neurosciences, inc with...cm h2o) pushes technology limits other challenges: cost, regulatory most...

Barry Lutz Ph DBarry Lutz, Ph.D.Research Assistant ProfessorDepartment of BioengineeringUniversity of Washington

Samuel R. Browd, M.D., Ph.D.Assistant Professor of Neurological SurgeryDepartment of Neurological SurgeryDepartment of Neurological SurgeryUniversity of WashingtonAttending Pediatric NeurosurgeonSeattle Children’s Hospital

Disclaimer: co‐founder of Aqueduct Neurosciences, Inc with q ,Sam Browd and Tom Clement (developing a smart shunt)

Shunt history: 50 years in 5 minutes

today

1950sSilicone1-way differential

y

pressure valves(Hakim, Pudenz,Heyer-Schulte)

Dates derived from “The scientific history of hydrocephalus and its treatment.” Aschoff, Kremer, Hashemi, Kunze. Neurosurg. Reviews (1999).


today


1970sSiphon control(ASD, SCD, gravity)

y


Some adjustable designs (Portnoy,Hakim)



today

1980sProgrammable(Medos-Hakim)

y



Flow control valve (OSV)


Some adjustable designs (Portnoy, Hakim)



1980sProgrammable(Medos-Hakim)

1990s onwardModest changesMany clone devices



Flow control valve (OSV)


Some adjustable designs (Portnoy,Hakim)


Limited options for type of controll d d ff l lNearly every device is differential pressure valve

Siphon‐control (add‐on or integrated)Adjustable pressure set point (from all majors)Adjustable pressure set point (from all majors)A few flow control valves (OSV, Diamond)

E t di f il tExtraordinary failure rates40% by year 1, 50% by year 2, 98% by year 10Obstruction is key cause: proximal (60%) valve (30%)Obstruction is key cause: proximal (60%), valve (30%)

No sensors, no reliable failure diagnostics, no it i bilitmonitoring capability

What can we do to really advance the status quo?status quo?

Methods/designs that reduce obstruction & in vitro biological models to test them

Diagnostics for shunt failure & monitoring g g

Smart Shunts for advanced control and diagnostics & bench models to test them diagnostics & bench models to test them (dynamic models)

I d d di f h d i bl Improved understanding of the desirable control approaches (and devices to carry h )them out)

Shunt obstruction

Proximal catheter obstructionCatheter geometryAnti‐fouling coatingsActive methods to fight in‐growth

How do we test new methods?

Proximal obstruction: geometry

Early efforts (from The Shunt Book!)

Proximal obstruction: geometry

Tissue in‐growth may favor distal holesWhat effect does hole size have on flow?

Proximal obstruction: coatings

Promising priority area, no clear winners yetPromising priority area, no clear winners yet

Filter added to proximal catheter

NJ Institute of TechnologyFilter added to catheterGroup has large NIH grant for related work

Proximal obstruction: active method

Jack Judy, UCLAMicroelectromechanical(MEMS) “flappers” in catheter holes break tissue growthActivated by external magnetic field

US Patent Disclosure‚ Self-Clearing Catheter for Clinical Implantation (2004)

Proximal obstruction: testing

Pat McAllister, Carolyn HarrisFlow‐based cell culture system for testing proximal catheter obstruction (& valves too)

“Mechanical contribution to astrocyte adhesion using a novel in vitro model of catheter obstruction.” Harris, Resau, Hudson, West, Moon, McAllister. Exptl Neurology (2010).

Obstruction: status and needs

Proximal catheter obstruction (60%)l bCoatings: no proven solutions yet, but promising

Active methods: intriguing but research stageBetter CSF control may reduce failure (OSV)Better CSF control may reduce failure (OSV)

Valve obstruction (30%)P ibl i i h l d i l fl Possible issues with valve designs: complex flow path, small gaps, CSF contacts intricate partsLittle‐to‐no activity to reduce valve obstructionLittle‐to‐no activity to reduce valve obstruction

Need in vitro biological models to evaluate b t ti ti th dnew obstruction‐prevention methods

Shunt failure diagnostics

Common components:Sensors (pressure or flow)Some source of power (wireless or battery)

Option #1. External reader & transmitted power: on‐demand measurement (clinic, home)power: on demand measurement (clinic, home)

Option #2. Implant with battery: potential for continuous monitoring to identify problems continuous monitoring to identify problems before they occur (and generate useful data)

Reader‐based flow diagnostics

NeuroDx ShuntCheck with MicropumperFlow sensor based on classic “ice cube” testOver‐skin sensor (no implanted parts)multiple NIH SBIRs, some clinical testing


Transonic SystemsUltrasonic flow detection (CSF flow is near detection limit for this technology)External reader &

dtransmitted power Several clinical

ltrials, outcome?


