Preclinical Imaging Data Research Articles

Image data harmonization tools for the analysis of post-traumatic epilepsy development in preclinical multisite MRI studies

Preclinical MRI studies have been utilized for the discovery of biomarkers that predict post-traumatic epilepsy (PTE). However, these single site studies often lack statistical power due to limited and homogeneous datasets. Therefore, multisite studies, such as the Epilepsy Bioinformatics Study for Antiepileptogenic Therapy (EpiBioS4Rx), are developed to create large, heterogeneous datasets that can lead to more statistically significant results. EpiBioS4Rx collects preclinical data internationally across sites, including the United States, Finland, and Australia. However, in doing so, there are robust normalization and harmonization processes that are required to obtain statistically significant and generalizable results. This work describes the tools and procedures used to harmonize multisite, multimodal preclinical imaging data acquired by EpiBioS4Rx. There were four main harmonization processes that were utilized, including file format harmonization, naming convention harmonization, image coordinate system harmonization, and diffusion tensor imaging (DTI) metrics harmonization. By using Python tools and bash scripts, the file formats, file names, and image coordinate systems are harmonized across all the sites. To harmonize DTI metrics, values are estimated for each voxel in an image to generate a histogram representing the whole image. Then, the Quantitative Imaging Toolkit (QIT) modules are utilized to scale the mode to a value of one and depict the subsequent harmonized histogram. The standardization of file formats, naming conventions, coordinate systems, and DTI metrics are qualitatively assessed. The histograms of the DTI metrics were generated for all the individual rodents per site. For inter-site analysis, an average of the individual scans was calculated to create a histogram that represents each site. In order to ensure the analysis can be run at the level of individual animals, the sham and TBI cohort were analyzed separately, which depicted the same harmonization factor. The results demonstrate that these processes qualitatively standardize the file formats, naming conventions, coordinate systems, and DTI metrics of the data. This assists in the ability to share data across the study, as well as disseminate tools that can help other researchers to strengthen the statistical power of their studies and analyze data more cohesively.

Measurement of Tumor T2* Relaxation Times after Iron Oxide Nanoparticle Administration.

T2* relaxometry is one of the established methods to measure the effect of superparamagnetic iron oxide nanoparticles on tumor tissues with magnetic resonance imaging (MRI). Iron oxide nanoparticles shorten the T1, T2, and T2* relaxation times of tumors. While the T1 effect is variable based on the size and composition of the nanoparticles, the T2 and T2* effects are usually predominant, and T2* measurements are the most time-efficient in a clinical context. Here, we present our approach to measuring tumor T2* relaxation times, using multi-echo gradient echo sequences, external software, and a standardized protocol for creating a T2* map with scanner-independent software. This facilitates the comparison of imaging data from different clinical scanners, different vendors, and co-clinical research work (i.e., tumor T2* data obtained in mouse models and patients). Once the software is installed, the T2 Fit Map plugin needs to be installed from the plugin manager. This protocol provides step-by-step procedural details, from importing the multi-echo gradient echo sequences into the software, to creating color-coded T2* maps and measuring tumor T2* relaxation times. The protocol can be applied to solid tumors in any body part and has been validated based on preclinical imaging data and clinical data in patients. This could facilitate tumor T2* measurements for multi-center clinical trials and improve the standardization and reproducibility of tumor T2* measurements in co-clinical and multi-center data analyses.

Machine learning identifies multi-parametric functional PET/MR imaging cluster to predict radiation resistance in preclinical head and neck cancer models

