A biomimetic tumor tissue phantom for validating diffusion-weighted MRI measurements

Pore size estimation in axon-mimicking microfibers with diffusion-relaxation MRI

PURPOSE

This study aims to evaluate two distinct approaches for fiber radius estimation using diffusion-relaxation MRI data acquired in biomimetic microfiber phantoms that mimic hollow axons. The methods considered are the spherical mean power-law approach and a T2-based pore size estimation technique.

THEORY AND METHODS

A general diffusion-relaxation theoretical model for the spherical mean signal from water molecules within a distribution of cylinders with varying radii was introduced, encompassing the evaluated models as particular cases. Additionally, a new numerical approach was presented for estimating effective radii (i.e., MRI-visible mean radii) from the ground truth radii distributions, not reliant on previous theoretical approximations and adaptable to various acquisition sequences. The ground truth radii were obtained from scanning electron microscope images.

RESULTS

Both methods show a linear relationship between effective radii estimated from MRI data and ground-truth radii distributions, although some discrepancies were observed. The spherical mean power-law method overestimated fiber radii. Conversely, the T2-based method exhibited higher sensitivity to smaller fiber radii, but faced limitations in accurately estimating the radius in one particular phantom, possibly because of material-specific relaxation changes.

CONCLUSION

The study demonstrates the feasibility of both techniques to predict pore sizes of hollow microfibers. The T2-based technique, unlike the spherical mean power-law method, does not demand ultra-high diffusion gradients, but requires calibration with known radius distributions. This research contributes to the ongoing development and evaluation of neuroimaging techniques for fiber radius estimation, highlights the advantages and limitations of both methods, and provides datasets for reproducible research.

Tumor phantom model for MRI-guided focused ultrasound ablation studies

BACKGROUND

The persistent development of focused ultrasound (FUS) thermal therapy in the context of oncology creates the need for tissue-mimicking tumor phantom models for early-stage experimentation and evaluation of relevant systems and protocols.

PURPOSE

This study presents the development and evaluation of a tumor-bearing tissue phantom model for testing magnetic resonance imaging (MRI)-guided FUS (MRgFUS) ablation protocols and equipment based on MR thermometry.

METHODS

Normal tissue was mimicked by a pure agar gel, while the tumor simulator was differentiated from the surrounding material by including silicon dioxide. The phantom was characterized in terms of acoustic, thermal, and MRI properties. US, MRI, and computed tomography (CT) images of the phantom were acquired to assess the contrast between the two compartments. The phantom's response to thermal heating was investigated by performing high power sonications with a 2.4 MHz single element spherically focused ultrasonic transducer in a 3T MRI scanner.

RESULTS

The estimated phantom properties fall within the range of literature-reported values of soft tissues. The inclusion of silicon dioxide in the tumor material offered excellent tumor visualization in US, MRI, and CT. MR thermometry revealed temperature elevations in the phantom to ablation levels and clear evidence of larger heat accumulation within the tumor owing to the inclusion of silicon dioxide.

CONCLUSION

Overall, the study findings suggest that the proposed tumor phantom model constitutes a simple and inexpensive tool for preclinical MRgFUS ablation studies, and potentially other image-guided thermal ablation applications upon minimal modifications.

Estimating axon radius using diffusion-relaxation MRI: calibrating a surface-based relaxation model with histology

Axon radius is a potential biomarker for brain diseases and a crucial tissue microstructure parameter that determines the speed of action potentials. Diffusion MRI (dMRI) allows non-invasive estimation of axon radius, but accurately estimating the radius of axons in the human brain is challenging. Most axons in the brain have a radius below one micrometer, which falls below the sensitivity limit of dMRI signals even when using the most advanced human MRI scanners. Therefore, new MRI methods that are sensitive to small axon radii are needed. In this proof-of-concept investigation, we examine whether a surface-based axonal relaxation process could mediate a relationship between intra-axonal T2 and T1 times and inner axon radius, as measured using postmortem histology. A unique in vivo human diffusion-T1-T2 relaxation dataset was acquired on a 3T MRI scanner with ultra-strong diffusion gradients, using a strong diffusion-weighting (i.e., b = 6,000 s/mm2) and multiple inversion and echo times. A second reduced diffusion-T2 dataset was collected at various echo times to evaluate the model further. The intra-axonal relaxation times were estimated by fitting a diffusion-relaxation model to the orientation-averaged spherical mean signals. Our analysis revealed that the proposed surface-based relaxation model effectively explains the relationship between the estimated relaxation times and the histological axon radius measured in various corpus callosum regions. Using these histological values, we developed a novel calibration approach to predict axon radius in other areas of the corpus callosum. Notably, the predicted radii and those determined from histological measurements were in close agreement.

