Multiparametric MR for non-invasive evaluation of tumour tissue histological characteristics after radionuclide therapy

Co-administration with A1M does not influence apoptotic response of 177Lu-octreotate in GOT1 neuroendocrine tumors

Recombinant α₁-microglobulin (A1M) is a proposed radioprotector during ¹⁷⁷Lu-octreotate therapy of neuroendocrine tumors (NETs). To ensure a maintained therapeutic effect, we previously demonstrated that A1M does not affect the ¹⁷⁷Lu-octreotate induced decrease in GOT1 tumor volume. However, the underlying biological events of these findings are still unknown. The aim of this work was to examine the regulation of apoptosis-related genes in GOT1 tumors short-time after i.v. administration of ¹⁷⁷Lu-octreotate with and without A1M or A1M alone. Human GOT1 tumor-bearing mice received 30 MBq ¹⁷⁷Lu-octreotate or 5 mg/kg A1M or co-treatment with both. Animals were sacrificed after 1 or 7 days. Gene expression analysis of apoptosis-related genes in GOT1 tissue was performed with RT-PCR. In general, similar expression patterns of pro- and anti-apoptotic genes were found after ¹⁷⁷Lu-octreotate exposure with or without co-administration of A1M. The highest regulated genes in both irradiated groups compared to untreated controls were FAS and TNFSFRS10B. Administration of A1M alone only resulted in significantly regulated genes after 7 days. Co-administration of A1M did not negatively affect the transcriptional apoptotic response of ¹⁷⁷Lu-octreotate in GOT1 tumors.

Tumour Heterogeneity and the Consequent Practical Challenges in the Management of Gastroenteropancreatic Neuroendocrine Neoplasms

Tumour heterogeneity is a common phenomenon in neuroendocrine neoplasms (NENs) and a significant cause of treatment failure and disease progression. Genetic and epigenetic instability, along with proliferation of cancer stem cells and alterations in the tumour microenvironment, manifest as intra-tumoural variability in tumour biology in primary tumours and metastases. This may change over time, especially under selective pressure during treatment. The gastroenteropancreatic (GEP) tract is the most common site for NENs, and their diagnosis and treatment depends on the specific characteristics of the disease, in particular proliferation activity, expression of somatostatin receptors and grading. Somatostatin receptor expression has a major role in the diagnosis and treatment of GEP-NENs, while Ki-67 is also a valuable prognostic marker. Intra- and inter-tumour heterogeneity in GEP-NENS, however, may lead to inaccurate assessment of the disease and affect the reliability of the available diagnostic, prognostic and predictive tests. In this review, we summarise the current available evidence of the impact of tumour heterogeneity on tumour diagnosis and treatment of GEP-NENs. Understanding and accurately measuring tumour heterogeneity could better inform clinical decision making in NENs.

Dynamic Contrast-Enhanced MRI in the Abdomen of Mice with High Temporal and Spatial Resolution Using Stack-of-Stars Sampling and KWIC Reconstruction

Application of quantitative dynamic contrast-enhanced (DCE) MRI in mouse models of abdominal cancer is challenging due to the effects of RF inhomogeneity, image corruption from rapid respiratory motion and the need for high spatial and temporal resolutions. Here we demonstrate a DCE protocol optimized for such applications. The method consists of three acquisitions: (1) actual flip-angle B₁ mapping, (2) variable flip-angle T₁ mapping and (3) acquisition of the DCE series using a motion-robust radial strategy with k-space weighted image contrast (KWIC) reconstruction. All three acquisitions employ spoiled radial imaging with stack-of-stars sampling (SoS) and golden-angle increments between the views. This scheme is shown to minimize artifacts due to respiratory motion while simultaneously facilitating view-sharing image reconstruction for the dynamic series. The method is demonstrated in a genetically engineered mouse model of pancreatic ductal adenocarcinoma and yielded mean perfusion parameters of K^trans = 0.23 ± 0.14 min⁻¹ and v_e = 0.31 ± 0.17 (n = 22) over a wide range of tumor sizes. The SoS-sampled DCE method is shown to produce artifact-free images with good SNR leading to robust estimation of DCE parameters.

