386 research outputs found
Automated Inline Analysis of Myocardial Perfusion MRI with Deep Learning
Recent development of quantitative myocardial blood flow (MBF) mapping allows
direct evaluation of absolute myocardial perfusion, by computing pixel-wise
flow maps. Clinical studies suggest quantitative evaluation would be more
desirable for objectivity and efficiency. Objective assessment can be further
facilitated by segmenting the myocardium and automatically generating reports
following the AHA model. This will free user interaction for analysis and lead
to a 'one-click' solution to improve workflow. This paper proposes a deep
neural network based computational workflow for inline myocardial perfusion
analysis. Adenosine stress and rest perfusion scans were acquired from three
hospitals. Training set included N=1,825 perfusion series from 1,034 patients.
Independent test set included 200 scans from 105 patients. Data were
consecutively acquired at each site. A convolution neural net (CNN) model was
trained to provide segmentation for LV cavity, myocardium and right ventricular
by processing incoming 2D+T perfusion Gd series. Model outputs were compared to
manual ground-truth for accuracy of segmentation and flow measures derived on
global and per-sector basis. The trained models were integrated onto MR
scanners for effective inference. Segmentation accuracy and myocardial flow
measures were compared between CNN models and manual ground-truth. The mean
Dice ratio of CNN derived myocardium was 0.93 +/- 0.04. Both global flow and
per-sector values showed no significant difference, compared to manual results.
The AHA 16 segment model was automatically generated and reported on the MR
scanner. As a result, the fully automated analysis of perfusion flow mapping
was achieved. This solution was integrated on the MR scanner, enabling
'one-click' analysis and reporting of myocardial blood flow.Comment: This work has been submitted to Radiology: Artificial Intelligence
for possible publicatio
Evaluation of an automated method for arterial input function detection for first-pass myocardial perfusion cardiovascular magnetic resonance
ABSTRACT: Background: Quantitative assessment of myocardial blood flow (MBF) with first-pass perfusion cardiovascular magnetic resonance (CMR) requires a measurement of the arterial input function (AIF). This study presents an automated method to improve the objectivity and reduce processing time for measuring the AIF from first-pass perfusion CMR images. This automated method is used to compare the impact of different AIF measurements on MBF quantification.Methods: Gadolinium-enhanced perfusion CMR was performed on a 1.5 T scanner using a saturation recovery dual-sequence technique. Rest and stress perfusion series from 270 clinical studies were analyzed. Automated image processing steps included motion correction, intensity correction, detection of the left ventricle (LV), independent component analysis, and LV pixel thresholding to calculate the AIF signal. The results were compared with manual reference measurements using several quality metrics based on the contrast enhancement and timing characteristics of the AIF. The median and 95 % confidence interval (CI) of the median were reported. Finally, MBF was calculated and compared in a subset of 21 clinical studies using the automated and manual AIF measurements.Results: Two clinical studies were excluded from the comparison due to a congenital heart defect present in one and a contrast administration issue in the other. The proposed method successfully processed 99.63 % of the remaining image series. Manual and automatic AIF time-signal intensity curves were strongly correlated with median correlation coefficient of 0.999 (95 % CI [0.999, 0.999]). The automated method effectively selected bright LV pixels, excluded papillary muscles, and required less processing time than the manual approach. There was no significant difference in MBF estimates between manually and automatically measured AIFs (p = NS). However, different sizes of regions of interest selection in the LV cavity could change the AIF measurement and affect MBF calculation (p = NS to p = 0.03).Conclusion: The proposed automatic method produced AIFs similar to the reference manual method but required less processing time and was more objective. The automated algorithm may improve AIF measurement from the first-pass perfusion CMR images and make quantitative myocardial perfusion analysis more robust and readily available