Cell-Membrane Coated Nanoparticles for Tumor Delineation and Qualitative Estimation of Cancer Biomarkers at Single Wavelength Excitation in Murine and Phantom Models

Real-time guidance through fluorescence imaging improves the surgical outcomes of tumor resections, reducing the chances of leaving positive margins behind. As tumors are heterogeneous, it is imperative to interrogate multiple overexpressed cancer biomarkers with high sensitivity and specificity to improve surgical outcomes. However, for accurate tumor delineation and ratiometric detection of tumor biomarkers, current methods require multiple excitation wavelengths to image multiple biomarkers, which is impractical in a clinical setting. Here, we have developed a biomimetic platform comprising near-infrared fluorescent semiconducting polymer nanoparticles (SPNs) with red blood cell membrane (RBC) coating, capable of targeting two representative cell-surface biomarkers (folate, αυβ3 integrins) using a single excitation wavelength for tumor delineation during surgical interventions. We evaluate our single excitation ratiometric nanoparticles in in vitro tumor cells, ex vivo tumor-mimicking phantoms, and in vivo mouse xenograft tumor models. Favorable biological properties (improved biocompatibility, prolonged blood circulation, reduced liver uptake) are complemented by superior spectral features: (i) specific fluorescence enhancement in tumor regions with high tumor-to-normal tissue (T/NT) ratios in ex vivo samples and (ii) estimation of cell-surface tumor biomarkers with single wavelength excitation providing insights about cancer progression (metastases). Our single excitation, dual output approach has the potential to differentiate between the tumor and healthy regions and simultaneously provide a qualitative indicator of cancer progression, thereby guiding surgeons in the operating room with the resection process.

Soy lecithin: A beneficial substance for adjusting the ADC in aqueous solutions to the values of biological tissues

PURPOSE

To test soy lecithin as a substance added to water for the construction of MRI phantoms with tissue-like diffusion coefficients. The performance of soy lecithin was assessed for the useable range of adjustable ADC values, the degree of non-Gaussian diffusion, simultaneous effects on relaxation times, and spectral signal properties.

METHODS

Aqueous soy lecithin solutions of different concentrations (0%, 0.5%, 1%, 2%, 3% …, 10%) and soy lecithin-agar gels were prepared and examined on a 3 Tesla clinical scanner at 18.5° ± 0.5°C. Echoplanar sequences (b values: 0-1000/3000 s/mm² ) were applied for ADC measurements. Quantitative relaxometry and MRS were performed for assessment of T₁ , T₂ , and detectable spectral components.

RESULTS

The presence of soy lecithin significantly restricts the diffusion of water molecules and mimics the nearly Gaussian nature of diffusion observed in tissue (for b values <1000 s/mm² ). ADC values ranged from 2.02 × 10^-3  mm² /s to 0.48 × 10^-3  mm² /s and cover the entire physiological range reported on biological tissue. Measured T₁ /T₂ values of pure lecithin solutions varied from 2685/2013 to 668/133 ms with increasing concentration. No characteristic signals of soy lecithin were observed in the MR spectrum. The addition of agar to the soy lecithin solutions allowed T₂ values to be well adjusted to typical values found in parenchymal tissue without affecting the soy lecithin-controlled ADC value.

CONCLUSION

Soy lecithin is a promising substance for the construction of diffusion phantoms with tissue-like ADC values. It provides several advantages over previously proposed substances, in particular a wide range of adjustable ADC values, the lack of additional ¹ H-signals, and the possibility to adjust ADC and T₂ values (by adding agar) almost independently of each other.

Apparent diffusion coefficient values in Modic changes – interobserver reproducibility and relation to Modic type

Background

Modic Changes (MCs) in the vertebral bone marrow were related to back pain in some studies but have uncertain clinical relevance. Diffusion weighted MRI with apparent diffusion coefficient (ADC)-measurements can add information on bone marrow lesions. However, few have studied ADC measurements in MCs. Further studies require reproducible and valid measurements. We expect valid ADC values to be higher in MC type 1 (oedema type) vs type 3 (sclerotic type) vs type 2 (fatty type). Accordingly, the purpose of this study was to evaluate ADC values in MCs for interobserver reproducibility and relation to MC type.