VERDICT MRI for radiation treatment response assessment in neuroendocrine tumors

Noninvasive methods to study changes in tumor microstructure enable early assessment of treatment response and thus facilitate personalized treatment. The aim of this study was to evaluate the diffusion MRI model, Vascular, Extracellular and Restricted Diffusion for Cytometry in Tumors (VERDICT), for early response assessment to external radiation treatment and to compare the results with those of more studied sets of parameters derived from diffusion-weighted MRI data. Mice xenografted with human small intestine tumors were treated with external radiation treatment, and diffusion MRI experiments were performed on the day before and up to 2 weeks after treatment. The diffusion models VERDICT, ADC, IVIM, and DKI were fitted to MRI data, and the treatment response of each tumor was calculated based on pretreatment tumor growth and post-treatment tumor volume regression. Linear regression and correlation analysis were used to evaluate each model and their respective parameters for explaining the treatment response. VERDICT analysis showed significant changes from day -1 to day 3 for the intracellular and extracellular volume fraction, as well as the cell radius index (p < 0.05; Wilcoxon signed-rank test). The strongest correlation between the diffusion model parameters and the tumor treatment response was seen for the ADC, kurtosis-corrected diffusion coefficient, and intracellular volume fraction on day 3 (τ = 0.47, 0.52, and -0.49, respectively, p < 0.05; Kendall rank correlation coefficient). Of all the tested models, VERDICT held the strongest explanatory value for the tumor treatment response on day 3 (R²  = 0.75, p < 0.01; linear regression). In conclusion, VERDICT has potential for early assessment of external radiation treatment and may provide further insights into the underlying biological effects of radiation on tumor tissue. In addition, the results suggest that the time window for assessment of treatment response using dMRI may be narrow.

Know thy tumour: Biomarkers to improve treatment of molecular radionuclide therapy

Molecular radionuclide therapy (MRT) is an effective treatment for both localised and disseminated tumours. Biomarkers can be used to identify potential subtypes of tumours that are known to respond better to standard MRT protocols. These enrolment-based biomarkers can further be used to develop dose-response relationships using image-based dosimetry within these defined subtypes. However, the biological identity of the cancers treated with MRT are commonly not well-defined, particularly for neuroendocrine neoplasms. The biological heterogeneity of such cancers has hindered the establishment of dose-responses and minimum tumour dose thresholds. Biomarkers could also be used to determine normal tissue MRT dose limits and permit greater injected doses of MRT in patients. An alternative approach is to understand the repair capacity limits of tumours using radiobiology-based biomarkers within and outside patient cohorts currently treated with MRT. It is hoped that by knowing more about tumours and how they respond to MRT, biomarkers can provide needed dimensionality to image-based biodosimetry to improve MRT with optimized protocols and personalised therapies.

Hyperfractionated Treatment with 177Lu-Octreotate Increases Tumor Response in Human Small-Intestine Neuroendocrine GOT1 Tumor Model

Simple Summary

Neuroendocrine tumors are slow growing and initially associated with vague symptoms and, therefore, often spread in the patient’s body at diagnosis, leading to a poor prognosis without means of curation through surgery. Although tumor-targeting treatments exist and are used in clinics, they are not fully optimized. The aim of this study was to test different dosages and time intervals of the radioactive pharmaceutical ¹⁷⁷Lu-octreotate. We found that dividing a dosage into several portions and administering it at short time intervals resulted in a stronger tumor reduction and/or prolonged time for regrowth in mice than if given as a single dose. The biggest differences were seen in the lower dosage levels of the study. The findings indicate that there is clear room for improvements in the treatment of neuroendocrine tumors with ¹⁷⁷Lu-octreotate.

Abstract

Radionuclide treatment of patients with neuroendocrine tumors has advanced in the last decades with favorable results using ¹⁷⁷Lu-octreotate. However, the gap between the high cure rate in animal studies vs. patient studies indicates a potential to increase the curation of patients. The aim of this study was to investigate the tumor response for different fractionation schemes with ¹⁷⁷Lu-octreotate. BALB/c mice bearing a human small-intestine neuroendocrine GOT1 tumor were either mock treated with saline or injected intravenously with a total of 30–120 MBq of ¹⁷⁷Lu-octreotate: 1 × 30, 2 × 15, 1 × 60, 2 × 30, 1 × 120, 2 × 60, or 3 × 40 MBq. The tumor volume was measured twice per week until the end of the experiment. The mean tumor volume for mice that received 2 × 15 = 30 and 1 × 30 MBq ¹⁷⁷Lu-octreotate was reduced by 61% and 52%, respectively. The mean tumor volume was reduced by 91% and 44% for mice that received 2 × 30 = 60 and 1 × 60 MBq ¹⁷⁷Lu-octreotate, respectively. After 120 MBq ¹⁷⁷Lu-octreotate, given as 1–3 fractions, the mean tumor volume was reduced by 91–97%. Multiple fractions resulted in delayed regrowth and prolonged overall survival by 20–25% for the 120 MBq groups and by 45% for lower total activities, relative to one fraction. The results indicate that fractionation and hyperfractionation of ¹⁷⁷Lu-octreotate are beneficial for tumor reduction and prolongs the time to regrowth.

