This talk delvers an hour-long overview of MR physics focusing on multiple topics at an introductory level, proceeds to provide tools that are open source based, for MR enthusiasts and beginners
Muon g-2 and Physics Beyond Standard ModelAtanu Nath
A talk delivered at the department of Physics of Assam University Silchar, especially directed towards the masters students. Central topic is the "Muon g-2 Experiment of Fermilab, USA" and how it might lead to the discovery of new physics (beyond the standard model of physics). This is a very basic introduction to the g-2 experiment.
Fermilab Muon g − 2 Experiment: Laser Based Gain Calibration SystemAtanu Nath
The Muon g-2 experiment at Fermilab (E989) is currently measuring the muon magnetic anomaly with a goal precision of 140 parts per billion, which will be a fourfold precision improvement over the current best measurement by the previous muon g-2 experiment at the Brookhaven Laboratory (BNL). The BNL-measured value of the muon magnetic anomaly and the corresponding Standard Model (SM) best estimate, differ by more than three standard deviation which inspired the current measurement as well as a theoretical drive for a significantly more precise calculation of the muon magnetic anomaly to rule out (or establish) statistical fluctuation as the origin of such a huge discrepancy. Stable central values along with 4-fold precision improvements in both theoretical (SM) and experimental fronts, would imply a ∼ 7σ discrepancy and that will be a clear hint of the physics beyond the Standard Model. Such unprecedented precision demands state-of-the-art technological improvements in all involved components to keep the systematic uncertainty below 70 ppb. This paper reports the current status of the E989 experiment after two years of data acquisition.
This presentation focuses on the role of MRI in biomedical engineering research with examples of a few global studies and the workflow associated with a MR academic project
This presentation is a starter for folks interested in the implementation and application of compressed sensing (CS) MRI. It includes a Matlab demo and list of well-known resources for CS MRI.
Muon g-2 and Physics Beyond Standard ModelAtanu Nath
A talk delivered at the department of Physics of Assam University Silchar, especially directed towards the masters students. Central topic is the "Muon g-2 Experiment of Fermilab, USA" and how it might lead to the discovery of new physics (beyond the standard model of physics). This is a very basic introduction to the g-2 experiment.
Fermilab Muon g − 2 Experiment: Laser Based Gain Calibration SystemAtanu Nath
The Muon g-2 experiment at Fermilab (E989) is currently measuring the muon magnetic anomaly with a goal precision of 140 parts per billion, which will be a fourfold precision improvement over the current best measurement by the previous muon g-2 experiment at the Brookhaven Laboratory (BNL). The BNL-measured value of the muon magnetic anomaly and the corresponding Standard Model (SM) best estimate, differ by more than three standard deviation which inspired the current measurement as well as a theoretical drive for a significantly more precise calculation of the muon magnetic anomaly to rule out (or establish) statistical fluctuation as the origin of such a huge discrepancy. Stable central values along with 4-fold precision improvements in both theoretical (SM) and experimental fronts, would imply a ∼ 7σ discrepancy and that will be a clear hint of the physics beyond the Standard Model. Such unprecedented precision demands state-of-the-art technological improvements in all involved components to keep the systematic uncertainty below 70 ppb. This paper reports the current status of the E989 experiment after two years of data acquisition.
This presentation focuses on the role of MRI in biomedical engineering research with examples of a few global studies and the workflow associated with a MR academic project
This presentation is a starter for folks interested in the implementation and application of compressed sensing (CS) MRI. It includes a Matlab demo and list of well-known resources for CS MRI.
This is a starter-presentation for folks trying to get their feet wet with medical image processing in a Matlab environment. It discusses certain simple image processing algorithms employed in the context of MR imaging with examples.
The talk gives an overview on pulse sequence design components in general and k-space trajectories in particular. Design problems are solved step by step for multiple trajectories with examples of applications. A few simulations of artifacts from these trajectories are also illustrated
Getting started with Matlab by Hannah Dotson, Vikram Kodibagkar laboratorySairam Geethanath
These slides are put together by Hannah Dotson, a STARS program intern at the Kodibagkar laboratory at UTSW. Folks new to Matlab and its usage at MIRC can find this tutorial material handy. Thanks Hannah!
Two Dimensional Image Reconstruction Algorithmsmastersrihari
Convolution Back-Projection (CBP) Algorithm was used for the reconstruction of the image. The performance was compared by implementing the algorithm by using RAM- LAK filter, Shepp- Logan filter and also No filter being used.
