Imaging Potential

Professor Sue Francis Sir Peter Mansfield Imaging Centre University of Nottingham Cardiovascular, Metabolic and Kidney disease

 Patients with kidney disease are at marked increased risk of cardiovascular disease including stroke, as well as diabetes and metabolic disease. The same is true in reverse.

Kidney disease

cardiovascular

Stroke

diabetes Obesity  Diseases across organ systems often co-exist due to shared risk-factors.  Inflammation and/or fibrosis are common to many organ systems. Outline

• What can imaging provide?

• Quantitative imaging for assessment of mechanistic factors: inflammation and fibrosis

• Imaging in kidney, heart, brain, and skeletal muscle and adipose tissue: ’routine’ and ’advanced’ methods

• Examples of imaging in common disease pathways

• Using existing infrastructure such as UK Biobank Potential of imaging to underpin multimorbidity studies

• Magnetic Resonance Imaging (MRI) allows the recording of highly resolved 3D data sets across the multiple organs in a single MR scan - move away from one-disease, one mechanism approach. • MRI and MRS non-invasively provide insight into anatomy and tissue distribution in the human (and animal) body and allow quantitative analysis of tissue composition. Skeletal muscle Renal imaging Brain imaging and adipose tissue Cardiac imaging What can MRI tell us? Quantitative MRI

Anatomical 1H imaging and MRS Relaxation • Volume • Cortical • T1 Thickness • T2*

Motion Tissue Characterisation • Blood Flow • Perfusion • Diffusion • Fat Percentage • Strain • Stiffness

Voxelwise mapping Quantitative MRI to measure fibrotic changes .. in the kidney

Healthy kidney Fibrotic kidney T1 mapping Fibrosis

T1 mapping

DWI/DTI DWI

ASL perfusion

Elastography ASL perfusion

Healthy tubules Dilated, atrophic tubules Preserved capillary density Reduced capillary density Minimal interstitial extracellular matrix Increased interstitial extracellular matrix Minimal matrix cross-linking Increased matrix cross-linking

 Decrease water mobility, altering T1 relaxation time and impairing water diffusion (DWI)  Disrupt the ordered structure of the renal parenchyma (DTI)  Capillary loss and impaired microvascular perfusion, altering ASL perfusion  Increased extracellular matrix and cross-linking, increases kidney stiffness (MR Elastography). T1 mapping to measure fibrosis

• MR signals (T1 relaxation time) from protons change when protons interact with membranes.

 T1 increases with fibrosis/inflammation.

normal

fibrosis Healthy volunteer CKD patient Reduced corticomedullary differentiation in CKD patients inflammation

Time of AKI 3 months post AKI Diffusion Imaging

• Diffusion weighted imaging (DWI) reflects amount of hindrance/restriction experienced by water molecules.

• Diffusion tensor imaging (DTI) measures water mobility in a specific direction. Disruption of ordered Random Brownian motion of water molecules movement (e.g. in tubules) can be detected.

Renal DTI map FA quantifies diffusion with a preferred direction. FA higher in medulla than cortex, indicating the medulla tends to have a preferential direction. Arterial Spin Labelling (ASL) perfusion

• Fibrosis is associated with capillary loss and impaired microvascular perfusion.

 Decreased ASL perfusion in CKD may be a surrogate measure of whole-kidney

fibrotic burden and predict progression risk. Perfusion Perfusion (ml/100g/min)

Renal ASL perfusion Cardiac ASL perfusion No gadolinium required Brain ASL perfusion • Reduced microvascular blood flow results in diminished oxygen delivery to tubular epithelial cells, leading to apoptosis, inflammation, and release of profibrotic stimuli that further drives fibrogenesis in a positive feedback loop. T 1 c o r te x T 1 c o r te x T 1 m e d u llTa1 m e d u lla T 1 C M d iffTe1r eCnMti adtifofne re n tia tio n P e rfu s io nP e rfu s io n

1 8 0 0 1 8 0 0 2 0 0 0 2 0 0 0 5 0 0 5 0 0 3 0 0 3 0 0

)

)

n

n

i

i

m

)

m

) )

1 9 0 0 4 0 0 /

)