Development of Advanced Acquisition and Reconstruction Techniques for Real-Time Perfusion MRI
Diese Doktorarbeit befasst sich mit der methodischen Entwicklung von Akquisition- und Rekonstruktionstechniken zur Anwendung von Echtzeit-Bildgebungstechniken auf das Gebiet der dynamischen kontrastmittelgestützten Magentresonanztomographie. Zur Unterdrückung unerwünschter Bildartefakte wird eine neue Spoiling-Technik vorgeschlagen, die auf randomisierten Phasen der Hochfrequenzanregung basiert. Diese Technik erlaubt eine schnelle, artefaktfreie Aufnahme von T1-gewichteten Rohdaten bei radialer Abtastung. Die Rekonstruktion quantitativer Parameterkarten aus solchen Rohdaten kann als nichtlineares, inverses Problem aufgefasst werden. In dieser Arbeit wird eine modellbasierte Rekonstruktionstechnik zur quantitativen T1-Kartierung entwickelt, die dieses inverse Problem mittels der iterativ regularisierten Gauß-Newton-Methode mit parameterspezifischer Regularisierung löst. In Simulationen sowie in-vitro- und in-vivo-Studien wird Genauigkeit und Präzision dieser neuen Methode geprüft, die ihre direkte Anwendung in in-vitro-Experimenten zur "first-pass"-Perfusion findet. In diesen Experimenten wird ein kommerziell verfügbares Phantom verwendet, dass in-vivo-Perfusion simuliert und gleichzeitig vollständige Kontrolle über die vorherrschenden Austauschraten erlaubt
Evaluation of an automated method for arterial input function detection for first-pass myocardial perfusion cardiovascular magnetic resonance
Background: Quantitative assessment of myocardial blood flow (MBF) with first-pass perfusion cardiovascular magnetic resonance (CMR) requires a measurement of the arterial input function (AIF). This study presents an automated method to improve the objectivity and reduce processing time for measuring the AIF from first-pass perfusion CMR images. This automated method is used to compare the impact of different AIF measurements on MBF quantification.Methods: Gadolinium-enhanced perfusion CMR was performed on a 1.5 T scanner using a saturation recovery dual-sequence technique. Rest and stress perfusion series from 270 clinical studies were analyzed. Automated image processing steps included motion correction, intensity correction, detection of the left ventricle (LV), independent component analysis, and LV pixel thresholding to calculate the AIF signal. The results were compared with manual reference measurements using several quality metrics based on the contrast enhancement and timing characteristics of the AIF. The median and 95 % confidence interval (CI) of the median were reported. Finally, MBF was calculated and compared in a subset of 21 clinical studies using the automated and manual AIF measurements.Results: Two clinical studies were excluded from the comparison due to a congenital heart defect present in one and a contrast administration issue in the other. The proposed method successfully processed 99.63 % of the remaining image series. Manual and automatic AIF time-signal intensity curves were strongly correlated with median correlation coefficient of 0.999 (95 % CI [0.999, 0.999]). The automated method effectively selected bright LV pixels, excluded papillary muscles, and required less processing time than the manual approach. There was no significant difference in MBF estimates between manually and automatically measured AIFs (p = NS). However, different sizes of regions of interest selection in the LV cavity could change the AIF measurement and affect MBF calculation (p = NS to p = 0.03).Conclusion: The proposed automatic method produced AIFs similar to the reference manual method but required less processing time and was more objective. The automated algorithm may improve AIF measurement from the first-pass perfusion CMR images and make quantitative myocardial perfusion analysis more robust and readily available
Analysis of contrast-enhanced medical images.