Methods

We used ADC maps (b 50, 400, 800 s/mm²) from 1.5 T lumbar spine MRI of 90 chronic low back pain patients with MCs in the AIM (Antibiotics In Modic changes)-study. Two radiologists independently measured ADC in fixed-sized regions of interests. Variables were MC-ADC (ADC in MC), MC-ADC% (0% = vertebral body, 100% = cerebrospinal fluid) and MC-ADC-ratio (MC-ADC divided by vertebral body ADC). We calculated mean difference between observers ± limits of agreement (LoA) at separate endplates. The relation between ADC variables and MC type was assessed using linear mixed-effects models and by calculating the area under the receiver operating characteristic curve (AUC).

Results

The 90 patients (mean age 44 years; 54 women) had 224 MCs Th12-S1 comprising type 1 (n = 111), type 2 (n = 91) and type 3 MC groups (n = 22). All ADC variables had higher predicted mean for type 1 vs 3 vs 2 (p < 0.001 to 0.02): MC-ADC (10^− 6 mm²/s) 1201/796/576, MC-ADC% 36/21/14, and MC-ADC-ratio 5.9/4.2/3.1. MC-ADC and MC-ADC% had moderate to high ability to discriminate between the MC type groups (AUC 0.73–0.91). MC-ADC-ratio had low to moderate ability (AUC 0.67–0.85). At L4-S1, widest/narrowest LoA were for MC-ADC 20 ± 407/12 ± 254, MC-ADC% 1.6 ± 18.8/1.4 ± 10.4, and MC-ADC-ratio 0.3 ± 4.3/0.2 ± 3.9. Difference between observers > 50% of their mean value was less frequent for MC-ADC (9% of MCs) vs MC-ADC% and MC-ADC-ratio (17–20%).

Conclusions

The MC-ADC variable (highest mean ADC in the MC) had best interobserver reproducibility, discriminated between MC type groups, and may be used in further research. ADC values differed between MC types as expected from previously reported MC histology.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12891-022-05610-4.

Developing quality assurance tests for simultaneous Positron Emission Tomography - Magnetic Resonance imaging for radiotherapy planning

Background and purpose Simultaneous Positron Emission Tomography - Magnetic Resonance (PET-MR) imaging can potentially improve radiotherapy by enabling more accurate tumour delineation and dose painting. The use of PET-MR imaging for radiotherapy planning requires a comprehensive Quality Assurance (QA) programme to be developed. This study aimed to develop the QA tests required and assess their repeatability and stability. Materials and methods QA tests were developed for: MR image quality, MR geometric accuracy, electromechanical accuracy, PET-MR alignment accuracy, Diffusion Weighted (DW)-MR Apparent Diffusion Coefficient (ADC) accuracy and PET Standard Uptake Value (SUV) accuracy. Each test used a dedicated phantom and was analysed automatically or semi-automatically, with in-house software. Repeatability was evaluated by three same-day measurements with independent phantom positions. Stability was assessed through 12 monthly measurements. Results The repeatability Standard Deviations (SDs) of distortion for the MR geometric accuracy test were ⩽ 0.7 mm . The repeatability SDs in ADC difference from reference were ⩽ 3 % for the DW-MR accuracy test. The PET SUV difference from reference repeatability SD was 0.3 % . The stability SDs agreed within 0.6 mm , 1 percentage point and 1.4 percentage points of the repeatability SDs for the geometric, ADC and SUV accuracy tests respectively. There were no monthly trends apparent. These results were representative of the other tests. Conclusions QA Tests for radiotherapy planning PET-MR have been developed. The tests appeared repeatable and stable over a 12-month period. The developed QA tests could form the basis of a QA programme that enables high-quality, robust PET-MR imaging for radiotherapy planning.

Coaxial electrospun biomimetic copolymer fibres for application in diffusion magnetic resonance imaging