) /

1 9 0 0 ) 4 0 0

s

s

s

g

s

s

s

g

0

m

0

m

m m

1 6 0 0 ( m

m 2 0 0

0

( (

1 6 0 0 (

2 0 0

0

(

(

1

f a

1 8 0 0 3 0 0 1

/

f

x

a f

1 8 0 0 l 3 0 0

/

l

x

f

l

i

l

l

e

i

l

e

t

d

u

m

t

d

u

r

m

(

r

d

(

d

o

M

e

o n

1 7 0 0 M 2 0 0 e

1 7 0 0 2 0 0 n

C

C

C

o

M

1 4 0 0 C

1 0 0

o

M i

1 4 0 0

1 0 0

i

1

1

1

s

1

1

s

1

T

T

T

u

T

T

u T 1 6 0 0 1 0 0 f

1 6 0 0 1 0 0 f

r

r

e

e P 1 2 0 0 P 1 2 0 0 1 5 0 0 1 5 0 0 0 0 Linking0 0 renal fibrosis to MRI: Reducing the need for biopsy C K D H E A L T H Y C K D H E A L T H Y C K D C K HD E A L T H Y H E A L T H Y C K D C K HD E A L T H Y H E A L T H Y C K D C K HD E A L T H Y H E A L T H Y

T1 mapping MRI related to %fibrosis on biopsy

T 1 c o r te x T 1 cTo1 r mteexd u lla T T1 1C mM e ddiufflelare n tia tio n T 1 C M d iffePre nrftuiastiioonn P e rfu s io n T 1 c o r te x T 1 m e d u lla T 1 C M d iffe re n tia tio n P e rfu s io n

1 8 0 0 1 8 0 02 0 0 0 2 0 0 0 5 0 0 5 0 0 3 0 0 3 0 0 )

1 8 0 0 2 0 0 0 5 0 0 ) 3 0 0

)

n

n

i

i

n

i

m

)

m

) )

1 9 0 0 4 0 0 /

)

)

) /

1 9 0 0 4 0 0 m

)

s

)

)

/ s

s 1 9 0 0 4 0 0

g

s

s

s

g

s

s

s

g

0

m

0

m

m m

1 6 0 0 (

0 2 0 0

m

m

0

m

( (

1 6 0 0 (

m

m 2 0 0

0

(

(

1 6 0 0 (

2 0 0

0

(

(

1

f

a

1 8 0 0 3 0 0

1

/

x

f

1

f l

a 1 8 0 0 3 0 0

f

l

/ a

x 1 8 0 0 3 0 0

/

i

f

l

l

x

f

l

l

e

l

i

l

i

l

e

t

e

d

u

m

t

d

t

u

r

d

u

m

(

m

d

r

r

(

(

d

o

d

M

e

o o

1 7 0 0 2 0 0 n

M

M

e

e n

1 7 0 0 1 7 0 0 2 0 0 2 0 0 n

C

C

o

C M

C 1 4 0 0

C

C 1 0 0

i

o

o

M

1 4 0 0 1 4 0 0 M

1 0 0 1 0 0

i

1

i

1

s

1

1

1

1

1

s

1

s

T

1

T

T

u

T

T

T

u

T

T

f u

T 1 6 0 0 1 0 0

1 6 0 0 1 0 0 f f

1 6 0 0 1 0 0 r

r

r

e

e

e

P P 1 2 0 0 1 2 0 0 1 5 0 0 P 0 0 1 2 0 0 1 5 0 0 1 5 0 0 0 0 0 0 C K D HCEKADL T H Y H E A L T H Y C K D H E A L T H Y C K D H E A L T H Y C K D H E A L T H Y C K D H E A L T H Y C K D H E A L T H Y C K D H E A L T HCYK D H E A L T H Y C K D H E A L T H Y C K D H E A L T H Y C K D H E A L T H Y DWI

K id n e y v oKluidmnee y v o lu m e R ig h t R e nRa li gAhrtt eRrey n Fallo Awrte ry F lo w A D C c o rteAxD C c o rte x A D C m e d uAlDlaC m e d u lla

6 0 0 6 0 0 1 0 1 0 3 .0 3 .0 2 .5 2 .5

)

)

