy response correction factors were determined for a range of conditions and compared to measured correction factors with good agreement. When using OSLD for dose measurement in a diagnostic imaging environment, photon energy spectra are often referenced to a therapy-energy or orthovoltage photon beam – commonly 250kVp, Co-60, or even 6MV, where the spectra are substantially different. Appropriate calibration techniques specifically for the OSLD nanoDot in a CT environment have not been presented in the literature; furthermore the dependence of the energy response of the calibration energy has not been emphasized. The results of this work include detailed calibration procedures for CT dosimetry using OSLD, and a full characterization of this dosimetry system in a low-dose, low-energy setting.

Design and Optimization of Four-dimensional Cone-beam Computed Tomography in Image-guided Radiation Therapy

The influence of respiratory motion on patient anatomy poses a challenge to accurate radiation therapy, especially in lung cancer treatment. Modern radiation therapy planning uses models of tumor respiratory motion to account for target motion in targeting. The tumor motion model can be verified on a per-treatment session basis with four-dimensional cone-beam computed tomography (4D-CBCT), which acquires an image set of the dynamic target throughout the respiratory cycle during the therapy session. 4D-CBCT is undersampled if the scan time is too short. However, short scan time is desirable in clinical practice to reduce patient setup time. This dissertation presents the design and optimization of 4D-CBCT to reduce the impact of undersampling artifacts with short scan times. This work measures the impact of undersampling artifacts on the accuracy of target motion measurement under different sampling conditions and for various object sizes and motions. The results provide a minimum scan time such that the target tracking error is less than a specified tolerance. This work also presents new image reconstruction algorithms for reducing undersampling artifacts in undersampled datasets by taking advantage of the assumption that the relevant motion of interest is contained within a volume-of-interest (VOI). It is shown that the VOI-based reconstruction provides more accurate image intensity than standard reconstruction. The VOI-based reconstruction produced 43% fewer least-squares error inside the VOI and 84% fewer error throughout the image in a study designed to simulate target motion. The VOI-based reconstruction approach can reduce acquisition time and improve image quality in 4D-CBCT.

Radiomics of NSCLC: Quantitative CT Image Feature Characterization and Tumor Shrinkage Prediction

Radiomics is the high-throughput extraction and analysis of quantitative image features. For non-small cell lung cancer (NSCLC) patients, radiomics can be applied to standard of care computed tomography (CT) images to improve tumor diagnosis, staging, and response assessment. The first objective of this work was to show that CT image features extracted from pre-treatment NSCLC tumors could be used to predict tumor shrinkage in response to therapy. This is important since tumor shrinkage is an important cancer treatment endpoint that is correlated with probability of disease progression and overall survival. Accurate prediction of tumor shrinkage could also lead to individually customized treatment plans. To accomplish this objective, 64 stage NSCLC patients with similar treatments were all imaged using the same CT scanner and protocol. Quantitative image features were extracted and principal component regression with simulated annealing subset selection was used to predict shrinkage. Cross validation and permutation tests were used to validate the results. The optimal model gave a strong correlation between the observed and predicted shrinkages with . The second objective of this work was to identify sets of NSCLC CT image features that are reproducible, non-redundant, and informative across multiple machines. Feature sets with these qualities are needed for NSCLC radiomics models to be robust to machine variation and spurious correlation. To accomplish this objective, test-retest CT image pairs were obtained from 56 NSCLC patients imaged on three CT machines from two institutions. For each machine, quantitative image features with concordance correlation coefficient values greater than 0.90 were considered reproducible. Multi-machine reproducible feature sets were created by taking the intersection of individual machine reproducible feature sets. Redundant features were removed through hierarchical clustering. The findings showed that image feature reproducibility and redundancy depended on both the CT machine and the CT image type (average cine 4D-CT imaging vs. end-exhale cine 4D-CT imaging vs. helical inspiratory breath-hold 3D CT). For each image type, a set of cross-machine reproducible, non-redundant, and informative image features was identified. Compared to end-exhale 4D-CT and breath-hold 3D-CT, average 4D-CT derived image features showed superior multi-machine reproducibility and are the best candidates for clinical correlation.