Early detection of human organ diseases is of great importance for the accurate diagnosis and institution of appropriate therapies. This can potentially prevent progression to end-stage disease by detecting precursors that evaluate organ functionality. In addition, it also assists the clinicians for therapy evaluation, tracking diseases progression, and surgery operations. Advances in functional and contrast-enhanced (CE) medical images enabled accurate noninvasive evaluation of organ functionality due to their ability to provide superior anatomical and functional information about the tissue-of-interest. The main objective of this dissertation is to develop a computer-aided diagnostic (CAD) system for analyzing complex data from CE magnetic resonance imaging (MRI). The developed CAD system has been tested in three case studies: (i) early detection of acute renal transplant rejection, (ii) evaluation of myocardial perfusion in patients with ischemic heart disease after heart attack; and (iii), early detection of prostate cancer. However, developing a noninvasive CAD system for the analysis of CE medical images is subject to multiple challenges, including, but are not limited to, image noise and inhomogeneity, nonlinear signal intensity changes of the images over the time course of data acquisition, appearances and shape changes (deformations) of the organ-of-interest during data acquisition, determination of the best features (indexes) that describe the perfusion of a contrast agent (CA) into the tissue. To address these challenges, this dissertation focuses on building new mathematical models and learning techniques that facilitate accurate analysis of CAs perfusion in living organs and include: (i) accurate mathematical models for the segmentation of the object-of-interest, which integrate object shape and appearance features in terms of pixel/voxel-wise image intensities and their spatial interactions; (ii) motion correction techniques that combine both global and local models, which exploit geometric features, rather than image intensities to avoid problems associated with nonlinear intensity variations of the CE images; (iii) fusion of multiple features using the genetic algorithm. The proposed techniques have been integrated into CAD systems that have been tested in, but not limited to, three clinical studies. First, a noninvasive CAD system is proposed for the early and accurate diagnosis of acute renal transplant rejection using dynamic contrast-enhanced MRI (DCE-MRI). Acute rejection–the immunological response of the human immune system to a foreign kidney–is the most sever cause of renal dysfunction among other diagnostic possibilities, including acute tubular necrosis and immune drug toxicity. In the U.S., approximately 17,736 renal transplants are performed annually, and given the limited number of donors, transplanted kidney salvage is an important medical concern. Thus far, biopsy remains the gold standard for the assessment of renal transplant dysfunction, but only as the last resort because of its invasive nature, high cost, and potential morbidity rates. The diagnostic results of the proposed CAD system, based on the analysis of 50 independent in-vivo cases were 96% with a 95% confidence interval. These results clearly demonstrate the promise of the proposed image-based diagnostic CAD system as a supplement to the current technologies, such as nuclear imaging and ultrasonography, to determine the type of kidney dysfunction. Second, a comprehensive CAD system is developed for the characterization of myocardial perfusion and clinical status in heart failure and novel myoregeneration therapy using cardiac first-pass MRI (FP-MRI). Heart failure is considered the most important cause of morbidity and mortality in cardiovascular disease, which affects approximately 6 million U.S. patients annually. Ischemic heart disease is considered the most common underlying cause of heart failure. Therefore, the detection of the heart failure in its earliest forms is essential to prevent its relentless progression to premature death. While current medical studies focus on detecting pathological tissue and assessing contractile function of the diseased heart, this dissertation address the key issue of the effects of the myoregeneration therapy on the associated blood nutrient supply. Quantitative and qualitative assessment in a cohort of 24 perfusion data sets demonstrated the ability of the proposed framework to reveal regional perfusion improvements with therapy, and transmural perfusion differences across the myocardial wall; thus, it can aid in follow-up on treatment for patients undergoing the myoregeneration therapy. Finally, an image-based CAD system for early detection of prostate cancer using DCE-MRI is introduced. Prostate cancer is the most frequently diagnosed malignancy among men and remains the second leading cause of cancer-related death in the USA with more than 238,000 new cases and a mortality rate of about 30,000 in 2013. Therefore, early diagnosis of prostate cancer can improve the effectiveness of treatment and increase the patient’s chance of survival. Currently, needle biopsy is the gold standard for the diagnosis of prostate cancer. However, it is an invasive procedure with high costs and potential morbidity rates. Additionally, it has a higher possibility of producing false positive diagnosis due to relatively small needle biopsy samples. Application of the proposed CAD yield promising results in a cohort of 30 patients that would, in the near future, represent a supplement of the current technologies to determine prostate cancer type. The developed techniques have been compared to the state-of-the-art methods and demonstrated higher accuracy as shown in this dissertation. The proposed models (higher-order spatial interaction models, shape models, motion correction models, and perfusion analysis models) can be used in many of today’s CAD applications for early detection of a variety of diseases and medical conditions, and are expected to notably amplify the accuracy of CAD decisions based on the automated analysis of CE images
Mapping the Impact and Plasticity of Cortical-Cardiovascular Interactions in Vascular Disease Using Structural and Functional MRI
There is growing interest in the role of vascular disease in accelerating age-related decline in cerebrovascular structural and functional integrity. Since an increased number of older adults are surviving chronic diseases, of which cardiovascular disease (CVD) is prevalent, there is an urgent need to understand relationships between cardiovascular dysfunction and brain health. It is unclear if CVD puts the brains of older adults, already experiencing natural brain aging, at greater risk for degeneration. In this thesis, the role of CVD in accelerating brain aging is explored. Because physical activity is known to provide neuroprotective benefits to brains of older adults, the role of physical activity in mediating disease effects were also explored.