)

s

)

s

s

s

m

m

/ m

8 /

m

/ 2

e 8

/

2 e

2 2 .5

2 2 .5

m

m

m

m m

4 0 0 m 

4 0 0 u



u

l

(



w

l

(



(

w 6

( o

6

o

o

o

l

a

x

V

l

a

l

f

x

V

l

f

2 .0 l 2 .0

e

2 .0 l 2 .0

e

y

t

u

y

t

A

u

r

A

e

r e

4 d R

4 d

o

n

R

o

e n

2 0 0 e d

2 0 0 C

d

i

C

m

i

m

1 .5

K

1 .5 C

K C

2 C

2 C

D

D

D

D

A

A

A A 0 0 0 0 1 .0 1 .0 1 .5 1 .5 C K D C KHDE A L T H Y H E A L T H Y C K D C K HD E A L T H Y H E A L T H Y C K D C K HD E A L T H Y H E A L T H Y C K D C K HD E A L T H Y H E A L T H Y Haemodynamics

K id n e y v o lu m e R ig h t R e n a l A rte ry F lo w A D C c o rte x A D C m e d u lla K id n e y v o lu m e R ig h t R e n a l A rte ry F lo w A D C c o rte x A D C m e d u lla

T 1 c o r te x T 1 m e d uKlildan e y v o lu m e 6 0 0 T 1 C M d ifRfeigrehnt tRiaetnioanl A rte ry F lo w 1 0 P e rfu s io n A D C c o rte x 3 .0 A D C m e d u lla 2 .5

) )

6 0 0 1 0 3 .0 s 2 .5

s )

1 8 0 0 2 0 0 0 5 0 0 3 0 0 m )

6 0 0 1 0 3 .0 2 .5 /

m s

) 8

/

2

e

)

s 2

n 2 .5

)

m

s

i

m

m

/ m

s 8

m

/ 2

4 0 0 e



u

m

m

)

2

l (

 2 .5

)

) /

1 9 0 0 4 0 0 /

m

w

8 6 (

m

/

s

m

2

o

e

s

s

g

o m

2 2 .5

4 0 0 l

a



u

x

V

0

l

f

m

l

(

m



m

m

m

l

w 2 .0 2 .0

1 6 0 0 (

e ( 2 0 0 m

0 6

(

(

y

4 0 0 o



t

u

u

o

A

l

(

1



r

l

f

a

e a

1 8 0 0 3 0 0 w

x

V

/

(

x d

4 l

f f

l 6

l

R

o

o

l

i 2 .0 2 .0

n

l

o

e

e

e

l

y a

2 0 0 t

x

V

t

u

d

d

u

C

A

l

f

m

i

r

r

e

2 .0 l 2 .0

m

(

e d

d 4

y R

t 1 .5

o

K

n

o

u

C

A

M

e

e

r e 1 7 0 0 2 0 0 n

2 0 0 2 C

d d

4 C

C

D

R

i

C

o

n

o

M

1 4 0 0 m

D

1 0 0 e

i

2 0 0 A 1 .5

1

K

d

C

C

1

A

s

1

i

C

2 m

T

T

D u

T 1 .5

K

C f

1 6 0 0 0 1 0 0 0 1 .0 1 .5 D

C A

2 r

D A

C K D H E A L T H Y e C K D H E A L T H Y C K D H E A L T H Y C K D H E A L T H Y

D A

0 P 0 1 .0 1 .5 1 2 0 0 A 1 5 0 0 0 0 0 C K D H E A L T H Y 0 1 .0 C K D H E A L T H Y 1 .5 C K D H E A L T H Y C K D H E A L T H Y C K D H E A L T H Y C K D H E A L T H Y C K D H E A L T H Y C K D H E A L T H Y C K D H E A L T H Y C K D H E A L T H Y C K D H E A L T H Y C K D H E A L T H Y Multiparametric MRI in renal disease Quantitative assessment of structural and functional changes in CKD using multiparametric renal MRI and the association with biochemical and histological measures. Buchanan, Mahmoud, Cox, McCulloch, Prestwich, Taal, Selby, Francis, Nephrology Dialysis Transplantation, in press.