MRI PHYSICS PART 3 Susceptibility-weighted images BY GKM .pptxGulshan Verma
Susceptibility-weighted imaging (SWI) is based on a fully flow compensated, high-resolution, 3D gradient echo method by integrating both magnitude and phase information.
It was previously referred to as high resolution blood oxygen level– dependent (BOLD) venography (HRBV), but because of its broader application than evaluating venous structures, it is now referred to as SWI.
Susceptibility-weighted imaging (SWI) allows detection and characterization of tissue components based on differences in their susceptibilities.
SWI sequences are typically acquired in 3D (rather than 2D) mode,
Allowing thinner slices, and Use Smaller voxel sizes,
Flow compensation in all three directions is used to reduce artifacts,
Parallel imaging is employed to reduce imaging time.
Either single or multiple echoes may be acquired in a given TR interval.
A key feature of SWI is that magnitude and phase information are independently processed/displayed as well as combined for diagnostic purposes
This is a starter-presentation for folks trying to get their feet wet with medical image processing in a Matlab environment. It discusses certain simple image processing algorithms employed in the context of MR imaging with examples.
The talk gives an overview on pulse sequence design components in general and k-space trajectories in particular. Design problems are solved step by step for multiple trajectories with examples of applications. A few simulations of artifacts from these trajectories are also illustrated
Getting started with Matlab by Hannah Dotson, Vikram Kodibagkar laboratorySairam Geethanath
These slides are put together by Hannah Dotson, a STARS program intern at the Kodibagkar laboratory at UTSW. Folks new to Matlab and its usage at MIRC can find this tutorial material handy. Thanks Hannah!
Two Dimensional Image Reconstruction Algorithmsmastersrihari
Convolution Back-Projection (CBP) Algorithm was used for the reconstruction of the image. The performance was compared by implementing the algorithm by using RAM- LAK filter, Shepp- Logan filter and also No filter being used.
MRI PHYSICS PART 3 Susceptibility-weighted images BY GKM .pptxGulshan Verma
Susceptibility-weighted imaging (SWI) is based on a fully flow compensated, high-resolution, 3D gradient echo method by integrating both magnitude and phase information.
It was previously referred to as high resolution blood oxygen level– dependent (BOLD) venography (HRBV), but because of its broader application than evaluating venous structures, it is now referred to as SWI.
Susceptibility-weighted imaging (SWI) allows detection and characterization of tissue components based on differences in their susceptibilities.
SWI sequences are typically acquired in 3D (rather than 2D) mode,
Allowing thinner slices, and Use Smaller voxel sizes,
Flow compensation in all three directions is used to reduce artifacts,
Parallel imaging is employed to reduce imaging time.
Either single or multiple echoes may be acquired in a given TR interval.
A key feature of SWI is that magnitude and phase information are independently processed/displayed as well as combined for diagnostic purposes
International Journal of Computational Engineering Research(IJCER)ijceronline
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology.
UCSF Hyperpolarized MR #2: DNP Physics and Hardware (2019Peder Larson
UCSF Hyperpolarized MR Seminar
Summer 2019, Lecture #2
"DNP Physics and Hardware"
Lecturer: Jeremy Gordon
Sponsored by the NIH/NIBIB-supported UCSF Hyperpolarized MRI Technology Resource Center (P41EB013598)
https://radiology.ucsf.edu/research/labs/hyperpolarized-mri-tech
Optical band gap measurement by diffuse reflectance spectroscopy (drs)Sajjad Ullah
Introduction to Optical band gap measurement
by electronic spectroscopy and diffuse reflectance spectroscopy (DRS) with comparison of the results obtained suing different equation and measurement techniques.
The role of scattering in extinction of light as it passes through media is briefly discussed.
Unit 8 - Information and Communication Technology (Paper I).pdfThiyagu K
This slides describes the basic concepts of ICT, basics of Email, Emerging Technology and Digital Initiatives in Education. This presentations aligns with the UGC Paper I syllabus.
A Strategic Approach: GenAI in EducationPeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
Embracing GenAI - A Strategic ImperativePeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
2024.06.01 Introducing a competency framework for languag learning materials ...Sandy Millin
http://sandymillin.wordpress.com/iateflwebinar2024
Published classroom materials form the basis of syllabuses, drive teacher professional development, and have a potentially huge influence on learners, teachers and education systems. All teachers also create their own materials, whether a few sentences on a blackboard, a highly-structured fully-realised online course, or anything in between. Despite this, the knowledge and skills needed to create effective language learning materials are rarely part of teacher training, and are mostly learnt by trial and error.
