The impact of schizophrenia on frontal perfusion parameters: a DSC-MRI study

We performed a dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI) analysis to study the role of the demographic/clinical information on perfusion parameters between patients with schizophrenia and normal control subjects. 39 schizophrenia patients and 27 normal controls were studied with a Siemens 1.5T magnet. PWI images were obtained following intravenous injection of paramagnetic contrast agent (gadolinium-DTPA). For each perfusion parameter, i.e. relative cerebral blood flow (rCBF), relative cerebral blood volume (rCBV), mean transit time (MTT) and time-to-peak (TTP), the best predictor model was computed in left and right frontal cortex following a stepwise strategy. First of all, a linear model, including all the sociodemographic information and clinical variables as predictors was computed. At each step, the least significant predictor was excluded and a new linear model was evaluated until all predictors were excluded. Then, the best predictor model was selected based on the F statistic value and on the p value. The models for the rCBF and the rCBV both in the left and right frontal cortex were estimated independently from each other, and the best models contained the same predictors, i.e. clinical state, age, and length of illness. No significant models were obtained for the MTT and the TTP. This study showed a decrease in rCBF and rCBV frontal cortex values in subject affected by schizophrenia. Future DSC-MRI studies should further investigate the role of cerebral perfusion for the pathophysiology of the disease by recruiting first-episode patients and by considering cerebellar, parietal and temporal regions.

[1]  B. Rosen,et al.  High resolution measurement of cerebral blood flow using intravascular tracer bolus passages. Part II: Experimental comparison and preliminary results , 1996, Magnetic resonance in medicine.

[2]  R. Slutsky,et al.  Tissue distribution and magnetic resonance spin lattice relaxation effects of gadolinium-DTPA. , 1985, Radiology.

[3]  A. Versace,et al.  Decreased entorhinal cortex volumes in schizophrenia , 2008, Schizophrenia Research.

[4]  D G Gadian,et al.  Quantification of Perfusion Using Bolus Tracking Magnetic Resonance Imaging in Stroke: Assumptions, Limitations, and Potential Implications for Clinical Use , 2002, Stroke.

[5]  M. Viergever,et al.  Maximum likelihood estimation of cerebral blood flow in dynamic susceptibility contrast MRI , 1999, Magnetic resonance in medicine.

[6]  Hiroki Yamada,et al.  Quantitative analysis of cerebral microvascular hemodynamics with T2‐weighted dynamic MR imaging , 1999, Journal of magnetic resonance imaging : JMRI.

[7]  L. K. Hansen,et al.  Defining a local arterial input function for perfusion MRI using independent component analysis , 2004, Magnetic resonance in medicine.

[8]  T. Brugha,et al.  SCAN. Schedules for Clinical Assessment in Neuropsychiatry. , 1990, Archives of general psychiatry.

[9]  R. C. Oldfield The assessment and analysis of handedness: the Edinburgh inventory. , 1971, Neuropsychologia.

[10]  K. Zierler Equations for Measuring Blood Flow by External Monitoring of Radioisotopes , 1965, Circulation research.

[11]  C. Rasmussen,et al.  Perfusion quantification using Gaussian process deconvolution , 2002, Magnetic resonance in medicine.

[12]  Transfer index of MR relaxation enhancer: a quantitative evaluation of MR contrast enhancement. , 1989, AJNR. American journal of neuroradiology.

[13]  D. Gadian,et al.  Quantification of perfusion using bolus tracking MRI in stroke - Assumptions, limitations, and potential implications for clinical use , 2002 .

[14]  F. Ståhlberg,et al.  Assessment of regional cerebral blood flow by dynamic susceptibility contrast MRI using different deconvolution techniques , 2000, Magnetic resonance in medicine.

[15]  V. Haughton,et al.  Automatic calculation of the arterial input function for cerebral perfusion imaging with MR imaging. , 2003, Radiology.

[16]  R. Murray,et al.  Meta-analysis of regional brain volumes in schizophrenia. , 2000, The American journal of psychiatry.

[17]  David L. Thomas,et al.  Measuring Cerebral Blood Flow Using Magnetic Resonance Imaging Techniques , 1999, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[18]  Søren Christensen,et al.  Automatic selection of arterial input function using cluster analysis , 2006, Magnetic resonance in medicine.

