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June 29, 2016 Presentation to the Interagency Working Group June 29, 2016 Presentation to the Interagency Working Group

June 29, 2016 Presentation to the Interagency Working Group - PowerPoint Presentation

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June 29, 2016 Presentation to the Interagency Working Group - PPT Presentation

John R Leyendecker MD Vice Chairman of Clinical Operations and Professor of Radiology UT Southwestern Medical Center Dallas TX Who am I I am a practicing Radiologist with 23 years experience ID: 550796

data imaging click renal imaging data renal click risk information patient medical contrast image based software treatment urologist patient

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Slide1

June 29, 2016 Presentation to the Interagency Working Group on Medical Imaging

John R. Leyendecker, M.D.Vice Chairman of Clinical OperationsandProfessor of RadiologyUT Southwestern Medical CenterDallas, TXSlide2

Who am I?

I am a practicing Radiologist with 23 years experience.Vascular and interventional radiology (USAF)Abdominal imaging and interventionUTSA, Wake Forest, UT SouthwesternMy time is spent:Clinical (30%)Educational (10%)Research (10%)Administrative (50%) I receive no federal research funding.

But I will be a patient some day!Slide3

Outline

Why focus on imaging?A tale of two patients: Present care versus future care.How do we get there from here? Slide4

Detection

Localization and severity assessment

Diagnosis

Treatment planning

Treatment

treatment response

ImagingSlide5

Precision Medicine

Cancer moonshot

Imagine fighting a war in which you…

can’t find the enemy

can’t determine the enemy’s strength

have limited means to deliver weapons to the battlefield

have no idea whether your weapons are effectiveSlide6

Image processing and enhancementFeature extraction

Noise reductionData compressionData mining/Machine learning Information systems integration and data sharingWe all share the same challengesSlide7

“What frustrates you that you wish you could change?”

A tale of two patientsSlide8

A 75 year old man has blood in his urine detected at a routine physical exam. His primary care doctor refers him to a urologist

The urologist accesses the patient’s electronic medical record to order an imaging exam.

The urologist accesses the patient’s electronic medical record to order an imaging exam.

Documentation regarding the patient’s allergy history and CKD are buried deep in the medical record and go unnoticed.

The order is placed for a contrast-enhanced CT

Cumulative

radiation

dose

Allergies

Implanted devices

Warning: This patient has had a prior severe reaction to iodinated contrast and grade 3 CKD

click here for details

Based on the information you entered and published evidence, the following imaging tests are considered appropriate and do not require pre-approval

Ultrasound of kidneys

MRI of kidneys

WHERE WE ARE NOW WHERE WE CAN BE

Systems integration and data sharing

Evidence-based decision supportSlide9

Assessment of the kidneys is performed on a high field open MRI scanner using rapid free-breathing sequences that generate a portfolio of reproducible and standardized quantitative measurements displayed as parametric maps overlaying high spatial resolution anatomic images.

The patient arrives for his CT scan. Although the scan is completed, he has a reaction to the intravenous contrast material necessitating resuscitation and an overnight admission to a nearby hospital. The prolonged hypotensive episode further worsens his renal function.

T1= 800

msec

T2 = 24

msec

R2* = 22

ADC = 0.923

Ve

= 10 mL/100mL

Vp

= 9 mL/100mL

Fat content = 0%

WHERE WE ARE NOW WHERE WE CAN BE

Technological innovation

Standardization and quantificationSlide10

Computer Assisted Functions identify and volumetrically measure a mass in the kidney.

Segmentation software estimates the risk of surgical resection based on lesion size and location (nephrometry).

The

quantitative MRI data is digitally compared to an extensive open-access national database of renal tumors, correlating the tumor’s

imaging “fingerprint”

with biomarkers associated with specific genetic mutations, biologic behavior, and molecular targets.

A mass is identified in the kidney and measured manually by the radiologist in a single axial dimension.

WHERE WE ARE NOW WHERE WE CAN BE

Data/image analysis software

Databases correlating imaging phenotypes with genomics and outcomesSlide11

WHERE WE ARE NOW WHERE WE CAN BE

Image data is integrated with information available in the patient’s portable medical database to determine a risk/benefit profile for various treatment strategies. Software surveys the rest of the image data for additional findings and lesions demonstrating a similar molecular signature. It detects a 6 mm lung nodule. Software automatically calculates a risk profile for the nodule.

Software also determines risk profile for diabetes, heart disease, and osteoporosis-related fractures

.

The busy radiologist quickly looks through the 800 acquired images for evidence of metastatic disease.

A small lung nodule is missed.

