CT attenuation values of blood and myocardium: rationale for accurate coronary artery calcifications detection with multi-detector CT.

OBJECTIVES: To determine inter-session and intra/inter-individual variations of the attenuations of aortic blood/myocardium with MDCT in the context of calcium scoring. To evaluate whether these variations are dependent on patients' characteristics. METHODS: Fifty-four volunteers were evaluated with calcium scoring non-enhanced CT. We measured attenuations (inter-individual variation) and standard deviations (SD, intra-individual variation) of the blood in the ascending aorta and of the myocardium of left ventricle. Every volunteer was examined twice to study the inter-session variation. The fat pad thickness at the sternum and noise (SD of air) were measured too. These values were correlated with the measured aortic/ventricular attenuations and their SDs (Pearson). Historically fixed thresholds (90 and 130 HU) were tested against different models based on attenuations of blood/ventricle. RESULTS: The mean attenuation was 46 HU (range, 17-84 HU) with mean SD 23 HU for the blood, and 39 HU (10-82 HU) with mean SD 18 HU for the myocardium. The attenuation/SD of the blood were significantly higher than those of the myocardium (p < 0.01). The inter-session variation was not significant. There was a poor correlation between SD of aortic blood/ventricle with fat thickness/noise. Based on existing models, 90 HU threshold offers a confidence interval of approximately 95% and 130 HU more than 99%. CONCLUSIONS: Historical thresholds offer high confidence intervals for exclusion of aortic blood/myocardium and by the way for detecting calcifications. Nevertheless, considering the large variations of blood/myocardium CT values and the influence of patient's characteristics, a better approach might be an adaptive threshold.

Anatomic study of the feline bronchial and vascular structures with a 64 detector-row computed tomography

Multidetector row computed tomography over the last decade is commonly used in veterinary medicine. This new technology has an increased spatial and temporal resolution, could evaluate wider scanning range in shorter scanning time, providing an advanced imaging modality. Computed tomography angiographic studies are commonly used in veterinary medicine in order to evaluate vascular structures of the abdomen and the thorax. Pulmonary pathology in feline patients is a very common condition and usually is further evaluating with computed tomography. Up to date few references of the normal computed tomographic aspects of the feline thorax are reported. In this study a computed tomographic pulmonary angiography (CTPA) protocol is reported in normal cats and is compared with the up to date anatomical references. A CTPA protocol using a 64 MDCT in our study achieved high resolution images of the pulmonary arteries, pulmonary veins and bronchial lumen till the level of minor segmental branches. Feline pulmonary bronchial parenchyma demonstrates an architecture of mixed type with a monopedial model observed in the most anatomical parts and the dichotomic aspect is seen at the accessory lobe. The arterial and venous architecture is similar to the bronchial. Statistical analysis demonstrates the linear correlation of tracheal diameter to the felines weight. Vascular variations were noticed. The pulmonary venous system enters into the left atrium through three ostia (left cranial ostia: consisted of the anastomosis of the cranial and caudal portion of the left cranial pulmonary vein; right ostia: consisted of the anastomosis of the right cranial and middle pulmonary vein; and the caudal ostia: consisted of the anastomosis of the right and left caudal pulmonary vein). In conclusion CTPA is applicable in feline patients and provides an excellent imaging of the pulmonary arterial, venous and bronchial system till the level of minor segmental branches.

Multi-detector row CT of the small bowel: peak enhancement temporal window--initial experience

PURPOSE: To prospectively determine quantitatively and qualitatively the timing of maximal enhancement of the normal small-bowel wall by using contrast material-enhanced multi-detector row computed tomography (CT). MATERIALS AND METHODS: This HIPAA-compliant study was approved by the institutional review board. After information on radiation risk was given, written informed consent was obtained from 25 participants with no history of small-bowel disease (mean age, 58 years; 19 men) who had undergone single-level dynamic CT. Thirty seconds after the intravenous administration of contrast material, a serial dynamic acquisition, consisting of 10 images obtained 5 seconds apart, was performed. Enhancement measurements were obtained over time from the small-bowel wall and the aorta. Three independent readers qualitatively assessed small-bowel conspicuity. Quantitative and qualitative data were analyzed during the arterial phase, the enteric phase (which represented peak small-bowel mural enhancement), and the venous phase. Statistical analysis included paired Student t test and Wilcoxon signed rank test with Bonferroni correction. A P value less than .05 was used to indicate a significant difference. RESULTS: The mean time to peak enhancement of the small-bowel wall was 49.3 seconds +/- 7.7 (standard deviation) and 13.5 seconds +/- 7.6 after peak aortic enhancement. Enhancement values were highest during the enteric phase (P < .05). Regarding small-bowel conspicuity, images obtained during the enteric phase were most preferred qualitatively; there was a significant difference between the enteric and arterial phases (P < .001) but not between the enteric and venous phases (P = .18). CONCLUSION: At multi-detector row CT, peak mural enhancement of the normal small bowel occurs on average about 50 seconds after intravenous administration of contrast material or 14 seconds after peak aortic enhancement.