Objective. The use of diffusion magnetic resonance imaging (dMRI) opens the door to characterizing brain microstructure because water diffusion is anisotropic in axonal fibres in brain white matter and is sensitive to tissue microstructural changes. As dMRI becomes more sophisticated and microstructurally informative, it has become increasingly important to use a reference object (usually called an imaging phantom) for validation of dMRI. This study aims to develop axon-mimicking physical phantoms from biocopolymers and assess their feasibility for validating dMRI measurements.Approach. We employed a simple and one-step method-coaxial electrospinning-to prepare axon-mimicking hollow microfibres from polycaprolactone-b-polyethylene glycol (PCL-b-PEG) and poly(D, L-lactide-co-glycolic) acid (PLGA), and used them as building elements to create axon-mimicking phantoms. Electrospinning was firstly conducted using two types of PCL-b-PEG and two types of PLGA with different molecular weights in various solvents, with different polymer concentrations, for determining their spinnability. Polymer/solvent concentration combinations with good fibre spinnability were used as the shell material in the following co-electrospinning process in which the polyethylene oxide polymer was used as the core material. Following the microstructural characterization of both electrospun and co-electrospun fibres using optical and electron microscopy, two prototype phantoms were constructed from co-electrospun anisotropic hollow microfibres after inserting them into water-filled test tubes.Main results. Hollow microfibres that mimic the axon microstructure were successfully prepared from the appropriate core and shell material combinations. dMRI measurements of two phantoms on a 7 tesla (T) pre-clinical scanner revealed that diffusivity and anisotropy measurements are in the range of brain white matter.Significance. This feasibility study showed that co-electrospun PCL-b-PEG and PLGA microfibre-based axon-mimicking phantoms could be used in the validation of dMRI methods which seek to characterize white matter microstructure.

Diffusion model comparison identifies distinct tumor sub-regions and tracks treatment response

PURPOSE

MRI biomarkers of tumor response to treatment are typically obtained from parameters derived from a model applied to pre-treatment and post-treatment data. However, as tumors are spatially and temporally heterogeneous, different models may be necessary in different tumor regions, and model suitability may change over time. This work evaluates how the suitability of two diffusion-weighted (DW) MRI models varies spatially within tumors at the voxel level and in response to radiotherapy, potentially allowing inference of qualitatively different tumor microenvironments.

METHODS

DW-MRI data were acquired in CT26 subcutaneous allografts before and after radiotherapy. Restricted and time-independent diffusion models were compared, with regions well-described by the former hypothesized to reflect cellular tissue, and those well-described by the latter expected to reflect necrosis or oedema. Technical and biological validation of the percentage of tissue described by the restricted diffusion microstructural model (termed %MM) was performed through simulations and histological comparison.

RESULTS

Spatial and radiotherapy-related variation in model suitability was observed. %MM decreased from a mean of 64% at baseline to 44% 6 days post-radiotherapy in the treated group. %MM correlated negatively with the percentage of necrosis from histology, but overestimated it due to noise. Within MM regions, microstructural parameters were sensitive to radiotherapy-induced changes.

CONCLUSIONS

There is spatial and radiotherapy-related variation in different models' suitability for describing diffusion in tumor tissue, suggesting the presence of different and changing tumor sub-regions. The biological and technical validation of the proposed %MM cancer imaging biomarker suggests it correlates with, but overestimates, the percentage of necrosis.

Co-electrospraying of tumour cell mimicking hollow polymeric microspheres for diffusion magnetic resonance imaging

Diffusion magnetic resonance imaging (dMRI) is considered as a useful tool to study solid tumours. However, the interpretation of dMRI signal and validation of quantitative measurements of is challenging. One way to address these challenges is by using a standard reference material that can mimic tumour cell microstructure. There is a growing interest in using hollow polymeric microspheres, mainly prepared by multiple steps, as mimics of cells in healthy and diseased tissue. The present work reports on tumour cell-mimicking materials composed of hollow microspheres for application as a standard material in dMRI. These microspheres were prepared via one-step co-electrospraying process. The shell material was poly(d,l-lactic-co-glycolic acid) (PLGA) polymers with different molecule weights and/or ratios of glycolic acid-to-lactic, while the core was polyethylene glycol (PEG) or ethylene glycol. The resultant co-electrosprayed products were characterised by optical microscopy, scanning electron microscopy (SEM) and synchrotron X-ray micro-CT. These products were found to have variable structures and morphologies, e.g. from spherical particles with/without surface hole, through beaded fibres to smooth fibres, which mainly depend on PLGA composition and core materials. Only the shell material of PLGA polymer with ester terminated, Mw 50,000-75,000 g mol-1, and lactide:glycolide 85:15 formed hollow microspheres via the co-electrospraying process using the core material of 8 wt% PEG/chloroform as the core. A water-filled test object (or phantom) was designed and constructed from samples of the material generated from co-electrosprayed PLGA microspheres and tested on a 7 T MRI scanner. The preliminary MRI results provide evidence that hollow PLGA microspheres can restrict/hinder water diffusion as cells do in tumour tissue, implying that the phantom may be suitable for use as a quantitative validation and calibration tool for dMRI.