Non-Invasive Assessment of Hypoxia and Neovascularization with MRI for Identification of Aggressive Breast Cancer

Assessment of hypoxia and its dynamic evolution in glioblastoma via qBOLD MRI: a comparative study with metformin treatment

BACKGROUND

To investigate the accuracy of quantitative blood oxygen level-dependent (qBOLD) magnetic resonance imaging (MRI) in identifying hypoxia within glioblastoma and explore dynamic changes in oxygenation status of glioblastoma with and without metformin administration.

METHODS

Three healthy and seven C6-bearing rats underwent 7-T qBOLD MRI. Oxygen extraction fraction (OEF) and cerebral metabolism rate of O2 (CMRO2) were calculated from qBOLD data. Tumor tissues were stained using hypoxia-inducible factor-1 α (HIF-1 α ) and pimonidazole. The correlation between the hypoxia markers and corresponding qBOLD-based parameters was analyzed. Six C6-bearing rats were divided into metformin-treated and control groups for a longitudinal study of qBOLD imaging changes, with scans conducted on the 12th, 15th, and 18th day post-tumor implantation.

RESULTS

In healthy rats, gray matter showed higher values than white matter in T2, T2*, cerebral blood volume (CBV), and cerebral blood flow (CBF), whereas OEF was lower. Glioblastoma tissues exhibited elevated T2, T2*, CBV, and CBF but decreased OEF and CMRO2 relative to normal-appearing white matter. No significant correlation was found between staining scores from HIF-1 α and pimonidazole. T2* and T2 values were negatively correlated with pimonidazole scores in tumor regions. As the tumor progressed, OEF values increased with intra-tissue variations, whereas CMRO2 decreased. Metformin delayed the reduction of T2 and T2* values, with significant differences in OEF and CMRO2 values compared to controls on day 18.

CONCLUSION

T2* and T2 values were significantly associated with the hypoxia status in glioma. Metformin could potentially mitigate the progression of hypoxia in glioblastoma, which can be tracked by qBOLD parameters.

RELEVANCE STATEMENT

This study demonstrates the potential of qBOLD parameters in assessing glioma dynamic oxygen metabolism and the efficacy of metformin as an anti-hypoxic agent, providing insights into improving glioblastoma treatment strategies.

KEY POINTS

The study investigated qBOLD imaging's accuracy in identifying hypoxia status within glioblastoma. qBOLD effectively assesses hypoxia and its dynamic evolution in glioblastoma. qBOLD parameters assist in identifying a suitable patient demographic for metformin treatment.

[Multiparametric magnetic resonance imaging of the breast : What can we expect from the future?]

BACKGROUND

The combination of different MRI methods is described as multiparametric MRI (mpMRI) and plays a significant role in breast cancer diagnostics. Currently, mpMRI includes contrast-enhanced and diffusion-weighted MRI. For a more comprehensive characterization of the key processes involved in cancer development, additional MRI methods that capture functional processes at the cellular and molecular levels are necessary. In the context of preclinical studies, MRI methods that enable contrast-free evaluation of key processes at the metabolic and molecular levels are being developed for future clinical applications.

OBJECTIVES

What does multiparametric MRI in breast cancer look like in the future?

METHODS

Systematic literature analysis focusing on preclinical research with regard to mpMRI as well as development and modification of noninvasive MRI methods.

RESULTS

Some of the most promising MRI methods for the evaluation of breast cancer that can answer functional and metabolic questions are BOLD (blood oxygen level dependent), IVIM (intravoxel incoherent motion), DMI (deuterium metabolic imaging) and CEST (chemical exchange saturation transfer). A combination and, therefore, a multiparametric approach allows for a noninvasive differentiation of breast cancer subtypes and early detection of treatment response which is crucial for the future development of the disease.

CONCLUSION

Standardization of quantification methods as well as improvement and expansion of MRI methods enable such a multiparametric, functional, and metabolic evaluation of the tumor. Many of these are initially developed in preclinical settings before they can be translated into clinical practice.

Affinity of PET-MRI Tracers for Hypoxic Cells in Breast Cancer: A Systematic Review

Tumour hypoxia is a known microenvironmental culprit for treatment resistance, tumour recurrence and promotion of metastatic spread. Despite the long-known existence of this factor within the tumour milieu, hypoxia is still one of the greatest challenges in cancer management. The transition from invasive and less reliable detection methods to more accurate and non-invasive ways to identify and quantify hypoxia was a long process that eventually led to the promising results showed by functional imaging techniques. Hybrid imaging, such as PET-CT, has the great advantage of combining the structural or anatomical image (offered by CT) with the functional or metabolic one (offered by PET). However, in the context of hypoxia, it is only the PET image taken after appropriate radiotracer administration that would supply hypoxia-specific information. To overcome this limitation, the development of the latest hybrid imaging systems, such as PET-MRI, enables a synergistic approach towards hypoxia imaging, with both methods having the potential to provide functional information on the tumour microenvironment. This study is designed as a systematic review of the literature on the newest developments of PET-MRI for the imaging of hypoxic cells in breast cancer. The analysis includes the affinity of various PET-MRI tracers for hypoxia in this patient group as well as the correlations between PET-specific and MRI-specific parameters, to offer a broader view on the potential for the widespread clinical implementation of this hybrid imaging technique.