Thoracolumbar spine fractures in patients who have sustained severe trauma: depiction with multi-detector row CT

PURPOSE: To determine if multi–detector row computed tomography (CT) can replace conventional radiography and be performed alone in severe trauma patients for the depiction of thoracolumbar spine fractures. MATERIALS AND METHODS: One hundred consecutive severe trauma patients who underwent conventional radiography of the thoracolumbar spine as well as thoracoabdominal multi–detector row CT were prospectively identified. Conventional radiographs were reviewed independently by three radiologists and two orthopedic surgeons; CT images were reviewed by three radiologists. Reviewers were blinded both to one another’s reviews and to the results of initial evaluation. Presence, location, and stability of fractures, as well as quality of reviewed images, were assessed. Statistical analysis was performed to determine sensitivity and interobserver agreement for each procedure, with results of clinical and radiologic follow-up as the standard of reference. The time to perform each examination and the radiation dose involved were evaluated. A resource cost analysis was performed. RESULTS: Sixty-seven fractured vertebrae were diagnosed in 26 patients. Twelve patients had unstable spine fractures. Mean sensitivity and interobserver agreement, respectively, for detection of unstable fractures were 97.2% and 0.951 for multi–detector row CT and 33.3% and 0.368 for conventional radiography. The median times to perform a conventional radiographic and a multi–detector row CT examination, respectively, were 33 and 40 minutes. Effective radiation doses at conventional radiography of the spine and thoracoabdominal multi–detector row CT, respectively, were 6.36 mSv and 19.42 mSv. Multi–detector row CT enabled identification of 146 associated traumatic lesions. The costs of conventional radiography and multi–detector row CT, respectively, were $145 and $880 per patient. CONCLUSION: Multi–detector row CT is a better examination for depicting spine fractures than conventional radiography. It can replace conventional radiography and be performed alone in patients who have sustained severe trauma.

Feasible Dose Reduction in Routine Chest Computed Tomography Maintaining Constant Image Quality Using the Last Three Scanner Generations: From Filtered Back Projection to Sinogram-affirmed Iterative Reconstruction and Impact of the Novel Fully Integrated Detector Design Minimizing Electronic Noise

OBJECTIVE The aim of the present study was to evaluate a dose reduction in contrast-enhanced chest computed tomography (CT) by comparing the three latest generations of Siemens CT scanners used in clinical practice. We analyzed the amount of radiation used with filtered back projection (FBP) and an iterative reconstruction (IR) algorithm to yield the same image quality. Furthermore, the influence on the radiation dose of the most recent integrated circuit detector (ICD; Stellar detector, Siemens Healthcare, Erlangen, Germany) was investigated. MATERIALS AND METHODS 136 Patients were included. Scan parameters were set to a thorax routine: SOMATOM Sensation 64 (FBP), SOMATOM Definition Flash (IR), and SOMATOM Definition Edge (ICD and IR). Tube current was set constantly to the reference level of 100 mA automated tube current modulation using reference milliamperes. Care kV was used on the Flash and Edge scanner, while tube potential was individually selected between 100 and 140 kVp by the medical technologists at the SOMATOM Sensation. Quality assessment was performed on soft-tissue kernel reconstruction. Dose was represented by the dose length product. RESULTS Dose-length product (DLP) with FBP for the average chest CT was 308 mGy*cm ± 99.6. In contrast, the DLP for the chest CT with IR algorithm was 196.8 mGy*cm ± 68.8 (P = 0.0001). Further decline in dose can be noted with IR and the ICD: DLP: 166.4 mGy*cm ± 54.5 (P = 0.033). The dose reduction compared to FBP was 36.1% with IR and 45.6% with IR/ICD. Signal-to-noise ratio (SNR) was favorable in the aorta, bone, and soft tissue for IR/ICD in combination compared to FBP (the P values ranged from 0.003 to 0.048). Overall contrast-to-noise ratio (CNR) improved with declining DLP. CONCLUSION The most recent technical developments, namely IR in combination with integrated circuit detectors, can significantly lower radiation dose in chest CT examinations.