New Jersey Institute of Technology (w/ Infoscitex)Large NIH

f fgrant for flow sensor and

lproximal catheter filter

h TMSmartShuntTM

Sensorized Shunt Concept

Alfred Mann Foundation pressure sensors

Current Technology

Intermediate Goal

Final GoalTechnology Goal

20

Pressure Sensor Requirements

AMF minimum sensor requirements demonstratedq

Range: 680 to 1220 cm H2O absolute (‐350 to +200 cm H2O gauge)cm H2O gauge)Accuracy: ±2.7 cm H2O Resolution: 0.27 cm H2OLow current RF coupled power systemPackage‐capable for long‐term implantationR li bl tReliable pressure measurementFunctional lifetime: at least 1 year

21

Reader‐based pressure diagnostics

Many active developers, including majors

External‐power (no battery)On‐demand measurements

Meithke

On demand measurementsMeithke SensorReservior (left)RadionicsTelesensorMedtronic InSiteCodman (2009 patent)H‐cubed (development stage?)Issys (development stage?)Alfred Mann FoundationAlfred Mann Foundation

Diagnostics: status of systems

High value, lots of activity (including majors)Potential payoff: cost savings for averted diagnostic procedures ($1.3B/year???)Sensor challenges: required accuracy (mL/hr, cm H2O) pushes technology limits Other challenges: cost, regulatoryMost require external power (MRI issues?)

l d l lLittle activity on stand‐alone implantsEarly detection, potential use in a smart shunt B t t b t d l ith But, must be stand‐alone with power source

“Smart” Shunts – the common vision

Sensors (flow or pressure)Pump or valveElectronicsImplanted power (battery)Control algorithm

hMeasure thingsChange pump/valve setting

Two way communications Two‐way communications (diagnostics, intervention)

Anticipated for decades. Why don’t we have one yet?

Smart Shunts: Codman & Shurtleff

Based on adjustable Codman‐Hakim valveSmart actuator on adjustment cam

actuator

Smart Shunts: Medtronic

Positive displacement pump (e.g. drug pump)Timed pump program or P‐sensor controlled

Smart Shunts: Integra Lifesciences

Regulation based on transient component of ICP as a measure of brain compliance

Smart Shunts: Meithke valve

Meithke valve mechanism (on‐off switch)Drainage via on‐off valve scheduleAl‐Nuaimy group developing algorithmsMeithke patent (2005) Al-Nuaimy group (Univ. of Liverpool)

Smart Shunts: tube squeezer

Tube squeezer with feedback controlAachen University (Leonhardt) simulated control dynamics

“Simulation of….future electromechanical valves….” Leonhardt group (2012)

Early models of the CSF system

Early models: static single‐compartment Bench testing of shunts follows similar “plumbing” approach

Maramou electrical modelHakim physical model

Advanced models of CSF dynamics

Dynamic models needed to test smart shuntse.g., R. Penn (left), A. Linninger, Dr. Bradley ETH Zurich SmartShunt project (right)

Penn group

Smart shunts: challenges & payoff

Remaining challenges/needsh ff flSensors with sufficient accuracy (pressure, flow)

Power consumption (lifetime 5+ years?)Size MRI compatibilitySize, MRI compatibilityCost (viable under existing reimbursement?)Regulatory (what is acceptable testing?)egu ato y ( at s acceptab e test g )

Potential payoffDiagnostics, failure detection, improved safetyDiagnostics, failure detection, improved safetyData logging, new insight into conditionOpportunity to implement sophisticated control

Summary: potential wins in next 5 years

Reducing obstruction remains a key needl h dProximal: coatings, active methods

Valve: almost no activity on this problemNeed biological models to evaluate methodsNeed biological models to evaluate methods

Shunt diagnostics & monitoringMany folks developing on‐demand diagnosticsMany folks developing on demand diagnosticsContinuous monitoring could alert before problems occur and provide patient data – does not existp p

Smart shunts (anticipated for decades)Needs: designs to defeat the power draw problem, g p p ,implantable sensors, good regulatory strategies

This just in –CSF glucose power for brain machine interface (June 2012)machine interface (June 2012)

Needs with promise in next 3‐5 years

1) Obstruction‐resistant shunts (proximal, valve) and in vitro biological models to test themvitro biological models to test them

2) Fully‐implanted battery‐powered sensors for shunt failure diagnostics (& monitoring to generate better data)

3) Improved understanding of desirable algorithms for CSF d iCSF drainage

4) Smart shunts with diagnostics, advanced control, and maintenance and bench models to test themmaintenance and bench models to test them

5) Funding for collaborations between clinicians, scientists, and engineers (program, center), g (p g , )

Questions1) What CSF control methods are needed that we don’t

have today (pressure, flow, combination, time have today (pressure, flow, combination, time variable, shunt weaning)?

2) What are the arguments for and against anti‐siphoning in a differential pressure shunt?

3) What are the key needs of different patient l i ( di i d l NPH)?populations (pediatric, adult, NPH)?

4) For implanted electrical systems (diagnostics, smart shunts) is there an acceptable battery replacement shunts), is there an acceptable battery replacement model by elective surgery (e.g., pacemaker) ?

5) What testing threshold is needed (bench, animal, 5) g ( , ,human) to reach a comfort level for clinician adoption (for implantable diagnostics, smart shunts)?

neurosciences, inc with...cm h2o) pushes technology limits other challenges: cost, regulatory most...

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