Joint total variation-based reconstruction of multiparametric magnetic resonance images for mapping tissue types

Multispectral analysis of coregistered multiparametric magnetic resonance (MR) images provides a powerful method for tissue phenotyping and segmentation. Acquisition of a sufficiently varied set of multicontrast MR images and parameter maps to objectively define multiple normal and pathologic tissue types can require long scan times. Accelerated MRI on clinical scanners with multichannel receivers exploits techniques such as parallel imaging, while accelerated preclinical MRI scanning must rely on alternate approaches. In this work, tumor-bearing mice were imaged at 7 T to acquire k-space data corresponding to a series of images with varying T1-, T2- and T2*-weighting. A joint reconstruction framework is proposed to reconstruct a series of T1-weighted images and corresponding T1 maps simultaneously from undersampled Cartesian k-space data. The ambiguity introduced by undersampling was resolved by using model-based constraints and structural information from a reference fully sampled image as the joint total variation prior. This process was repeated to reconstruct T2-weighted and T2*-weighted images and corresponding maps of T2 and T2* from undersampled Cartesian k-space data. Validation of the reconstructed images and parameter maps was carried out by computing tissue-type maps, as well as maps of the proton density fat fraction (PDFF), proton density water fraction (PDwF), fat relaxation rate ( R2f*) and water relaxation rate ( R2w*) from the reconstructed data, and comparing them with ground truth (GT) equivalents. Tissue-type maps computed using 18% k-space data were visually similar to GT tissue-type maps, with dice coefficients ranging from 0.43 to 0.73 for tumor, fluid adipose and muscle tissue types. The mean T1 and T2 values within each tissue type computed using only 18% k-space data were within 8%-10% of the GT values from fully sampled data. The PDFF and PDwF maps computed using 27% k-space data were within 3%-15% of GT values and showed good agreement with the expected values for the four tissue types.

Current Applications and Future Development of Magnetic Resonance Fingerprinting in Diagnosis, Characterization, and Response Monitoring in Cancer

Magnetic resonance imaging (MRI) has enabled non-invasive cancer diagnosis, monitoring, and management in common clinical settings. However, inadequate quantitative analyses in MRI continue to limit its full potential and these often have an impact on clinicians' judgments. Magnetic resonance fingerprinting (MRF) has recently been introduced to acquire multiple quantitative parameters simultaneously in a reasonable timeframe. Initial retrospective studies have demonstrated the feasibility of using MRF for various cancer characterizations. Further trials with larger cohorts are still needed to explore the repeatability and reproducibility of the data acquired by MRF. At the moment, technical difficulties such as undesirable processing time or lack of motion robustness are limiting further implementations of MRF in clinical oncology. This review summarises the latest findings and technology developments for the use of MRF in cancer management and suggests possible future implications of MRF in characterizing tumour heterogeneity and response assessment.

Ex Vivo MR Histology and Cytometric Feature Mapping Connect Three-dimensional in Vivo MR Images to Two-dimensional Histopathologic Images of Murine Sarcomas

Purpose To establish a platform for quantitative tissue-based interpretation of cytoarchitecture features from tumor MRI measurements. Materials and Methods In a pilot preclinical study, multicontrast in vivo MRI of murine soft-tissue sarcomas in 10 mice, followed by ex vivo MRI of fixed tissues (termed MR histology), was performed. Paraffin-embedded limb cross-sections were stained with hematoxylin-eosin, digitized, and registered with MRI. Registration was assessed by using binarized tumor maps and Dice similarity coefficients (DSCs). Quantitative cytometric feature maps from histologic slides were derived by using nuclear segmentation and compared with registered MRI, including apparent diffusion coefficients and transverse relaxation times as affected by magnetic field heterogeneity (T2* maps). Cytometric features were compared with each MR image individually by using simple linear regression analysis to identify the features of interest, and the goodness of fit was assessed on the basis of R² values. Results Registration of MR images to histopathologic slide images resulted in mean DSCs of 0.912 for ex vivo MR histology and 0.881 for in vivo MRI. Triplicate repeats showed high registration repeatability (mean DSC, >0.9). Whole-slide nuclear segmentations were automated to detect nuclei on histopathologic slides (DSC = 0.8), and feature maps were generated for correlative analysis with MR images. Notable trends were observed between cell density and in vivo apparent diffusion coefficients (best line fit: R² = 0.96, P < .001). Multiple cytoarchitectural features exhibited linear relationships with in vivo T2* maps, including nuclear circularity (best line fit: R² = 0.99, P < .001) and variance in nuclear circularity (best line fit: R² = 0.98, P < .001). Conclusion An infrastructure for registering and quantitatively comparing in vivo tumor MRI with traditional histologic analysis was successfully implemented in a preclinical pilot study of soft-tissue sarcomas. Keywords: MRI, Pathology, Animal Studies, Tissue Characterization Supplemental material is available for this article. © RSNA, 2021.