Dipyridamole stress myocardial perfusion by computed tomography in patients with left bundle branch block

Abstract Background: Functional tests have limited accuracy for identifying myocardial ischemia in patients with left bundle branch block (LBBB). Objective: To assess the diagnostic accuracy of dipyridamole-stress myocardial computed tomography perfusion (CTP) by 320-detector CT in patients with LBBB using invasive quantitative coronary angiography (QCA) (stenosis ≥ 70%) as reference; to investigate the advantage of adding CTP to coronary computed tomography angiography (CTA) and compare the results with those of single photon emission computed tomography (SPECT) myocardial perfusion scintigraphy. Methods: Thirty patients with LBBB who had undergone SPECT for the investigation of coronary artery disease were referred for stress tomography. Independent examiners performed per-patient and per-coronary territory assessments. All patients gave written informed consent to participate in the study that was approved by the institution’s ethics committee. Results: The patients’ mean age was 62 ± 10 years. The mean dose of radiation for the tomography protocol was 9.3 ± 4.6 mSv. With regard to CTP, the per-patient values for sensitivity, specificity, positive and negative predictive values, and accuracy were 86%, 81%, 80%, 87%, and 83%, respectively (p = 0.001). The per-territory values were 63%, 86%, 65%, 84%, and 79%, respectively (p < 0.001). In both analyses, the addition of CTP to CTA achieved higher diagnostic accuracy for detecting myocardial ischemia than SPECT (p < 0.001). Conclusion: The use of the stress tomography protocol is feasible and has good diagnostic accuracy for assessing myocardial ischemia in patients with LBBB.

Model-based Segmentation and Fusion of 3D Computed Tomography and 3D Ultrasound of the Eye for Radiotherapy Planning

Computed Tomography (CT) represents the standard imaging modality for tumor volume delineation for radiotherapy treatment planning of retinoblastoma despite some inherent limitations. CT scan is very useful in providing information on physical density for dose calculation and morphological volumetric information but presents a low sensitivity in assessing the tumor viability. On the other hand, 3D ultrasound (US) allows a highly accurate definition of the tumor volume thanks to its high spatial resolution but it is not currently integrated in the treatment planning but used only for diagnosis and follow-up. Our ultimate goal is an automatic segmentation of gross tumor volume (GTV) in the 3D US, the segmentation of the organs at risk (OAR) in the CT and the registration of both modalities. In this paper, we present some preliminary results in this direction. We present 3D active contour-based segmentation of the eye ball and the lens in CT images; the presented approach incorporates the prior knowledge of the anatomy by using a 3D geometrical eye model. The automated segmentation results are validated by comparing with manual segmentations. Then, we present two approaches for the fusion of 3D CT and US images: (i) landmark-based transformation, and (ii) object-based transformation that makes use of eye ball contour information on CT and US images.

Distribution of artifactual gas on post-mortem multidetector computed tomography (MDCT)