She doesn’t mention the indicators of metabolic syndrome, such as fatty liver disease, or the coronary artery calcifications, because that takes additional time and she knows the urologist won’t follow-up on those findings

Image analysis software

Seamless integration of imaging, clinical, and risk stratification dataSlide12

Lungs: normal

Liver: normalGallbladder: normalSpleen: normalPancreas: normalAdrenal glands: normalKidneys: a 2.0 cm solid enhancing mass is seen in the right kidneyBowel: normalMusculoskeletal: normalLymph nodes: normalOther: No free air, no free fluidImpression: Enhancing mass in the right kidney concerning for renal cell carcinoma.

Right renal mass

5-30-2020

1

st

follow-up

2

nd

follow-up

Location

Upper pole, right kidney

Volume

35 ml

Metastasis

#1

N/A

Metastasis

#2

N/A

Mutated genes

MET

SETD2BAP1Diabetes

ModIschemic heart diseaseModOsteoporosis-related fracture

LowNASHMod

Click here for a 3D printed modelClick here for interactive virtual resection

Name: BobNational medical record number: 33333Age: 75

Lifetime effective medical radiation dose: 23 mSvImplanted devices: noneAllergies: iodinated contrast material

Contrast administered: 8 ml brand X Complications

: noneCritical Findings

Right renal mass

99% probability of Renal Cell Carcinoma

97% probability of type I papillary typeStage T1aNephrometry score = 4p

Findings requiring follow-up

Finding

MethodInterval

6 mm pulmonary noduleChest CT6 months

Based on your patient’s risk factors, the risk of malignancy is 8%

Click here to enroll your patient in a lung nodule registry and clinicAdditional FindingsHepatic steatosis (fatty liver)Colonic diverticulosis Click here for more informationClick here for more informationClick here for more informationRisk profileClick here for more informationClick here for more informationClick here for more informationCoronal MR imageClick here to view all imagesImaging-based genomic analysisOncologic follow-upImaging features suggest a significant likelihood that mutations in the following genes are presentSlide13

Evidence-based outcomes data is combined with patient-specific data to determine

the relative risk of disease progression, complications, and

cost vis-à-vis various

treatment

strategies.

His cancer qualifies as low risk for progression. Surveillance has the highest area under risk/benefit/cost curve of all possible treatment strategies.

Based on this data, the patient chooses annual imaging surveillance.

The urologist performs a partial nephrectomy in the operating room under general anesthesia, because that’s what the urologist does for all small renal masses.

Pathology

report: Renal cell carcinoma, papillary type,

T1a.

The

patient undergoes repeat imaging every 6 months

.

The

patient’s renal

function

never fully recovers from his contrast reaction and deteriorates further after surgery, necessitating dialysis.

WHERE WE ARE NOW WHERE WE CAN BE

Outcomes data

Cost effectiveness dataSlide14

The patient is referred back to his primary doctor for follow-up of his lung nodule and for lifestyle and medical interventions for type II diabetes, mild renal insufficiency, fatty liver disease, and coronary artery disease.

The patient develops complications related to poorly controlled diabetes/metabolic syndrome and renal insufficiency and spends his final days in and out of hospitals

He dies a short time later from a heart attack.

He spends many happy years enjoying the company of his grandchildren.

WHERE WE ARE NOW WHERE WE CAN BESlide15

How do we get there from here?Slide16

STANDARDIZATION

Image acquisitionImage analysisImage reportingSlide17

Support and Encourage…

Glycosylated liposome

Core contrast

Continued technological innovation

Faster

, safer, more effective

Vendor neutral quantitative imaging

Data management and integrated information systems

Large databases

with

clinical

trials data

Machine learning and computer aided diagnostic tools

Outcomes data (also emphasizing when NOT to treat)

Contrast agents with better safety profiles and targeted ligands for diagnosis, therapy, and surveillance.

Minimally invasive

procedures

Insertion of novel imaging into therapeutic clinical

trials

Potential to accelerate clinical translationSlide18

Build a research infrastructure that fosters innovation

We can’t just invest in tools, we also need to invest in people and processes.Create the next generation of radiologist (translational) scientistsDebt, lack of time, lack of training are all barriersDevelop and encourage successful industry/investigator collaborative modelsRevamp the grants review processShould every grant be treated like an R01?Reinvigorate the R21/R33 grant?Slide19

Industry

Clinical

researchers

Basic

scientists

Translational

scientists

universities

Advocacy

groupsSlide20

Industry

Clinical

researchers

Basic

scientists

Translational

scientists

universities

Advocacy

groups

patientsSlide21

Thank you