Concept of a fully-implantable system to monitor tumor recurrence

Abstract

Current treatment for glioblastoma includes tumor resection followed by radiation, chemotherapy, and periodic post-operative examinations. Despite combination therapies, patients face a poor prognosis and eventual recurrence, which often occurs at the resection site. With standard MRI imaging surveillance, histologic changes may be overlooked or misinterpreted, leading to erroneous conclusions about the course of adjuvant therapy and subsequent interventions. To address these challenges, we propose an implantable system for accurate continuous recurrence monitoring that employs optical sensing of fluorescently labeled cancer cells and is implanted in the resection cavity during the final stage of tumor resection. We demonstrate the feasibility of the sensing principle using miniaturized system components, optical tissue phantoms, and porcine brain tissue in a series of experimental trials. Subsequently, the system electronics are extended to include circuitry for wireless energy transfer and power management and verified through electromagnetic field, circuit simulations and test of an evaluation board. Finally, a holistic conceptual system design is presented and visualized. This novel approach to monitor glioblastoma patients is intended to early detect recurrent cancerous tissue and enable personalization and optimization of therapy thus potentially improving overall prognosis.

Figure 1

High-level diagram of the components and their interaction.

Figure 2

Schematic representation of the electronic measurement circuit.

Figure 3

Experimental setup: (a) setup with aligned height adjustable holder for liquid samples; (b) left-hand side: depiction of the phantom samples (top) and setup with a stationary placeholder for solid sample placement (bottom). (b) right-hand side: schematic representation of the measurement setup with varying thicknesses of the glioblastoma phantom, denoted as alpha [1.2 mm, 2.25 mm, 3.45 mm, 4.5 mm, 8 mm] (top), and the measurement of the obscured glioblastoma phantom by PPIX-free samples with thickness beta [1.5 mm, 2.2 mm] (bottom).

Figure 4

Experimental setup for fluorescence detection in biological tissue: (a) porcine brain tissue samples - cortex facing up; (b) porcine brain tissue samples - white matter facing up; (c) sensor and sample placement.

Figure 5

(a) Implementation of an axisymmetric subcutaneous wireless power transfer problem in FEMM 4.2. Representation of the coil topology of the (b) flat coil, (c) layered coil, (d) hemispherical coil, and the magnetic field propagation radiating from them through the head model.

Figure 6

Charging circuit schematic including inductively coupled power transmission coils, charge management IC, and Li-Ion battery equivalent circuit.

Figure 7

Experimental setup for transcutaneous wireless charging validation: (a) wireless charging evaluation circuit board; (b) wireless energy transceiver coil; (c) porcine skin (d) measurement setup.

Figure 8

(a) Light signal intensity recorded at different distances between the PPIX-free reference sample and photodiode. (b) Cleaned intensity signals of the liquid PPIX-samples vs. photodiode distance.

Figure 9

(a) Light signal intensity recorded from gelatin phantom samples with different thicknesses. (b) Intensity measured at PPIX-free reference phantom, and PPIX-containing phantom covered with PPIX-free phantom.

Figure 10

(a) Light signal intensity recorded from porcine brain grey matter before (blue) and after (red) injection with PPIX. (b) Light signal intensity recorded from porcine brain white matter before (blue) and after (red) injection with PPIX.

Figure 11

Simulated power transmission characteristics of the three investigated transceiver coil topologies with the input power (blue), transferred power (red), and transfer efficiency (orange) vs. input frequency.

Figure 12

Measured power transmission characteristics including input power (blue), transferred power (red), and transfer efficiency (orange) vs. input frequency.

Figure 13

Visualization of the envisioned implantable cancer tissue detection system based on previously tested or simulated electronics. The image on the right is adapted from “A depiction of various types of cerebral Hematoma(L to R) - Epidural Hematoma, Subdural Hematoma, and Intracranial Hematoma.” by www.scientificanimations.com licensed under CC BY-SA 4.0. The image has been cropped and items have been added.