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CiiS Lab
Johns Hopkins University
112 Hackerman Hall
3400 N. Charles Street
Baltimore, MD 21218
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Lab Director
Russell Taylor
127 Hackerman Hall
rht@jhu.edu
Last updated: February 14th, 2021 1:51AM EST
We are developing the very first skull-embedded implant that enables chronic infusion of medicine directly into the brain. Our role is to develop the Bluetooth connectivity of the implant device for real-time interaction between the device, cellular devices, and the monitoring network.
BACKGROUND
Glioblastoma Multiforme (GBM) is one of the most aggressive types of brain cancer. Currently, the diagnosis of GBM is somewhat of a death sentence for patients because of its malignancy – the median survival time is 14.6 months [1]. There are more than 18,000 new cases in the U.S. per year [2] and the recurrence rate is over 90% [3]. When a GBM is diagnosed, the patient first receives a surgery to remove as much of the tumor as possible. However, total removal is impossible, hence radiotherapy and chemotherapy are often administered to eliminate any potential remaining tumor cells [4]. Unfortunately, over 99% of promising therapies [5] are unable to reach the tumor and be effective due to the blood-brain barrier, which is a barrier that mediates communication between the peripheral and central nervous system.
Patient survival and the standard of care for GBM has been stagnant for the last three decades. Thus, getting past the blood-brain barrier has become one of the most active areas of research, and intersects with the field of neuroplastic surgery: for a skull reconstruction surgery, the collapsed part of the skull is replaced with a 3D-printed, plastic cranial implant that emulates the strength and biocompatibility of the human skull bone. There is a hollow thickness in the cranial implant very close to the brain. Hence, the idea of embedding a cranial implant in this space with functional technology to deliver therapeutics across the blood-brain barrier is of great interest. Once this platform technology is developed, this implant device can be filled with any liquid therapeutics. The target users of this implant device are currently patients with GBM, but eventually it will be applicable to patients with all kinds of neurological diseases such as Alzheimer’s and Parkinson’s.
PRIOR WORK This project has been ongoing for several years in the Center for Neuroplastic Surgery Research. Significant progress has been made in the hardware components for the implant device, such as manufacturing all parts of the device with MRI-compatible material, developing the mechanisms for the pump that delivers drugs from the reservoir through the catheters, and designing the mechanism of power supply for the pumps. A sketch of one of the prototype designs is shown below. Now that a prototype has been developed, it will be implanted in a swine study in March 2021. The pump will not be turned on because the purpose of this initial study is to evaluate the structural integrity (i.e. no leakages) and compatibility of the device in an animal model.
(Gordon)
SPECIFIC AIMS
SIGNIFICANCE
For our first aim where we are using information from sensing pins in the implant device to calculate the flow rate of the drug being delivered, this allows clinicians to better understand the current medicine delivery status. For our second aim where the implant device would be able to report its flow rate to clinicians, as well as receive signals to turn itself on and off, this enhances the efficiency and convenience for real-time control of the device. Ultimately, implementing these two aims could improve the quality of treatment delivered by this implant device.
Design Requirements
The requirements for our software development are outlined in the table below. The requirements have been assigned a phase (1-3) which corresponds to the order of implementation. The phases 1, 2, and 3 roughly match the minimum, expected, and maximum deliverables respectively.
Software Architecture
A flow chart for the software architecture in which we are implementing our code is shown in Figure 2. The skull-embedded implant contains the nRF52 SoC board which is responsible for the pulse width modulation which enables the pumping action of two pumps that each have two directions (left and right). A pump can only be pumping in one direction at a single time. The nRF52 board remotely communicates with Implantd over BLE to receive signals to turn aspects of the implant state (such as pump A or pump B pumping action) on and off and transmit pump flow data (such as the flow rate estimate) back.
Implementation
Link to code documentation: https://docs.google.com/document/d/1gmXXaWYDUAOrYLGrMPfjG09q04LgdRhBOVwFNt8_p8I/edit?usp=sharing
Double pump functionality
Our implementation accounts for two pumps in the skull-embedded implant, pump_a and pump_b. The pumps run independently of each other, so one can run while the other is turned off and direction switches within the pump can occur without affecting the other. The pumps are “turned on” by implementing a pulse width modulation that initiates the pumping action in the implant. The sensing pin of the pump collects a volume reading every 1 minute. If the volume reading passes a predefined threshold, then the pump switches directions. The maximum amount of time in which the pump can run in one direction is 60 minutes. We implemented this by capping the number of times the function pump_loop() can be called on a pump without switching and then forcing the pump to switch directions once this number of iterations is reached.