Using novel neuroimaging techniques, measures of gray matter volume and cerebrovascular hemodynamics were compared between groups of coronary artery disease patients and age-matched controls, to describe regional effects of CVD on the brain. In a sub-set of patients, imaging measures were repeated after completion of a 6-month exercise training, part of a cardiac rehabilitation program, to examine exercise effects. Differences in cerebrovascular hemodynamics were measured as changes in resting cerebral blood flow (CBF) and changes in cerebrovascular reactivity (CVR) to hypercapnia (6% CO2) using a non-invasive perfusion magnetic resonance imaging technique, arterial spin labelling (ASL). We found decreased brain volume, CBF and CVR in several regions of the brains of coronary artery disease patients compared to age-matched healthy controls. The reductions in CBF and CVR were independent of underlying brain atrophy, suggesting that changes in cerebrovascular function could precede changes in brain structure. In addition, increase in brain volume and CBF were observed in some regions of the brain after exercise training, indicating that cardiac rehabilitation programs may have neurorehabiliation effects as well.
Since, CBF measured with ASL is not the [gold] standard measure of functional brain activity, we examined the regional correlation of ASL-CBF to glucose consumption rates (CMRglc) measured with positron emission tomography (PET), a widely acceptable marker of brain functional activity. Simultaneous measurements of ASL-CBF and PET-CMRglc were performed in a separate study in a group of older adults with no neurological impairment. Across brain regions, ASL-CBF correlated well with PET-CMRglc, but variations in regional coupling were found and demonstrate the role of certain brain regions in maintaining higher level of functional organization compared to other regions.
In general, the results of the thesis demonstrate the impact of CVD on brain health, and the neurorehabiliation capacity of cardiac rehabilitation. The work presented also highlights the ability of novel non-invasive neuroimaging techniques in detecting and monitoring subtle but robust changes in the aging human brain
Automatic Spatiotemporal Analysis of Cardiac Image Series
RÉSUMÉ
Ă€ ce jour, les maladies cardiovasculaires demeurent au premier rang des principales causes de
décès en Amérique du Nord. Chez l’adulte et au sein de populations de plus en plus jeunes,
la soi-disant épidémie d’obésité entraînée par certaines habitudes de vie tels que la mauvaise
alimentation, le manque d’exercice et le tabagisme est lourde de conséquences pour les personnes
affectées, mais aussi sur le système de santé. La principale cause de morbidité et de
mortalité chez ces patients est l’athérosclérose, une accumulation de plaque à l’intérieur des
vaisseaux sanguins à hautes pressions telles que les artères coronaires. Les lésions athérosclérotiques
peuvent entraîner l’ischémie en bloquant la circulation sanguine et/ou en provoquant
une thrombose. Cela mène souvent à de graves conséquences telles qu’un infarctus. Outre les
problèmes liés à la sténose, les parois artérielles des régions criblées de plaque augmentent la
rigidité des parois vasculaires, ce qui peut aggraver la condition du patient. Dans la population
pédiatrique, la pathologie cardiovasculaire acquise la plus fréquente est la maladie de
Kawasaki. Il s’agit d’une vasculite aigüe pouvant affecter l’intégrité structurale des parois des
artères coronaires et mener à la formation d’anévrismes. Dans certains cas, ceux-ci entravent
l’hémodynamie artérielle en engendrant une perfusion myocardique insuffisante et en activant
la formation de thromboses.