PurposeTumor hypoxia and other microenvironmental factors are key determinants of treatment resistance. Hypoxia positron emission tomography (PET) and functional magnetic resonance imaging (MRI) are established prognostic imaging modalities to identify radiation resistance in head-and-neck cancer (HNC). The aim of this preclinical study was to develop a multi-parametric imaging parameter specifically for focal radiotherapy (RT) dose escalation using HNC xenografts of different radiation sensitivities.MethodsA total of eight human HNC xenograft models were implanted into 68 immunodeficient mice. Combined PET/MRI using dynamic [18F]-fluoromisonidazole (FMISO) hypoxia PET, diffusion-weighted (DW), and dynamic contrast-enhanced MRI was carried out before and after fractionated RT (10 × 2 Gy). Imaging data were analyzed on voxel-basis using principal component (PC) analysis for dynamic data and apparent diffusion coefficients (ADCs) for DW-MRI. A data- and hypothesis-driven machine learning model was trained to identify clusters of high-risk subvolumes (HRSs) from multi-dimensional (1-5D) pre-clinical imaging data before and after RT. The stratification potential of each 1D to 5D model with respect to radiation sensitivity was evaluated using Cohen’s d-score and compared to classical features such as mean/peak/maximum standardized uptake values (SUVmean/peak/max) and tumor-to-muscle-ratios (TMRpeak/max) as well as minimum/valley/maximum/mean ADC.ResultsComplete 5D imaging data were available for 42 animals. The final preclinical model for HRS identification at baseline yielding the highest stratification potential was defined in 3D imaging space based on ADC and two FMISO PCs (p<0.001). In 1D imaging space, only clusters of ADC revealed significant stratification potential (p=0.002). Among all classical features, only ADCvalley showed significant correlation to radiation resistance (p=0.006). After 2 weeks of RT, FMISO_c1 showed significant correlation to radiation resistance (p=0.04).ConclusionA quantitative imaging metric was described in a preclinical study indicating that radiation-resistant subvolumes in HNC may be detected by clusters of ADC and FMISO using combined PET/MRI which are potential targets for future functional image-guided RT dose-painting approaches and require clinical validation.

Community Survey Results Show that Standardisation of Preclinical Imaging Techniques Remains a Challenge

PurposeTo support acquisition of accurate, reproducible and high-quality preclinical imaging data, various standardisation resources have been developed over the years. However, it is unclear the impact of those efforts in current preclinical imaging practices. To better understand the status quo in the field of preclinical imaging standardisation, the STANDARD group of the European Society of Molecular Imaging (ESMI) put together a community survey and a forum for discussion at the European Molecular Imaging Meeting (EMIM) 2022. This paper reports on the results from the STANDARD survey and the forum discussions that took place at EMIM2022.ProceduresThe survey was delivered to the community by the ESMI office and was promoted through the Society channels, email lists and webpages. The survey contained seven sections organised as generic questions and imaging modality-specific questions. The generic questions focused on issues regarding data acquisition, data processing, data storage, publishing and community awareness of international guidelines for animal research. Specific questions on practices in optical imaging, PET, CT, SPECT, MRI and ultrasound were further included.ResultsData from the STANDARD survey showed that 47% of survey participants do not have or do not know if they have QC/QA guidelines at their institutes. Additionally, a large variability exists in the ways data are acquired, processed and reported regarding general aspects as well as modality-specific aspects. Moreover, there is limited awareness of the existence of international guidelines on preclinical (imaging) research practices.ConclusionsStandardisation of preclinical imaging techniques remains a challenge and hinders the transformative potential of preclinical imaging to augment biomedical research pipelines by serving as an easy vehicle for translation of research findings to the clinic. Data collected in this project show that there is a need to promote and disseminate already available tools to standardise preclinical imaging practices.

An imaging-based stochastic model for simulation of tumour vasculature

A mathematical model which reconstructs the structure of existing vasculature using patient-specific anatomical, functional and molecular imaging as input was developed. The vessel structure is modelled according to empirical vascular parameters, such as the mean vessel branching angle. The model is calibrated such that the resultant oxygen map modelled from the simulated microvasculature stochastically matches the input oxygen map to a high degree of accuracy (R2 ≈ 1). The calibrated model was successfully applied to preclinical imaging data. Starting from the anatomical vasculature image (obtained from contrast-enhanced computed tomography), a representative map of the complete vasculature was stochastically simulated as determined by the oxygen map (obtained from hypoxia [64Cu]Cu-ATSM positron emission tomography). The simulated microscopic vasculature and the calculated oxygenation map successfully represent the imaged hypoxia distribution (R2 = 0.94). The model elicits the parameters required to simulate vasculature consistent with imaging and provides a key mathematical relationship relating the vessel volume to the tissue oxygen tension. Apart from providing an excellent framework for visualizing the imaging gap between the microscopic and macroscopic imagings, the model has the potential to be extended as a tool to study the dynamics between the tumour and the vasculature in a patient-specific manner and has an application in the simulation of anti-angiogenic therapies.