[19]  B. Rosen,et al.  Tracer arrival timing‐insensitive technique for estimating flow in MR perfusion‐weighted imaging using singular value decomposition with a block‐circulant deconvolution matrix , 2003, Magnetic resonance in medicine.

[20]  O Salonen,et al.  Cerebral hemodynamics in a healthy population measured by dynamic susceptibility contrast MR imaging , 2003, Acta radiologica.

[21]  B. Rosen,et al.  High resolution measurement of cerebral blood flow using intravascular tracer bolus passages. Part I: Mathematical approach and statistical analysis , 1996, Magnetic resonance in medicine.

[22]  K. Zierler Theoretical Basis of Indicator‐Dilution Methods For Measuring Flow and Volume , 1962 .

[23]  Marcella Bellani,et al.  Orbitofrontal cortex abnormalities in schizophrenia , 2010, Epidemiologia e Psichiatria Sociale.

[24]  Emotion-Based Decision Making in schizophrenia: evidence from the Iowa Gambling Task , 2009, Epidemiologia e Psichiatria Sociale.

[25]  J. Whisstock,et al.  The X-Ray Crystal Structure of Escherichia coli Succinic Semialdehyde Dehydrogenase; Structural Insights into NADP+/Enzyme Interactions , 2010, PloS one.

[26]  C. Grandin,et al.  Assessment of brain perfusion with MRI: methodology and application to acute stroke , 2003, Neuroradiology.

[27]  Pascal Spincemaille,et al.  In vivo quantification of contrast agent concentration using the induced magnetic field for time-resolved arterial input function measurement with MRI. , 2008, Medical physics.

[28]  M. van Buchem,et al.  Associations between Total Cerebral Blood Flow and Age Related Changes of the Brain , 2010, PloS one.

[29]  M. Tansella,et al.  Evaluating a community‐based mental health service focusing on severe mental illness. The Verona experience , 2006, Acta psychiatrica Scandinavica. Supplementum.

[30]  Michael Hermes,et al.  Resting cerebral blood flow, attention, and aging , 2009, Brain Research.

[31]  A. Mokdad,et al.  Gene polymorphisms in association with emerging cardiovascular risk markers in adult women , 2010, BMC Medical Genetics.

[32]  Michele Tansella,et al.  Information systems for mental health , 2009, Epidemiologia e Psichiatria Sociale.

[33]  I. Gottesman,et al.  Theories of schizophrenia: a genetic-inflammatory-vascular synthesis , 2005, BMC Medical Genetics.

[34]  D. Gadian,et al.  Is quantification of bolus tracking MRI reliable without deconvolution? , 2002, Magnetic resonance in medicine.

[35]  K. Nuechterlein,et al.  Symptom dimensions in recent-onset schizophrenia and mania: a principal components analysis of the 24-item Brief Psychiatric Rating Scale , 2000, Psychiatry Research.

[36]  M. Tansella,et al.  The role of white matter for the pathophysiology of schizophrenia , 2007, International review of psychiatry.

[37]  P. F. Renshaw,et al.  Dynamic susceptibility contrast magnetic resonance imaging in neuropsychiatry: present utility and future promise , 1997, European Radiology.

[38]  K Sartor,et al.  Accuracy of gamma-variate fits to concentration-time curves from dynamic susceptibility-contrast enhanced MRI: influence of time resolution, maximal signal drop and signal-to-noise. , 1997, Magnetic resonance imaging.

[39]  A. Versace,et al.  Cerebral atrophy and white matter disruption in chronic schizophrenia , 2007, European Archives of Psychiatry and Clinical Neuroscience.

[40]  V G Kiselev On the theoretical basis of perfusion measurements by dynamic susceptibility contrast MRI , 2001, Magnetic resonance in medicine.

[41]  Michele Tansella,et al.  Assessment of cerebral blood volume in schizophrenia: A magnetic resonance imaging study. , 2007, Journal of psychiatric research.

[42]  M E Moseley,et al.  Early detection of ischemic injury: comparison of spectroscopy, diffusion-, T2-, and magnetic susceptibility-weighted MRI in cats. , 1990, Acta neurochirurgica. Supplementum.

[43]  F. Rehman Schedules for clinical assessment in neuropsychiatry , 2011, BMJ : British Medical Journal.