Knowledge and skills frameworks, generally called competency frameworks, for ELT teachers, trainers and managers have existed for a few years now. However, until I created one for my MA dissertation, there wasn’t one drawing together what we need to know and do to be able to effectively produce language learning materials.
This webinar will introduce you to my framework, highlighting the key competencies I identified from my research. It will also show how anybody involved in language teaching (any language, not just English!), teacher training, managing schools or developing language learning materials can benefit from using the framework.
Operation “Blue Star” is the only event in the history of Independent India where the state went into war with its own people. Even after about 40 years it is not clear if it was culmination of states anger over people of the region, a political game of power or start of dictatorial chapter in the democratic setup.
The people of Punjab felt alienated from main stream due to denial of their just demands during a long democratic struggle since independence. As it happen all over the word, it led to militant struggle with great loss of lives of military, police and civilian personnel. Killing of Indira Gandhi and massacre of innocent Sikhs in Delhi and other India cities was also associated with this movement.
Francesca Gottschalk - How can education support child empowerment.pptxEduSkills OECD
Francesca Gottschalk from the OECD’s Centre for Educational Research and Innovation presents at the Ask an Expert Webinar: How can education support child empowerment?
Macroeconomics- Movie Location
This will be used as part of your Personal Professional Portfolio once graded.
Objective:
Prepare a presentation or a paper using research, basic comparative analysis, data organization and application of economic information. You will make an informed assessment of an economic climate outside of the United States to accomplish an entertainment industry objective.
Model Attribute Check Company Auto PropertyCeline George
In Odoo, the multi-company feature allows you to manage multiple companies within a single Odoo database instance. Each company can have its own configurations while still sharing common resources such as products, customers, and suppliers.
Safalta Digital marketing institute in Noida, provide complete applications that encompass a huge range of virtual advertising and marketing additives, which includes search engine optimization, virtual communication advertising, pay-per-click on marketing, content material advertising, internet analytics, and greater. These university courses are designed for students who possess a comprehensive understanding of virtual marketing strategies and attributes.Safalta Digital Marketing Institute in Noida is a first choice for young individuals or students who are looking to start their careers in the field of digital advertising. The institute gives specialized courses designed and certification.
for beginners, providing thorough training in areas such as SEO, digital communication marketing, and PPC training in Noida. After finishing the program, students receive the certifications recognised by top different universitie, setting a strong foundation for a successful career in digital marketing.
1. MRI Physics 101
Prof. Sairam Geethanath, Ph.D.
Medical Imaging Research Centre
Dayananda Sagar Institutions
1st October 2016
A"enua'on (E/E0)
(µV)
γ2G2δ2(∆- δ/3) (109 sm-2)
3. Outline
• High school physics – relevant to MRI
• Overview of the MRI system
• Precession and the Pelton Wheel
• Relaxa'on 'mes: T1 and T2
• Basis for contrast genera'on
• Spin Echo sequence: An example of image genera'on
• Spa'al localiza'on through magne'c field gradient
• k-space and its traversal
• Tools to get started
• Pulseq - Acquisi'on
• GPI - Reconstruc'on
• DIY assignments
MIRC 3
8. • The application of an RF pulse, causes alignment of spins away from the longitudinal axis (lower energy state) on a
transverse plane (higher energy state)
• Spins release the absorbed energy and drop back to their lower energy states
• Spin can exchange a quantum of energy with the lattice (also precessing at same frequency)
• Spin transitions from 𝑚=−1/2 (excited state) to 𝑚=1/2 (ground state) is accompanied by a transition
upwards in energy from some lower lattice state to a higher lattice state h
• Energy transition must be equal ‘ law of conservation of energy’
• Transfer of energy occurs through collisions, rotations, or electromagnetic interactions with the surrounding lattice
• This energy loss is unrecoverable and represents the transfer of heat.
h"p://mriques'ons.com
Magne'c resonance imaging: Physical principles and sequence design
𝑚=−1/2
𝑚=1/2
ℎ
𝑙
𝑝𝑟𝑜𝑡𝑜𝑛 𝑙𝑎𝑡𝑡𝑖𝑐𝑒
Boltzmann equa'on for
popula'on states
T1 relaxation
9. • The electromagnetic field from a particle can be considered to emanate
from an idealized tiny bar magnet with north and south poles ("dipole") .