Le diagnostic de ces deux maladies coronariennes sont traditionnellement effectués à l’aide
d’angiographies par fluoroscopie. Pendant ces examens paracliniques, plusieurs centaines de
projections radiographiques sont acquises en séries suite à l’infusion artérielle d’un agent de
contraste. Ces images révèlent la lumière des vaisseaux sanguins et la présence de lésions
potentiellement pathologiques, s’il y a lieu. Parce que les séries acquises contiennent de l’information
très dynamique en termes de mouvement du patient volontaire et involontaire (ex.
battements cardiaques, respiration et déplacement d’organes), le clinicien base généralement
son interprétation sur une seule image angiographique où des mesures géométriques sont effectuées
manuellement ou semi-automatiquement par un technicien en radiologie. Bien que
l’angiographie par fluoroscopie soit fréquemment utilisé partout dans le monde et souvent
considéré comme l’outil de diagnostic “gold-standard” pour de nombreuses maladies vasculaires,
la nature bidimensionnelle de cette modalité d’imagerie est malheureusement très
limitante en termes de spécification géométrique des différentes régions pathologiques. En effet,
la structure tridimensionnelle des sténoses et des anévrismes ne peut pas être pleinement
appréciée en 2D car les caractéristiques observées varient selon la configuration angulaire de
l’imageur. De plus, la présence de lésions affectant les artères coronaires peut ne pas refléter
la véritable santé du myocarde, car des mécanismes compensatoires naturels (ex. vaisseaux----------ABSTRACT
Cardiovascular disease continues to be the leading cause of death in North America. In adult
and, alarmingly, ever younger populations, the so-called obesity epidemic largely driven by
lifestyle factors that include poor diet, lack of exercise and smoking, incurs enormous stresses
on the healthcare system. The primary cause of serious morbidity and mortality for these
patients is atherosclerosis, the build up of plaque inside high pressure vessels like the coronary
arteries. These lesions can lead to ischemic disease and may progress to precarious blood
flow blockage or thrombosis, often with infarction or other severe consequences. Besides
the stenosis-related outcomes, the arterial walls of plaque-ridden regions manifest increased
stiffness, which may exacerbate negative patient prognosis. In pediatric populations, the
most prevalent acquired cardiovascular pathology is Kawasaki disease. This acute vasculitis
may affect the structural integrity of coronary artery walls and progress to aneurysmal lesions.
These can hinder the blood flow’s hemodynamics, leading to inadequate downstream
perfusion, and may activate thrombus formation which may lead to precarious prognosis.
Diagnosing these two prominent coronary artery diseases is traditionally performed using
fluoroscopic angiography. Several hundred serial x-ray projections are acquired during selective
arterial infusion of a radiodense contrast agent, which reveals the vessels’ luminal
area and possible pathological lesions. The acquired series contain highly dynamic information
on voluntary and involuntary patient movement: respiration, organ displacement and
heartbeat, for example. Current clinical analysis is largely limited to a single angiographic
image where geometrical measures will be performed manually or semi-automatically by a
radiological technician. Although widely used around the world and generally considered
the gold-standard diagnosis tool for many vascular diseases, the two-dimensional nature of
this imaging modality is limiting in terms of specifying the geometry of various pathological
regions. Indeed, the 3D structures of stenotic or aneurysmal lesions may not be fully appreciated
in 2D because their observable features are dependent on the angular configuration of
the imaging gantry. Furthermore, the presence of lesions in the coronary arteries may not
reflect the true health of the myocardium, as natural compensatory mechanisms may obviate
the need for further intervention. In light of this, cardiac magnetic resonance perfusion
imaging is increasingly gaining attention and clinical implementation, as it offers a direct
assessment of myocardial tissue viability following infarction or suspected coronary artery