Flow rate calculations
The flow rate is calculated for each pump every 1 minute. The flow rate is calculated from the current and previous volume readings from the sensing pin and the amount of time that has passed between readings. When a reading is collected from the sensing pin, it is pushed onto a queue within the pump variable. To make an estimate of the flow rate at that given time, the difference between the current reading and previous reading is computed and then divided by the amount of time (seconds) that has passed between these readings, as shown below:
FlowRate1 = ( reading0 – reading1 ) / ( time0 – time1 )
These flow rates collected every minute are stored in a queue for each pump. Every 10 minutes, when it is time to transmit a flow rate estimate to the user over BLE, these rates are averaged, then popped from the queue so that a new set can be pushed on. The frequency at which readings, flow rate calculations, and transmission of estimates to the user occur is easily modifiable and is subject to change in the future to meet the needs of clinical translation.
Remote Communication with BLE
Remote communication between the nRF52 board and the nRF Connect mobile app is achieved using BLE Peripheral. A BLE Peripheral Service, doublepumpService, is instantiated with a UUID, set as the advertising service for this instance of BLE Peripheral, and added as an attribute. Five BLE Characteristics are created and added as attributes to BLE Peripheral. There are two BLE Int Characteristics, one for each pump, that turn the respective pump off (0) and on (1). There is an additional BLE Int Characteristic that turns a builtin LED light on and off, used only for testing purposes. Lastly, there are two BLE Double Characteristics, one for each pump, which are read only and send the estimates of the respective pump’s flow rate to the user every 10 minutes. The Arduino loop() function checks if the user is connected, and if so collects new values written by the user for the pump (a and b) and LED characteristics. The only actions occurring while connection is established is the collection of new Characteristic values and updating of respective pump states to preserve power and use as little energy as possible. If new values are written the pump states are modified before disconnecting and then calls pump_loop() with the updated values. Every 10 minutes, the average flow rate estimate is made accessible to the user from the rate BLE Double Characteristics (0.00 if the pump is turned off).
Testing
We performed software quality control using a verification and validation approach on our code. Link to test plan documentation: https://docs.google.com/document/d/1P3Vd85WlWNlj2Er21diio-0oYDFRXm9iejzTHICTXRQ/edit?usp=sharing
Verification
We have developed tests to verify that the code we wrote meets the specified design requirements for 1) the pumps, and 2) BLE connection.
Pump functionality
As mentioned in the Technical Approach section, we implemented code to use information from sensing pins in the pumps to determine the action of the pumps and perform flow rate calculations every minute to be displayed. The tests listed below were used to determine whether the pumps exhibit expected behaviors:
The first two tests are used to ensure that the pump switches its pumping direction (left/ right) when its pumping action is completed (when the maximum runtime is reached or when the reservoir is empty). With this functionality tested, we then tested that the two pumps exhibit this correct behavior when the code is run on Pump A and B simultaneously. In the fourth test, we confirmed that the “turn off” command in the code works for both pumps. Finally, we tested that the flow rate calculations in each pump are done at the expected intervals such that clinicians would be updated with the current medicine delivery rate regularly. The passing of these five tests indicates that our code meets the specified design requirement for the pump’s functionality. Detail descriptions and significance of these tests can be found in the test plan documentation.
BLE connection and control
As discussed in the Technical Approach section, the BLE connection should be implemented such that flow rate estimates can be transmitted to connected devices, and that the pumps can be turned on or off as instructed by signals sent from connected devices. The tests listed below were used to determine whether the pumps exhibit expected behaviors:
These tests were performed by connecting to the board with the nRF Connect mobile app. The first two tests are used to ensure that the BLE Peripheral Connection can be established. After ensuring that the connection is established, we then tested that the two pumps exhibit the corresponding behavior when they are instructed to be turned on or off using the nRF Connect app. In the fourth and fifth test, we confirmed that the flow rate calculated for each pump can be displayed on the connected device at the expected intervals. Finally, we made sure that the functioning of the pumps are not affected by disconnection from BLE Peripheral. The passing of these 6 tests indicates that our code meets the specified design requirement for the BLE connection and control. Detail descriptions and significance of these tests can be found in the test plan documentation.