• A dipole-dipole interaction is a "through space" interaction of the
fields from two spinning particles
• Four major factors determine the strength of the dipolar interaction: (1)
types of spins; (2) the distance between them; (3) the angle between
them; and (4) their relative motion.
h"p://mriques'ons.com/dipole-dipole-interac'ons.html
T1 of water
T1 of water doped with
Copper Sulphate
T1 of oil
Dipole – dipole interactions
14. • Sampling commences at the centre of the echo
• Delay between the 180°pulse and the first sampled data point is TΕ
• TΕ must be chosen to be long enough
- to view the en're echo
- to allow for the complete relaxa'on of the signal excited
T2 Measurement:
• Measured using a succession of spin-echo experiments with incrementally longer echo 'mes
• The plot of echo amplitude as a func'on of echo 'me will be an exponen'al decay with a characteris'c decay
'me constant, T2
• The echo amplitude is given by,
where E - amplitude of an echo acquired with TΕ
E0 - echo amplitude in the absence of a T2 decay
31. Prof. Sairam Geethanath, Ph.D.
Medical Imaging Research Centre
Dayananda Sagar Institutions
1st October 2016
32. ¡ Head
¡ Tumors, aneurysms, bleeding in the brain,
¡ Nerve injury, damage caused by stroke.
¡ Spine
¡ Discs and nerves of the spine for conditions such
as spinal stenosis, disc bulges, and spinal tumors.
¡ Chest : Heart, the valves, and coronary blood vessels
¡ Blood vessels and ?low – Dr. Ramesh Venkatesan’s talk
¡ Abdomen and pelvis
¡ Belly, liver, gallbladder, pancreas, kidneys, and bladder
¡ Bones and joints
¡ Arthritis, problems with joints ,bone marrow problems,
¡ Bone tumors, cartilage problems,
¡ Torn ligaments or tendons, infection.
35. Result Interpretation
Quantitative analysis
Segmentation
Feature Extraction
Visualization
(may include generating FA,ADC, Tractograpghy)
Processing
(may include DWI enhancement using Super resolution techniques )
Preprocessing
(may include registration,skull stripping,normalization motion , denoisng of low field MR
image/DWI)
36. ¡ Dark regions – water diffusing slower,
more obstacles to movement OR
increased viscosity
¡ Bright regions – water diffusing faster
DWI
¡ Bright regions – decreased water diffusion
¡ Dark regions – increased water diffusion
Figure Source: www.radiopaedia.org
ADC
Matlab Code available with Arush, MIRC
37. COLOUR FA MAP TRACTOGRAPHY
• According to the principal direction
of diffusion, colour coding of the
diffusion data is done
• Red - transverse axis (x-axis)
• Blue – superior-inferior (z –axis)
• Green – anterior-posterior axis (y-
axis)
• Intensity of the colour is
proportional to the fractional
anisotropy
• It is 3D modeling technique used to
visually represent neural tracts
using data collected by diffusion
tensor imaging (DTI)
• Voxels are connected based upon
similarities in the maximum
diffusion direction.
Figure Source: www.radiopaedia.org
Matlab Code available with Arush, MIRC
38. ADC map computa'on
b=0 b=100 b=200 b=500 b=1000
Signal intensity decreasing with increase
in b-value ADC map scanner ADC map matlab
41. Figure source: Nucifora et al. Radiology 245:2 (2007)
Corticospinal Tracts -ProbabilisticCorticospinal Tracts - Streamline
1.Streamline tractography
• Connects neighbouring voxels
from user defined voxels (seed
regions)
• Tracts are traced until
termination criteria are met.
2.Probabilistic tractography
• Value of each voxel in the map is the
probability the voxel which is in the
diffusion path between the ROIs.
• It provides quantitative probability of
connection at each voxel
• Allows tracking into regions where there is
low anisotropy.