disease. This type of modality is plagued, however, by motion similar to that present in fluoroscopic
imaging. This issue predisposes clinicians to laborious manual intervention in order
to align anatomical structures in sequential perfusion frames, thus hindering automation o
Automatic Spatiotemporal Analysis of Cardiac Image Series
RÉSUMÉ
Ă€ ce jour, les maladies cardiovasculaires demeurent au premier rang des principales causes de
décès en Amérique du Nord. Chez l’adulte et au sein de populations de plus en plus jeunes,
la soi-disant épidémie d’obésité entraînée par certaines habitudes de vie tels que la mauvaise
alimentation, le manque d’exercice et le tabagisme est lourde de conséquences pour les personnes
affectées, mais aussi sur le système de santé. La principale cause de morbidité et de
mortalité chez ces patients est l’athérosclérose, une accumulation de plaque à l’intérieur des
vaisseaux sanguins à hautes pressions telles que les artères coronaires. Les lésions athérosclérotiques
peuvent entraîner l’ischémie en bloquant la circulation sanguine et/ou en provoquant
une thrombose. Cela mène souvent à de graves conséquences telles qu’un infarctus. Outre les
problèmes liés à la sténose, les parois artérielles des régions criblées de plaque augmentent la
rigidité des parois vasculaires, ce qui peut aggraver la condition du patient. Dans la population
pédiatrique, la pathologie cardiovasculaire acquise la plus fréquente est la maladie de
Kawasaki. Il s’agit d’une vasculite aigüe pouvant affecter l’intégrité structurale des parois des
artères coronaires et mener à la formation d’anévrismes. Dans certains cas, ceux-ci entravent
l’hémodynamie artérielle en engendrant une perfusion myocardique insuffisante et en activant
la formation de thromboses.
Le diagnostic de ces deux maladies coronariennes sont traditionnellement effectués à l’aide
d’angiographies par fluoroscopie. Pendant ces examens paracliniques, plusieurs centaines de
projections radiographiques sont acquises en séries suite à l’infusion artérielle d’un agent de
contraste. Ces images révèlent la lumière des vaisseaux sanguins et la présence de lésions
potentiellement pathologiques, s’il y a lieu. Parce que les séries acquises contiennent de l’information
très dynamique en termes de mouvement du patient volontaire et involontaire (ex.
battements cardiaques, respiration et déplacement d’organes), le clinicien base généralement
son interprétation sur une seule image angiographique où des mesures géométriques sont effectuées
manuellement ou semi-automatiquement par un technicien en radiologie. Bien que
l’angiographie par fluoroscopie soit fréquemment utilisé partout dans le monde et souvent
considéré comme l’outil de diagnostic “gold-standard” pour de nombreuses maladies vasculaires,
la nature bidimensionnelle de cette modalité d’imagerie est malheureusement très
limitante en termes de spécification géométrique des différentes régions pathologiques. En effet,
la structure tridimensionnelle des sténoses et des anévrismes ne peut pas être pleinement
appréciée en 2D car les caractéristiques observées varient selon la configuration angulaire de
l’imageur. De plus, la présence de lésions affectant les artères coronaires peut ne pas refléter
la véritable santé du myocarde, car des mécanismes compensatoires naturels (ex. vaisseaux----------ABSTRACT
Cardiovascular disease continues to be the leading cause of death in North America. In adult
and, alarmingly, ever younger populations, the so-called obesity epidemic largely driven by
lifestyle factors that include poor diet, lack of exercise and smoking, incurs enormous stresses
on the healthcare system. The primary cause of serious morbidity and mortality for these
patients is atherosclerosis, the build up of plaque inside high pressure vessels like the coronary
arteries. These lesions can lead to ischemic disease and may progress to precarious blood
flow blockage or thrombosis, often with infarction or other severe consequences. Besides
the stenosis-related outcomes, the arterial walls of plaque-ridden regions manifest increased
stiffness, which may exacerbate negative patient prognosis. In pediatric populations, the
most prevalent acquired cardiovascular pathology is Kawasaki disease. This acute vasculitis
may affect the structural integrity of coronary artery walls and progress to aneurysmal lesions.