Validation
We hope to validate that our system fulfills its intended role in the implant for clinicians, i.e. if the system in its current state could be useful in a clinical setting. While there are no concrete plans to integrate our code in the current prototype of the implant and test it in swine studies, we expect to receive qualitative feedback from our project mentors on the system and its clinical usability. This would provide us guidance for our next steps to maximize the utility of the BLE functionality established for a clinical setting in swine studies in Summer or Fall 2021.
This table shown below outlines our significant dependencies. While our supervisor Tushar and other members of the NPS lab helped with completing all hardware aspects of prototyping and testing our implementation, our team focused on the implementation of software components remotely connecting to hardware components. Should there be an extreme circumstance in which a team member has to go to the lab in person to interact with the hardware, Henry was in Baltimore for the rest of the spring semester and was able to do so.
* here list references and reading material Reading Material:
Oh S, Odland R, Wilson SR, Kroeger KM, Liu C, Lowenstein PR, Castro MG, Hall WA, Ohlfest JR. Improved distribution of small molecules and viral vectors in the murine brain using a hollow fiber catheter. J Neurosurg. 2007 Sep;107(3):568-77. doi: 10.3171/JNS-07/09/0568. PMID: 17886557; PMCID: PMC2615393. Chen PY, Ozawa T, Drummond DC, Kalra A, Fitzgerald JB, Kirpotin DB, Wei KC, Butowski N, Prados MD, Berger MS, Forsayeth JR, Bankiewicz K, James CD. Comparing routes of delivery for nanoliposomal irinotecan shows superior anti-tumor activity of local administration in treating intracranial glioblastoma xenografts. Neuro Oncol. 2013 Feb;15(2):189-97. doi: 10.1093/neuonc/nos305. Epub 2012 Dec 21. PMID: 23262509; PMCID: PMC3548589.
Zhou Z, Singh R, Souweidane MM. Convection-Enhanced Delivery for Diffuse Intrinsic Pontine Glioma Treatment. Curr Neuropharmacol. 2017;15(1):116-128. doi: 10.2174/1570159×14666160614093615. PMID: 27306036; PMCID: PMC5327456.
Vogelbaum MA, Aghi MK. Convection-enhanced delivery for the treatment of glioblastoma. Neuro Oncol. 2015 Mar;17 Suppl 2(Suppl 2):ii3-ii8. doi: 10.1093/neuonc/nou354. PMID: 25746090; PMCID: PMC4483037. Mehta AM, Sonabend AM, Bruce JN. Convection-Enhanced Delivery. Neurotherapeutics. 2017 Apr;14(2):358-371. doi: 10.1007/s13311-017-0520-4. PMID: 28299724; PMCID: PMC5398992.
Davis ME. Glioblastoma: Overview of Disease and Treatment. Clin J Oncol Nurs. 2016 Oct 1;20(5 Suppl):S2-8. doi: 10.1188/16.CJON.S1.2-8. PMID: 27668386; PMCID: PMC5123811.
References:
[1] Hottinger AF, Stupp R, Homicsko K. Standards of care and novel approaches in the management of glioblastoma multiforme. Chin J Cancer. 2014 Jan;33(1):32-9. doi: 10.5732/cjc.013.10207. PMID: 24384238; PMCID: PMC3905088.
[2] Solid lipid nanoparticles for skin and drug delivery: Methods of preparation and characterization techniques and applications - ScienceDirect: https://www.sciencedirect.com/science/article/pii/B9780128162002000153
[3] Gordon, Chad. Magnetic Resonance Imaging Compatible, Convection-Enhanced Delivery Cranial Implant Devices and Related Methods. CraniUSⓇ, 2020.
Here give list of other project files (e.g., source code) associated with the project. If these are online give a link to an appropriate external repository or to uploaded media files under this name space (2021-16).