42. Degree of anisotropy Streamline tractography
Probabilistic tractography
Figure source :Nucifora et al. Radiology 245:2 (2007)
43. • It has been well established that magne'c resonance
imaging (MRI) provides cri'cal informa'on about
cancer [3]
• Magne'c resonance spectroscopic imaging (MRSI)
furthers this capability by providing informa'on
about the presence of certain ‘metabolites’ which
are known to be important prognos'c markers of
cancer [4] (stroke, AD, energy metabolism, TCA
cycle)
• MRSI provides informa'on about the spa'al
distribu'on of these metabolites, hence enabling
metabolic imaging
[3] Huk WJ et al., Neurosurgical Review 7(4) 1984;
[4] Preul MC et al., Nat. Med. 2(3) 1996;
Metabolic imaging: applica'ons
CANCER
NORMAL
[5] H Kugel et al., Radiology 183 June 1992 MIRC 43
[5]
44. • 3D- PRESS makes it possible to localize the signal in the voxel formed by the intersection of the three
slices
Figure 7: Display of the volume of interest (voxel) located at the intersec8on of the slices
[3]*
47. • Long acquisi'on 'mes for MRSI
• A typical MRSI protocol (32 X 32 X 512) takes ~ 10-12 minutes
• Difficult to maintain anatomical posture for long 'me
• Increases pa'ent discomfort, likelihood of early termina'on of
study
• Discourages rou'ne clinical use of this powerful MRI technique
• To increase throughput (decreased scanner 'me, technician
'me)
• Reduc'on of acquisi'on 'me is usually accomplished by
under-sampling measured data (k-space)
• Limita'ons of Shannon-Nyquist criterion
• Compressed sensing provides a framework to achieve sub-
Nyquist sampling rates with good data fidelity
CS-MRSI: Need for accelera'on
MIRC 47
kx
ky
x
y
3D FT
48. Brain - normal
(N=6)
Brain - cancer
(N=2)
Prostate -cancer
(N=2)
MRSI data Scanner TR(ms) TE(ms) # Averages Grid Size FOV (mm3)
Brain - normal
(N=6)
Siemens 3.0T
Trio Tim
1700 270 4 16 x 16 x 1024 100 x 100 x 15
Brain cancer
(N=2)
Philips 3.0T Achieva 1000
112
112
2
2
18 x 21 x 1024
19 x 22 x 1024
180 x 210 x15
190 x 220 x 15
Prostate cancer
(N=2)
Philips 3.0T Achieva
1200
1000
140
140
1
1
14 x 10 x 1024
16 x 12 x 1024
25 x 50 x 33
20 x 51 x 26
In silico and in vitro phantom studies reported in [6] Geethanath et. al., SPIE Medical Imaging 2010
[7] Geethanath et al., Radiology. 2012
MRSI: acquisi'on parameters
MIRC 48
[7]
49. Applica'on of CS to MRSI
MIRC 49
• Signal model of a free-induc'on decay with N (3 in this case) metabolites
• The sparsely measured Fourier data is represented by y, Object to be es'mated is in
(x, y, f) space is m
• Undersampling in x-y dimensions vs x-f dimension
• Problem defini'on:
• Find the sparsest transform coefficients of m that provides for data consistency between Fourier
coefficients measured and es'mated, at sampled loca'ons
(2)
argminm∥Fu(m)-y∥2
2+λ∥ψ(m)∥1
(3)
(1)
50. Processing So=wares:
[1] jMRUI:
It is a software that can be used to process MRSI data.
The spectra are typically subjected to the following processing steps in jMRUI [5]:
(a) Apodization to remove existing truncation artifacts,
(b) baseline correction,
(c) time-domain Hankel-Lanczos singular value
decomposition filtering of residual water and fat peaks,
(d) Phase Correction,
(e) Frequency Shift.
5*
51. [2] VeSPA:
It is a open source software for MRS applications. It supports four applications:
1. RFPulse (for RF pulse design),
2. Simulation (for spectral simulation),
3. Priorset (for creating simulated MR spectroscopic data)
4. Analysis (for spectral data processing and analysis)
6*
Cr2
3.916
Cho
3.186
Cr
3.03
NAA
2.008
Lipids
0.9-1.4
Gln, Glu, GABA
2.12-2.42
Figure 8: Spectra simulated using VeSPA soVware with major metabolites of brain
54. Brain - cancer
Prostate - cancer
Brain - Normal
Brain - Normal
Brain - cancer
Prostate - cancer
CS-MRSI: Metabolite maps
MIRC 54
[7] Geethanath et al., Radiology. 2012
55. Limita'ons of PRESS
• Conventional slice-selective 180 refocusing pulses do not have particularly good slice profiles, leading to
non-uniform metabolite excitation and signal generation from outside PRESS box
• By definition, it restricts excitation to a rectangular volume, but brain has a curved, elliptical shape –
difficult to obtain signal from cortical regions close to the skull
• 3DPRESS-MRSI sequence - scan-time becomes very long if high spatial resolution in all three directions
is required (number of PE gradients to be recorded becomes very high since encoding is performed in all
three directions, hence giving long scan times)
• Difficulty of obtaining sufficient magnetic field homogeneity for large spatial coverages
[4]*
56. Schizophrenia:
- In a study [7], it is shown that using proton MRSI, in case of patients with schizophrenia, there will be a
relative loss of signal from N-acetyl- containing compounds (NAA)
- Patients with schizophrenia, when compared as a group to normal controls, show a consistent 1H-MRSI
pattern of group differences, i.e., bilateral reductions of NAA/CRE and NAA/CHO in HIPPO and DLPFC;
- 1H-MRSI data in both patients and controls do not show significant changes over a period of 90 days;
however, absolute metabolite ratios in individuals show low predictability over this time interval;
- 1H-MRSI data show relatively low variability (as measured by the coefficients of variation (CVs)) both in
patients and normal controls, especially for NAA/ CRE and CHO/CRE.