L'imagerie est de plus en plus utilisée en médecine forensique. Actuellement, les connaissances nécessaires pour interpréter les images post mortem sont faibles et surtout celles concernant les artéfacts post mortem. Le moyen radiologique le plus utilisé en médecine légale est la tomodensitométrie multi-coupes (TDMC). Un de ses avantages est la détection de gaz dans le corps. Cette technique est utile au diagnostic d'embolie gazeuse mais sa très grande sensibilité rend visible du gaz présent même en petite quantité. Les premières expériences montrent que presque tous les corps scannés présentent du gaz surtout dans le système vasculaire. Pour cette raison, le médecin légiste est confronté à un nouveau problème : la distinction entre du gaz d'origine post-mortem et une embolie gazeuse vraie. Pour parvenir à cette distinction, il est essentiel d'étudier la distribution de ces gaz en post mortem. Aucune étude systématique n'a encore été réalisée à ce jour sur ce sujet.¦Nous avons étudié l'incidence et la distribution des gaz présents en post mortem dans les vaisseaux, dans les os, dans les tissus sous-cutanés, dans l'espace sous-dural ainsi que dans les cavités crânienne, thoracique et abdominale (82 sites au total) de manière à identifier les facteurs qui pourraient distinguer le gaz post-mortem artéfactuel d'une embolie gazeuse¦Les données TDMC de 119 cadavres ont été étudiées rétrospectivement. Les critères d'inclusion des sujets sont l'absence de lésion corporelle permettant la contamination avec l'air extérieur, et, la documentation du délai entre le moment du décès et celui du CT-scan (p.ex. rapport de police, protocole de réanimation ou témoin). La présence de gaz a été évaluée semi-quantitativement par deux radiologues et codifiée. La codification est la suivante : grade 0 = pas de gaz, grade 1 = une à quelques bulles d'air, grade 2 = structure partiellement remplie d'air, grade 3 = structure complètement remplie d'air.¦Soixante-quatre des 119 cadavres présentent du gaz (62,2%), et 56 (75,7%) ont montré du gaz dans le coeur. Du gaz a été détecté le plus fréquemment dans le parenchyme hépatique (40%); le coeur droit (ventricule 38%, atrium 35%), la veine cave inférieure (infra-rénale 30%, supra-rénale 26%), les veines sus-hépatiques (gauche 26%, moyenne 29%, droite 22 %), et les espaces du porte (29%). Nous avons constaté qu'une grande quantité de gaz liée à la putréfaction présente dans le coeur droit (grade 3) est associée à des collections de gaz dans le parenchyme hépatique (sensibilité = 100%, spécificité = 89,7%). Pour décrire nos résultats, nous avons construit une séquence d'animation qui illustre le processus de putréfaction et l'apparition des gaz à la TDMC post-mortem.¦Cette étude est la première à montrer que l'apparition post-mortem des gaz suit un modèle de distribution spécifique. L'association entre la présence de gaz intracardiaque et dans le parenchyme hépatique pourrait permettre de distinguer du gaz artéfactuel d'origine post-mortem d'une embolie gazeuse vraie. Cette étude fournit une clé pour le diagnostic de la mort due à une embolie gazeuse cardiaque sur la base d'une TDMC post-mortem.¦Abstract¦Purpose: We investigated the incidence and distribution of post-mortem gas detected with multidetector computed tomography (MDCT) to identify factors that could distinguish artifactual gas from cardiac air embolism.¦Material and Methods: MDCT data of 119 cadavers were retrospectively examined. Gas was semiquantitatively assessed in selected blood vessels, organs and body spaces (82 total sites).¦Results: Seventy-four of the 119 cadavers displayed gas (62.2%; CI 95% 52.8 to 70.9), and 56 (75.7%) displayed gas in the heart. Most gas was detected in the hepatic parenchyma (40%); right heart (38% ventricle, 35% atrium), inferior vena cava (30% infrarenally, 26% suprarenally), hepatic veins (26% left, 29% middle, 22% right), and portal spaces (29%). Male cadavers displayed gas more frequently than female cadavers. Gas was detected 5-84 h after death; therefore, the post-mortem interval could not reliably predict gas distribution (rho=0.719, p<0.0001). We found that a large amount of putrefaction-generated gas in the right heart was associated with aggregated gas bubbles in the hepatic parenchyma (sensitivity = 100%, specificity = 89.7%). In contrast, gas in the left heart (sensitivity = 41.7%, specificity = 100%) or in peri-umbilical subcutaneous tissues (sensitivity = 50%, specificity = 96.3%) could not predict gas due to putrefaction.¦Conclusion: This study is the first to show that the appearance of post-mortem gas follows a specific distribution pattern. An association between intracardiac gas and hepatic parenchymal gas could distinguish between post- mortem-generated gas and vital air embolism. We propose that this finding provides a key for diagnosing death due to cardiac air embolism.