Radiation dose estimation using preclinical imaging with 124I-metaiodobenzylguanidine (MIBG) PET.

A pretherapy 124I-metaiodobenzylguanidine (MIBG) positron emission tomography (PET)/computed tomography (CT) provides a potential method to estimate radiation dose to normal organs, as well as tumors prior to 131I-MIBG treatment of neuroblastoma or pheochromocytoma. The aim of this work was to estimate human-equivalent internal radiation dose of 124I-MIBG using PET/CT data in a murine xenograft model. Athymic mice subcutaneously implanted with NB1691 cells that express high levels of human norepinephrine transporter (n = 4) were imaged using small animal microPET/CT over 96 h (approximate imaging time points: 0.5, 2, 24, 52, and 96 h) after intravenous administration of 3.07-4.84 MBq of 124I-MIBG via tail vein. The tumors did not accumulate 124I-MIBG to a detectable level. All four animals were considered as control and organ radiation dosimetry was performed. Volumes of interest were drawn on the coregistered CT images for thyroid, heart, lung, liver, kidney, and bladder, and transferred to PET images to obtain pharmacokinetic data. Based on tabulated organ mass distributions for both mice and adult male human, preclinical pharmacokinetic data were extrapolated to their human-equivalent values. Radiation dose estimations for different age groups were performed using the OLINDA/EXM software with modified tissue weighting factors in the recent International Commission on Radiological Protection (ICRP) Publication 103. The mean effective dose from 124I-MIBG using weighting factors from ICRP 103 to the adult male was estimated at 0.25 mSv/MBq. In different age groups, effective doses using values from ICRP 103 were estimated as follows: Adult female: 0.34, 15-yr-old: 0.39 mSv/MBq, 10-yr-old: 0.58 mSv/MBq, 5-yr-old: 1.03 mSv/MBq, 1-yr-old: 1.92 mSv/MBq, and newborn: 3.75 mSv/ MBq. For comparison, the reported effective dose equivalent of 124I-NaI for adult male (25% thyroid uptake, MIRD Dose Estimate Report No. 5) was 6.5 mSv/MBq. The authors estimated human-equivalent internal radiation dose of 124I-MIBG using preclinical imaging data. As a reference, the effective dose estimation showed that 124I-MIBG would deliver less radiation dose than 124I-NaI, a radiotracer already being used in patients with thyroid cancer.

Near infrared fluorescent optical imaging for nodal staging

Current techniques to assess lymph node metastases in cancer patients include lymphoscintigraphy after administration of a nonspecific radiocolloid in order to locate and resect lymph nodes for pathological examination of harbored cancer cells. Clinical trials involving intradermal or subcutaneous injection of antibody-based nuclear imaging agents have demonstrated the feasibility for target-specific, molecular imaging of cancer-positive lymph nodes. The basis for employing near-infrared (NIR) optical imaging for assessing disease is evidenced by recent work showing functional lymph imaging in mice, swine, and humans. We review antibody-based immunolymphoscintigraphy with an emphasis on the use of trastuzumab (or Herceptin) to target human epidermal growth factor receptor-2 (HER2) overexpressed in some breast cancers. Specifically, we review in vitro and preclinical imaging data from our laboratory that show how the dual-labeled agent ((111)In-DTPA)(n)-trastuzumab-(IRDye800)(m) utilizes the high photon count provided by an NIR fluorescent dye, IRDye 800CW, and the radioactive signal from a gamma emitter, Indium-111, for possible detection of HER2 metastasis in lymph nodes. We show that the accumulation and clearance of ((111)In-DTPA)(n)-trastuzumab-(IRDye800)(m) from the axillary nodes of mice occurs 48 h after intradermal injection into the dorsal aspect of the foot. The requirement for long clearance times from normal, cancer-negative nodes presents challenges for nuclear imaging agents with limited half-lives but does not hamper NIR optical imaging.