Early changes in intravoxel incoherent motion MRI parameters can potentially predict response to chemoradiotherapy in rectal cancer: An animal study

Imaging-based approaches for early predicting response of rectal cancer to neoadjuvant chemoradiotherapy remain an ongoing-challenge. In this study, we aimed to monitor the changes of intravoxel incoherent motion (IVIM) MRI parameters during the early post-treatment period in mouse models of human rectal carcinoma, and to test whether these changes relate to the final response. Thirty-two mice with subcutaneous-tumor were randomly divided into control (n = 11), chemoradiotherapy (n = 10) and chemotherapy (n = 11) group. Tumors were monitored by IVIM at day 0, 3, 7, 9 after treatment. The final tumor response was determined by tumor remission-rate and necrosis scores. The results indicated that within 9 days after treatment, D values increased in both treated groups, but remained stable in control group. D values were significantly higher in chemotherapy group at day 7 and in each treated group at day 9 than in control group (day 7, p = 0.004; day 9: p = 0.011 and 0.009, respectively). D* values decreased in treated groups, and showed significantly lower than in control group at day 7 (p < 0.001). There was a strong positive correlation between delta D*% (D*_{day0 - day7}/D*_day0) and tumor remission rate (r = 0.707, p < 0.001), and a mild negative correlation between delta D% and tumor necrosis scores (r = -0.526, p = 0.014). D and D* values in rectal carcinoma xenograft models appeared tendency change during the early post-treatment period. In conclusion, early changes of D and D* values may have potential for predicting the final efficacy of chemoradiotherapy.

Apparent diffusion coefficient for the prediction of tumor response to neoadjuvant chemo-radiotherapy in locally advanced rectal cancer

BACKGROUND

Patients with locally advanced rectal cancer generally have different response rates to preoperative neoadjuvant chemo-radiotherapy. This study investigated the value of the apparent diffusion coefficient (ADC) as a predictor to forecast the response to neoadjuvant chemo-radiotherapy in patients with locally advanced rectal cancer.

METHODS

Ninety-one locally advanced rectal cancer patients who underwent neoadjuvant chemo-radiotherapy between 2015 and 2018 were enrolled. Diffusion-weighted magnetic resonance imaging was performed before treatment and within 4 weeks after the completion of neoadjuvant chemo-radiotherapy. Mean ADC values of regions of interest were evaluated by two radiologists. The tumor response was evaluated according to RESCIST 1.1. The cut-off value for the mean ADC and increasing percentage (ΔADC%) after neoadjuvant chemo-radiotherapy was calculated using the receiver operating characteristic curve. The response rate of pre-ADC and ΔADC% above/below the cut-off values was determined using the chi-square test, respectively. Primary tumor progression-free survival (PFS) was analyzed using the Kaplan-Meier method, based on the pre-ADC and ΔADC% cut-off values.

RESULTS

The cut-off value of mean pre-ADC and ΔADC% was 0.94 × 10-3 mm2/s (80.36% sensitivity, 74.29% specificity) and 26.0% (73.21% sensitivity, 77.14% specificity), respectively. Lower mean pre-ADC values were related to a better response rate (83.3% vs 29.7%, P < 0.001) and PFS (26.12 vs 17.70 months, P = 0.004). ΔADC% above the cut-off value was also related to a better response rate (83.7% vs 35.7%, P < 0.001) and PFS (26.93 vs 15.65 months, P = 0.034).

CONCLUSIONS

The mean ADC pre-treatment value and ΔADC% were potential predictors for the tumor response in locally advanced rectal cancer patients treated with neoadjuvant chemo-radiotherapy.