Configurable γ Photon Spectrometer to Enable Precision Radioguided Tumor Resection

Surgical tumor resection aims to remove all cancer cells in the tumor margin and at centimeter-scale depths below the tissue surface. During surgery, microscopic clusters of disease are intraoperatively difficult to visualize and are often left behind, significantly increasing the risk of cancer recurrence. Radioguided surgery (RGS) has shown the ability to selectively tag cancer cells with gamma (γ) photon emitting radioisotopes to identify them, but require a mm-scale γ photon spectrometer to localize the position of these cells in the tissue margin (i.e., a function of incident γ photon energy) with high specificity. Here we present a 9.9 mm2 integrated circuit (IC)-based γ spectrometer implemented in 180 nm CMOS, to enable the measurement of single γ photons and their incident energy with sub-keV energy resolution. We use small 2 2 um reverse-biased diodes that have low depletion region capacitance, and therefore produce millivolt-scale voltage signals in response to the small charge generated by incident γ photons. A low-power energy spectrometry method is implemented by measuring the decay time it takes for the generated voltage signal to settle back to DC after a γ detection event, instead of measuring the voltage drop directly. This spectrometry method is implemented in three different pixel architectures that allow for configurable pixel sensitivity, energy-resolution, and energy dynamic range based on the widely heterogenous surgical and patient presentation in RGS. The spectrometer was tested with three common γ-emitting radioisotopes (64Cu, 133Ba, 177Lu), and is able to resolve activities down to 1 uCi with sub-keV energy resolution and 1.315 MeV energy dynamic range, using 5-minute acquisitions.

💡 Research Summary

This paper presents a novel, configurable gamma‑photon spectrometer designed specifically for precision radioguided tumor resection (RGS). Implemented in a standard 180 nm CMOS process, the ASIC occupies only 9.9 mm² and integrates 2 × 2 µm reverse‑biased deep N‑well/P‑substrate diodes as the primary sensing elements. Because of their extremely low parasitic capacitance, each diode can convert the few electron‑hole pairs generated by a single gamma interaction into a millivolt‑scale voltage pulse. Rather than measuring the pulse amplitude directly, the authors extract the incident photon’s energy by timing how long the voltage decays back to its DC level (decay time, DT). This time‑domain approach dramatically reduces power consumption while preserving sub‑keV energy resolution.

The relationship between DT and the deposited charge is highly non‑linear, depending on diode capacitance, bias resistance, and the silicon quenching factor. To map DT to the original gamma‑photon energy, the authors pre‑compute calibration tables using TOPAS, a state‑of‑the‑art radiation transport simulator that accounts for Compton scattering, depth‑dependent energy loss, and angular distribution. Three distinct pixel architectures are offered, each trading off sensitivity, energy resolution, and dynamic range: (1) high‑sensitivity, wide‑range, coarse‑resolution; (2) medium‑sensitivity, medium‑resolution, medium‑range; and (3) low‑sensitivity, fine‑resolution, narrow‑range. This configurability allows the system to be tuned for different isotopes, patient anatomy, and surgical scenarios.

The spectrometer’s readout is asynchronous, employing a low‑power digital controller and an SRAM‑based calibration unit that stores per‑pixel DT‑to‑energy conversion parameters. The total power budget remains in the tens of microwatts, making the device suitable for minimally invasive tools.

Experimental validation was performed with three clinically relevant gamma‑emitting isotopes: 64Cu (511 keV and 1.346 MeV lines), 133Ba (30, 81, 302, 356 keV lines), and 177Lu (113 keV, 208 keV lines). For each isotope, activities as low as 1 µCi were detected within a 5‑minute acquisition window. The system achieved sub‑keV energy resolution across a dynamic range up to 1.315 MeV, successfully discriminating the different gamma lines and demonstrating depth‑dependent spectral broadening consistent with Monte‑Carlo predictions.

Compared with prior art—scintillator‑coupled SPAD arrays, indirect detector ASICs, or bulk semiconductor spectrometers—the presented ASIC eliminates the need for bulky scintillators, high bias voltages, or 3‑D integration, while delivering a larger sensing area per energy bin, more energy bins, and full configurability. The authors argue that this combination enables real‑time feedback on microscopic tumor remnants during surgery, potentially reducing unnecessary healthy tissue removal and decreasing the need for repeat operations or adjuvant therapies.

Future work outlined includes scaling the diode array to increase spatial coverage, integrating on‑chip temperature compensation, and conducting in‑vivo clinical trials to assess performance under realistic surgical conditions. In summary, the paper delivers a compact, low‑power, highly configurable CMOS gamma‑spectrometer that meets the stringent requirements of modern radioguided oncology and represents a significant step toward intra‑operative, energy‑resolved tumor margin assessment.