K id n e y v o lu m e R ig h t R e n a l A rte ry F lo w A D C c o rte x A D C m e d u lla

6 0 0 1 0 3 .0 2 .5

)

)

s

s

m /

8 m

/

2 e

2 2 .5

m m

4 0 0 m



u

l

(



w

6 (

o

o

l

a

x

V

l

f

2 .0 l 2 .0

e

y

t

u

A

r e

4 d

R

o n

2 0 0 e

d

C

i

m

1 .5

K C

2 C

D

D

A A 0 0 1 .0 1 .5 C K D H E A L T H Y C K D H E A L T H Y C K D H E A L T H Y C K D H E A L T H Y UKRIN-MAPS (MRI Acquisition and Processing Standardisation)

Sharing of expertise and building capacity in renal MRI

• Development of a harmonized approaches in renal MRI across 1.5 and 3 T and MR vendors – GE, Philips, Siemens. • Large data set in healthy subjects • Data sharing and data analysis methods • Acceleration of new technological advances and realising the X13 UK sites clinical potential of renal MRI - linking with MR vendors

 To provide imaging methods to determine cause and prognosis of kidney disease for improved stratification of patients, improved patient care, and better assess targeting of current and novel treatments. UK Renal Imaging Network (UKRIN): Enabling clinical translation of functional MRI for kidney disease, MRC Partnership, Sept 2018 – Sept 2021. £795,786 Cardiac Imaging

• EDV, ESV, SV, EF, LV mass. • Aortic flow • Strain measures • Native T1 mapping Brain Imaging

Macro- and micro-structural changes in the brain. Perfusion (ml/100g/min)

T1 mapping: quantitative assessment of myelination Perfusion and angiography Angiography and MR perfusion

Resting state activity assessed by functional MRI Studying muscle architecture and metabolism

Adipose tissue:

IMCL/EMCL

e

n 200

i l Pi

e

s

a PCr

B

o

t 150 Pi/PCr

e

v

i

t

a

l

e

R 100

l

a

n

g

i

S 50

%

8 0 0 0 0 0 2 4 6 8 0 2 2 4 2

2 0 4 2 0 4 1 4 1 4 2 5 3 0 5

: : : : : : : : : : : : : : :

1 2 2 3 4 4 5 5 6 6 7 7 8 9 9

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

1H MRS: fatty acids inside 31P MRS: mitochondrial function from myocytes (IMCL). recovery of PCr after exercise. Cardiac MRI and renal MRI in renal patients CAMRID: Assessing cardiovascular function during dialysis

First study of intradialytic MRI to directly assess the cardiovascular effects at baseline AND during dialysis.

• Do changes occur in cardiac structure, function and perfusion during dialysis ?

• Is haemodiafiltration (HDF) relatively cardio-protective compared to haemodialysis (HD)?

Stunning of myocardium Brain imaging in End Stage Renal Disease (ESRD)

T2 FLAIR MRI demonstrating progression of white matter hyperintensities (WMH) over 1 year in a patient on haemodialysis. These changes were not significant in the transplant cohort. Haemodialysis Interventions to Reduce Multi-Organ Dysfunction (HD-REMODEL)

Examining multi-organ changes in dialysis

0 1 2 4 5 hours Brain: Comparison of standard dialysis with cooled dialysis Perfusion, Flow Resting state -fMRI, DTI Structural measures

Kidney: Perfusion, Flow, T1, DWI, UK Biobank

Brain Muscle/ adipose

Cardiac and some renal In Summary

• MRI provides multi-organ imaging markers for renal disease, cardiovascular, stroke, diabetes and obesity. • Imaging has the potential to: o underpin future multi-morbidity research. o reduce the reliance on biopsies for patient benefit.

• Multi-organ imaging protocols to address disease cluster • AI methods to improve automatic detection of imaging data, and identification of patterns/trends in clusters in imaging data.

• Imaging markers can: o Support clinical trial design and delivery, to aid potential of better diagnostics to improve prognosis. UK Renal Imaging Network (UKRIN)

UK Renal Imaging Network (UKRIN) brings together major UK renal MRI research centres through membership of a national group of MR physicists, radiologists, and clinicians dedicated to developing MRI methods for the study of the kidney.

Acute Chronic End stage renal Kidney Kidney disease and Injury Disease transplantation

UKRIN-MAPS, MRC Partnership grant https://www.kidneyresearchuk.org/research/uk-renal-imaging-network rd 3 International Conference Co-organised by on Functional Renal Imaging 2019

Nottingham, UK October 15-17th www.nottingham.ac.uk/go/3rdrenalmri