These can hinder the blood flow’s hemodynamics, leading to inadequate downstream
perfusion, and may activate thrombus formation which may lead to precarious prognosis.
Diagnosing these two prominent coronary artery diseases is traditionally performed using
fluoroscopic angiography. Several hundred serial x-ray projections are acquired during selective
arterial infusion of a radiodense contrast agent, which reveals the vessels’ luminal
area and possible pathological lesions. The acquired series contain highly dynamic information
on voluntary and involuntary patient movement: respiration, organ displacement and
heartbeat, for example. Current clinical analysis is largely limited to a single angiographic
image where geometrical measures will be performed manually or semi-automatically by a
radiological technician. Although widely used around the world and generally considered
the gold-standard diagnosis tool for many vascular diseases, the two-dimensional nature of
this imaging modality is limiting in terms of specifying the geometry of various pathological
regions. Indeed, the 3D structures of stenotic or aneurysmal lesions may not be fully appreciated
in 2D because their observable features are dependent on the angular configuration of
the imaging gantry. Furthermore, the presence of lesions in the coronary arteries may not
reflect the true health of the myocardium, as natural compensatory mechanisms may obviate
the need for further intervention. In light of this, cardiac magnetic resonance perfusion
imaging is increasingly gaining attention and clinical implementation, as it offers a direct
assessment of myocardial tissue viability following infarction or suspected coronary artery
disease. This type of modality is plagued, however, by motion similar to that present in fluoroscopic
imaging. This issue predisposes clinicians to laborious manual intervention in order
to align anatomical structures in sequential perfusion frames, thus hindering automation o
Diagnostic precision and sex differences in quantitative cardiovascular magnetic resonance
Correct medical treatment necessitates a correct diagnosis. Cardiac imaging aims to establish
an accurate diagnosis without performing unnecessary invasive procedures. Cardiovascular
magnetic resonance (CMR) has emerged as a valuable diagnostic tool in clinical cardiology
because of its inherently good soft-tissue contrast, dynamic visualizations and the possibility
to perform quantitative tissue characterization. However, diagnostic precision may be
affected in quantitative imaging by several factors such as the presence of sex differences, or
measurements errors. Therefore, the aim of this thesis was to identify parameters and sex
differences that affect precision and accuracy, and to evaluate post-processing methods to
increase diagnostic precision.
We found that intramyocardial blood affects native myocardial T1 values in patients without
focal abnormalities, and that native myocardial T1 values differ between the sexes. We
developed a blood correction model that maintained an increase in diagnostic precision by
13% when applied to an independent patient cohort, which furthermore also eliminated sex
differences in healthy volunteers in Study I. In Study II, we evaluated a post-processing
method called stationary tissue background correction for increasing diagnostic precision in
clinical blood flow measurements. We found that the number of patients with a pulmonaryto-systemic blood flow ratio (Qp/Qs) outside of the normal range decreased following
stationary tissue background correction. In Study III, we investigated the presence of sex
differences in a newly developed myocardial perfusion imaging sequence in healthy
volunteers. We found that women have higher myocardial blood volume, myocardial
perfusion and myocardial extracellular volume compared to men both at rest and during
adenosine stress, which provide mechanistic insight into myocardial physiology. In Study IV,
we investigated the clinical accuracy and precision of synthetic scar images (SynLGE) from
post-contrast T1 maps compared to conventional scar images (LGE) for diagnosing focal
myocardial fibrosis of any etiology. Compared to LGE, SynLGE yielded a sensitivity of 77%,
a specificity of 98%, a positive predictive value of 97% and a negative predictive value of
86%.
In conclusion, there are sex differences in several aspects of clinical quantitative CMR
imaging that may affect diagnostic precision. Post-processing is a powerful tool to improve
diagnostic precision both by increasing precision in native myocardial T1 values via blood
correction, and in Qp/Qs via stationary tissue background correction. SynLGE can provide
complementary confidence in the assessment of focal myocardial fibrosis in complement to
conventional LGE, and thereby increase diagnostic accuracy and precision
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