7*
57. Mild Cogni've Impairment:
- Mild cognitive impairment (MCI) is a clinical state between normal aging and Alzheimer's disease (AD)
- In a study [8], 1H-MRS findings were compared in the superior temporal lobe, posterior cingulate gyri
and medial occipital lobe among 21 patients with MCI, 21 patients with probable AD, and 63 elderly
controls
- Results showed that, NAA /Cr ratios were significantly lower in AD patients compared to both MCI and
normal control subjects in the left superior temporal and the posterior cingulate VOI
- Myoinositol (MI) /Cr ratios measured from the posterior cingulate VOI were significantly higher in both
MCI and AD patients than controls
- Cho /Cr ratios measured from the posterior cingulate VOI were higher in AD patients compared to both
MCI and control subjects
8*
58. • Increased informa'on content but at cost of increased acquisi'on 'me
• Provides richer insight into the pathophysiology and direct impact on therapeu'c
design
• Mul'ple open-source tools available – jMRUI and Vespa
• Increased clinical research in neuro-,breast, prostate, cardiac (murine) and liver
• Ac've area of research – development of PSD and recon
Summary
MIRC 58
59. References
[1] Nishimura, Dwight George. Principles of magnetic resonance imaging. Stanford University, 1996.
[2] SG Dissertation
[3] Theoretical background: MRI and MRS
[4] Peter B. Barker et al., “In vivo proton MR spectroscopy of the human brain”, Progress in Nuclear Magnetic
Resonance Spectroscopy 49 (2006) 99–128
[5] A. Naressi, et al. Java-based graphical user interface for MRUI, a software package for quantitation of in vivo/medical
magnetic resonance spectroscopy signals. Computers in Biology and Medicine, 31(4), 269-286 (2001)
[6] https://scion.duhs.duke.edu/vespa/
[7] Alessandro Bertolino et al., “Reproducibility of Proton Magnetic Resonance Spectroscopic Imaging in Patients with
Schizophrenia”, Neuropsychopharmacology 1998
[8] K. Kantarci et al., “Regional Metabolic Patterns In Mild Cognitive Impairment And Alzheimer's Disease A 1h Mrs
Study”, Neurology. 2000
60. Acknowledgement
• People
§ Prof. Vikram D. Kodibagkar
§ Prof. Joseph V. Hajnal
§ Colleagues at UT Southwestern
§ Colleagues at ICL
§ Students at MIRC & radiologists at
Sagar Hospital
§ Collaborators from
§ UMN
§ Oxford
§ GE Healthcare (Dr. Ramesh Venkatesan)
§ ASU
§ IISc
§ NIMHANS
§ Philips Healthcare
• Funding
§ Pilot grant (PI: Kodibagkar) from
UL1RR024982, (PI: Milton Packer)
§ ARP#010019-0056-2007 (PI: Kodibagkar)
§ R21CA132096-01A1 (PI: Kodibagkar)
§ W81XWH-05-1-0223 (PI: Kodibagkar)
§ R21 CA139688 (PI: Corum)
§ S10 RR023730 (PI: Garwood)
§ P41 RR008079 (PI: Garwood)
§ MRI India Na'onal Mission grant – SCANERA
(co-PI: Geethanath) from DEITY
§ DST-TSD grant and Wipro GE Healthcare
(PI: Geethanath)
§ KFIST grant (PI: Geethanath)
MIRC 60