Imaging and modeling of pore scale processes in porous media using X-ray computed tomography and lattice Boltzmann solver

In der Erdöl– und Gasindustrie sind bildgebende Verfahren und Simulationen auf der Porenskala im Begriff Routineanwendungen zu werden. Ihr weiteres Potential lässt sich im Umweltbereich anwenden, wie z.B. für den Transport und Verbleib von Schadstoffen im Untergrund, die Speicherung von Kohlendioxid und dem natürlichen Abbau von Schadstoffen in Böden. Mit der Röntgen-Computertomografie (XCT) steht ein zerstörungsfreies 3D bildgebendes Verfahren zur Verfügung, das auch häufig für die Untersuchung der internen Struktur geologischer Proben herangezogen wird. Das erste Ziel dieser Dissertation war die Implementierung einer Bildverarbeitungstechnik, die die Strahlenaufhärtung der Röntgen-Computertomografie beseitigt und den Segmentierungsprozess dessen Daten vereinfacht. Das zweite Ziel dieser Arbeit untersuchte die kombinierten Effekte von Porenraumcharakteristika, Porentortuosität, sowie die Strömungssimulation und Transportmodellierung in Porenräumen mit der Gitter-Boltzmann-Methode. In einer zylindrischen geologischen Probe war die Position jeder Phase auf Grundlage der Beobachtung durch das Vorhandensein der Strahlenaufhärtung in den rekonstruierten Bildern, das eine radiale Funktion vom Probenrand zum Zentrum darstellt, extrahierbar und die unterschiedlichen Phasen ließen sich automatisch segmentieren. Weiterhin wurden Strahlungsaufhärtungeffekte von beliebig geformten Objekten durch einen Oberflächenanpassungsalgorithmus korrigiert. Die Methode der „least square support vector machine” (LSSVM) ist durch einen modularen Aufbau charakterisiert und ist sehr gut für die Erkennung und Klassifizierung von Mustern geeignet. Aus diesem Grund wurde die Methode der LSSVM als pixelbasierte Klassifikationsmethode implementiert. Dieser Algorithmus ist in der Lage komplexe geologische Proben korrekt zu klassifizieren, benötigt für den Fall aber längere Rechenzeiten, so dass mehrdimensionale Trainingsdatensätze verwendet werden müssen. Die Dynamik von den unmischbaren Phasen Luft und Wasser wird durch eine Kombination von Porenmorphologie und Gitter Boltzmann Methode für Drainage und Imbibition Prozessen in 3D Datensätzen von Böden, die durch synchrotron-basierte XCT gewonnen wurden, untersucht. Obwohl die Porenmorphologie eine einfache Methode ist Kugeln in den verfügbaren Porenraum einzupassen, kann sie dennoch die komplexe kapillare Hysterese als eine Funktion der Wassersättigung erklären. Eine Hysterese ist für den Kapillardruck und die hydraulische Leitfähigkeit beobachtet worden, welche durch die hauptsächlich verbundenen Porennetzwerke und der verfügbaren Porenraumgrößenverteilung verursacht sind. Die hydraulische Konduktivität ist eine Funktion des Wassersättigungslevels und wird mit einer makroskopischen Berechnung empirischer Modelle verglichen. Die Daten stimmen vor allem für hohe Wassersättigungen gut überein. Um die Gegenwart von Krankheitserregern im Grundwasser und Abwässern vorhersagen zu können, wurde in einem Bodenaggregat der Einfluss von Korngröße, Porengeometrie und Fluidflussgeschwindigkeit z.B. mit dem Mikroorganismus Escherichia coli studiert. Die asymmetrischen und langschweifigen Durchbruchskurven, besonders bei höheren Wassersättigungen, wurden durch dispersiven Transport aufgrund des verbundenen Porennetzwerks und durch die Heterogenität des Strömungsfeldes verursacht. Es wurde beobachtet, dass die biokolloidale Verweilzeit eine Funktion des Druckgradienten als auch der Kolloidgröße ist. Unsere Modellierungsergebnisse stimmen sehr gut mit den bereits veröffentlichten Daten überein.

Hypervascular liver tumors: low tube voltage, high tube current multi-detector row CT for enhanced detection--phantom study

