Poster R7 - Molecular Quantification with Spectral Photon-Counting Computed Tomography for New Diagnostic Imaging Applications

Introduction: X-ray computed tomography (CT) allows scientists and clinicians to non-invasively visualize deep tissue structures in three-dimensions and at high spatial resolution. However, conventional CT is generally limited to anatomic imaging rather than molecular or functional imaging due to limitations in spectral resolution and soft tissue contrast. Spectral photon-counting computed tomography (PCCT) enables multi-energy X-ray imaging due to advanced, energy-discriminating photon-counting detectors. Material decomposition algorithms combined with spectral PCCT image acquisition transform CT beyond anatomic imaging to molecular imaging. However, clinical diagnostic imaging and preclinical research with spectral PCCT remains limited to applications that are already possible with conventional CT. The experimental demonstration of transformative imaging capabilities is needed to accelerate clinical and preclinical adoption of spectral PCCT.

Preclinical studies have shown that breast microcalcifications can be targeted by bisphosphonate-functionalized gold nanoparticles (BP-Au NPs) to enable contrast-enhanced radiographic detection (Cole et al., 2014), but conventional mammography and CT cannot distinguish contrast from the microcalcification vs. the contrast agent. X-ray CT has also recently been investigated for monitoring tissue-engineered medical products using exogeneous contrast agents, but conventional CT is limited to monitoring only one material/function and does not permit quantitative molecular imaging. Finally, CT scans used for other indications can be employed in screening for osteoporosis, but conventional CT cannot measure both bone mineral and lipid content.

Therefore, the overall objective of this work is to demonstrate experimental capabilities of spectral PCCT in high-impact applications that are currently impossible or severely limited with current diagnostic imaging modalities (Fig. 1).

Materials and

Methods: Hydroxyapatite (HA) µcals (control) and bisphosphonate-functionalized gold nanoparticle (BP-Au NP) labeled µcals of varying size (1 – 3 mm diameter) and HA density (100 – 200 mg/cm3) were prepared, embedded within agarose phantoms, and imaged by spectral PCCT. The Au and HA concentration in µcals was quantified using maximum likelihood estimation (MLE)-based material decomposition in the image domain (Curtis and Roeder, 2019). The Au:HA ratio was adopted to discriminate between control and labeled µcals.

Control (unloaded) and Au NP-loaded gelatin methacrylate (gelMA) hydrogel scaffolds (Li et al, 2022) were imaged by spectral PCCT over seven days in vitro. Both control and Au NP-loaded hydrogels were subject to enzymatic degradation between imaging time points to mimic in vivo degradation. The hydrogel degradation measured by spectral PCCT was compared to that measured by gold standard destructive techniques (ICP-OES, gravimetric analysis).

Constructs of various geometric designs containing Au and gadolinium oxide (Gd2O3) NPs were 3D-printed at high spatial fidelity with bioinks (Gil et al, 2023). Constructs were imaged via spectral PCCT and contrast agent concentrations were determined via material decomposition. Resulting material concentration maps were evaluated for quantitative and spatial accuracy compared to ground truth.

A custom lipid and water calibration phantom was created which, combined with existing bone mineral phantoms, enabled simultaneous quantification of bone mineral and lipid content using spectral PCCT. Phantom lipid content validated using X-ray micro-CT and MRI imaging. The accuracy of image domain material decomposition was evaluated using the quantitative metrics (RMSE, AUC, Sample Mean, Absolute Error).

Results, Conclusions, and Discussions: Spectral PCCT enabled contrast-enhanced detection of model breast microcalcifications of varying size and hydroxyapatite (HA) density, that were targeted by bisphosphonate functionalized gold (Au) nanoparticles, using the measured Au:HA ratio from image-based material decomposition (Fig. 2a). Au:HA ratios for µcals pooled across HA density suggest that the ability to discern between labeled and control µcals is size-dependent, as µcals 3 and 2 mm in size were able to be discriminated, but not µcals 1 mm in size.

Spectral PCCT further enabled nondestructive, longitudinal, quantitative monitoring of the degradation kinetics of hydrogel scaffolds covalently linked with Au nanoparticles and was validated by concurrent measurement with gold-standard techniques (Fig. 2b). GelMA-Au hydrogels were also shown to exhibit similar degradation kinetics compared with gelMA hydrogels as measured gravimetrically, confirming that Au NPs did not alter the gelMA degradation kinetics.

Additionally, geometric features of complex, multi-material 3D-bioprinted hydrogel constructs were able to be discriminated by multicontrast (Au and Gd2O3) decomposition in spectral PCCT imaging of phantoms and after implantation in mice (Fig. 2c), despite exhibiting similar overall X-ray attenuation. Contrast agent concentrations (Au, Gd2O3) within regions of bioprinted scaffolds of various geometric designs were discriminated and quantified with high spatial accuracy (Gd AUC > 0.9, Au AUC > 0.8) and quantitative accuracy (Gd: 21-26 mM, Au: 10-14 mM).

Finally, spectral PCCT enabled simultaneous quantification of bone mineral and lipid content within trabecular bone cores using image-based material decomposition calibrated by a custom oil/water imaging phantom (Fig. 2d). A lipid/water calibration phantom was developed and validated for measurement of bone adipose content using spectral PCCT. Lipid phantom samples exhibited a strongly correlated linear decrease in X-ray attenuation with increasing lipid content and were validated with concurrent measurement by MRI. The lipid content measured by spectral PCCT exhibited the greatest accuracy (± 4 vol%) in the range of 40 to 60 vol% lipid, which falls within human physiological range.

Thus, spectral PCCT enabled molecular quantification and new imaging capabilities for innovative and clinically relevant applications which are currently not possible with other current clinical imaging modalities.

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