PURPOSE: To prospectively evaluate, for the depiction of simulated hypervascular liver lesions in a phantom, the effect of a low tube voltage, high tube current computed tomographic (CT) technique on image noise, contrast-to-noise ratio (CNR), lesion conspicuity, and radiation dose. MATERIALS AND METHODS: A custom liver phantom containing 16 cylindric cavities (four cavities each of 3, 5, 8, and 15 mm in diameter) filled with various iodinated solutions to simulate hypervascular liver lesions was scanned with a 64-section multi-detector row CT scanner at 140, 120, 100, and 80 kVp, with corresponding tube current-time product settings at 225, 275, 420, and 675 mAs, respectively. The CNRs for six simulated lesions filled with different iodinated solutions were calculated. A figure of merit (FOM) for each lesion was computed as the ratio of CNR2 to effective dose (ED). Three radiologists independently graded the conspicuity of 16 simulated lesions. An anthropomorphic phantom was scanned to evaluate the ED. Statistical analysis included one-way analysis of variance. RESULTS: Image noise increased by 45% with the 80-kVp protocol compared with the 140-kVp protocol (P < .001). However, the lowest ED and the highest CNR were achieved with the 80-kVp protocol. The FOM results indicated that at a constant ED, a reduction of tube voltage from 140 to 120, 100, and 80 kVp increased the CNR by factors of at least 1.6, 2.4, and 3.6, respectively (P < .001). At a constant CNR, corresponding reductions in ED were by a factor of 2.5, 5.5, and 12.7, respectively (P < .001). The highest lesion conspicuity was achieved with the 80-kVp protocol. CONCLUSION: The CNR of simulated hypervascular liver lesions can be substantially increased and the radiation dose reduced by using an 80-kVp, high tube current CT technique.

True four-dimensional analysis of thoracic aortic displacement and distension using model-based segmentation of computed tomography angiography.

Previous analyses of aortic displacement and distension using computed tomography angiography (CTA) were performed on double-oblique multi-planar reformations and did not consider through-plane motion. The aim of this study was to overcome this limitation by using a novel computational approach for the assessment of thoracic aortic displacement and distension in their true four-dimensional extent. Vessel segmentation with landmark tracking was executed on CTA of 24 patients without evidence of aortic disease. Distension magnitudes and maximum displacement vectors (MDV) including their direction were analyzed at 5 aortic locations: left coronary artery (COR), mid-ascending aorta (ASC), brachiocephalic trunk (BCT), left subclavian artery (LSA), descending aorta (DES). Distension was highest for COR (2.3 ± 1.2 mm) and BCT (1.7 ± 1.1 mm) compared with ASC, LSA, and DES (p < 0.005). MDV decreased from COR to LSA (p < 0.005) and was highest for COR (6.2 ± 2.0 mm) and ASC (3.8 ± 1.9 mm). Displacement was directed towards left and anterior at COR and ASC. Craniocaudal displacement at COR and ASC was 1.3 ± 0.8 and 0.3 ± 0.3 mm. At BCT, LSA, and DES no predominant displacement direction was observable. Vessel displacement and wall distension are highest in the ascending aorta, and ascending aortic displacement is primarily directed towards left and anterior. Craniocaudal displacement remains low even close to the left cardiac ventricle.

Evaluation of treatment response after chemoembolisation (TACE) in hepatocellular carcinoma using real time image fusion of contrast-enhanced ultrasound (CEUS) and computed tomography (CT)--preliminary results.

OBJECTIVE To evaluate treatment response of hepatocellular carcinoma (HCC) after transarterial chemoembolization (TACE) with a new real-time imaging fusion technique of contrast-enhanced ultrasound (CEUS) with multi-slice detection computed tomography (CT) in comparison to conventional post-interventional follow-up. MATERIAL AND METHODS 40 patients with HCC (26 male, ages 46-81 years) were evaluated 24 hours after TACE using CEUS with ultrasound volume navigation and image fusion with CT compared to non-enhanced CT and follow-up contrast-enhanced CT after 6-8 weeks. Reduction of tumor vascularization to less than 25% was regarded as "successful" treatment, whereas reduction to levels >25% was considered as "partial" treatment response. Homogenous lipiodol retention was regarded as successful treatment in non-enhanced CT. RESULTS Post-interventional image fusion of CEUS with CT was feasible in all 40 patients. In 24 patients (24/40), post-interventional image fusion with CEUS revealed residual tumor vascularity, that was confirmed by contrast-enhanced CT 6-8 weeks later in 24/24 patients. In 16 patients (16/40), post-interventional image fusion with CEUS demonstrated successful treatment, but follow-up CT detected residual viable tumor (6/16). Non-enhanced CT did not identify any case of treatment failure. Image fusion with CEUS assessed treatment efficacy with a specificity of 100%, sensitivity of 80% and a positive predictive value of 1 (negative predictive value 0.63). CONCLUSIONS Image fusion of CEUS with CT allows a reliable, highly specific post-interventional evaluation of embolization response with good sensitivity without any further radiation exposure. It can detect residual viable tumor at early state, resulting in a close patient monitoring or re-therapy.

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.