Halofuginone-guided nano-local therapy: Nano-thermosensitive hydrogels for postoperative metastatic canine mammary carcinoma with scar removal

In female dogs, the highest morbidity and mortality rates cancer are the result of mammary adenocarcinoma, which presents with metastases in the lung. Other than early surgical removal, however, no special methods are available to treat mammary adenocarcinoma. Because human breast cancer and canine mammary carcinoma share clinical characteristics and heterogeneity, the canine model is a suitable spontaneous tumor model for breast cancer in humans. In this study, the physical swelling method was used to prepare halofuginone-loaded D-α-tocopherol polyethylene glycol 1000 succinate (TPGS) polymer micelles nano-thermosensitive hydrogels (HTPM-gel). Furthermore, HTPM-gel was investigated via characterization, morphology, properties such as swelling experiment and in vitro release with reflecting its splendid nature. Moreover, HTPM-gel was further examined its capability to anti-proliferation, anti-migration, and anti-invasion. Ultimately, HTPM-gel was investigated for its in vivo anticancer activity in the post-operative metastatic and angiogenic canine mammary carcinoma. HTPM-gel presented spherical under transmission electron microscope (TEM) and represented grid structure under scanning electron microscope (SEM), with hydrodynamic diameter (HD) of 20.25 ± 2.5 nm and zeta potential (ZP) of 15.10 ± 1.82 mV. Additionally, HTPM-gel own excellent properties comprised of pH-dependent swelling behavior, sustained release behavior. To impede the migration, invasion, and proliferation of CMT-U27 cells, we tested the efficacy of HTPM-gel. Evaluation of in vivo anti-tumor efficacy demonstrates HTPM-gel exhibit a splendid anti-metastasis and anti-angiogenic ability, with exhibiting ideal biocompatibility. Notably, HTPM-gel also inhibited the scar formation in the healing process after surgery. In summary, HTPM-gel exhibited anti-metastasis and anti-angiogenic and scar repair features. According to the results of this study, HTPM-gel has encouraging clinical potential to treat tumors with multifunctional hydrogel.

Non-Contrast-Enhanced Multiparametric MRI of the Hypoxic Tumor Microenvironment Allows Molecular Subtyping of Breast Cancer: A Pilot Study

Tumor neoangiogenesis is an important hallmark of cancer progression, triggered by alternating selective pressures from the hypoxic tumor microenvironment. Non-invasive, non-contrast-enhanced multiparametric MRI combining blood-oxygen-level-dependent (BOLD) MRI, which depicts blood oxygen saturation, and intravoxel-incoherent-motion (IVIM) MRI, which captures intravascular and extravascular diffusion, can provide insights into tumor oxygenation and neovascularization simultaneously. Our objective was to identify imaging markers that can predict hypoxia-induced angiogenesis and to validate our findings using multiplexed immunohistochemical analyses. We present an in vivo study involving 36 female athymic nude mice inoculated with luminal A, Her2+, and triple-negative breast cancer cells. We used a high-field 9.4-tesla MRI system for imaging and subsequently analyzed the tumors using multiplex immunohistochemistry for CD-31, PDGFR-β, and Hif1-α. We found that the hyperoxic-BOLD-MRI-derived parameter ΔR2* discriminated luminal A from Her2+ and triple-negative breast cancers, while the IVIM-derived parameter fIVIM discriminated luminal A and Her2+ from triple-negative breast cancers. A comprehensive analysis using principal-component analysis of both multiparametric MRI- and mpIHC-derived data highlighted the differences between triple-negative and luminal A breast cancers. We conclude that multiparametric MRI combining hyperoxic BOLD MRI and IVIM MRI, without the need for contrast agents, offers promising non-invasive markers for evaluating hypoxia-induced angiogenesis.

ncRNA-mediated ceRNA regulatory network: Transcriptomic insights into breast cancer progression and treatment strategies

With the rapid development of next-generation sequencing technology, several studies have shown that ncRNAs can act as competitive endogenous RNAs (ceRNAs) and are involved in various biological processes, such as proliferation, differentiation, apoptosis, and migration of breast cancer (BC) cells, and plays an important role in BC progression as a molecular target for its diagnosis, treatment, prognosis, and differentiation of subtypes and age groups of BC patients. Based on the description of ceRNA-related biological functions, this study screened and sorted the sequencing analysis and experimental verification conclusions of BC-related ceRNAs and found that the ncRNAs mediated ceRNA networks can promote the development of BC by promoting the expression of genes related to BC proliferation, drug resistance, and apoptosis, inducing the production of epithelial-mesenchymal transition (EMT) to promote metastasis and activating cancer-related signaling pathways.

Measurement of Cerebral Oxygen Extraction Fraction Using Quantitative BOLD Approach: A Review

Quantification of brain oxygenation and metabolism, both of which are indicators of the level of brain activity, plays a vital role in understanding the cerebral perfusion and the pathophysiology of brain disorders. Magnetic resonance imaging (MRI), a widely used clinical imaging technique, which is very sensitive to magnetic susceptibility, has the possibility of substituting positron emission tomography (PET) in measuring oxygen metabolism. This review mainly focuses on the quantitative blood oxygenation level-dependent (qBOLD) method for the evaluation of oxygen extraction fraction (OEF) in the brain. Here, we review the theoretic basis of qBOLD, as well as existing acquisition and quantification methods. Some published clinical studies are also presented, and the pros and cons of qBOLD method are discussed as well.

Molecular Imaging of Oxygenation Changes during Immunotherapy in Combination with Paclitaxel in Triple Negative Breast Cancer

Hypoxia is a common feature of the tumor microenvironment, including that of triple-negative breast cancer (TNBC), an aggressive breast cancer subtype with a high five-year mortality rate. Using [18F]-fluoromisonidazole (FMISO) positron emission tomography (PET) imaging, we aimed to monitor changes in response to immunotherapy (IMT) with chemotherapy in TNBC. TNBC-tumor-bearing mice received paclitaxel (PTX) ± immune checkpoint inhibitors anti-programmed death 1 and anti-cytotoxic T-lymphocyte 4. FMISO-PET imaging was performed on treatment days 0, 6, and 12. Max and mean standard uptake values (SUVmax and SUVmean, respectively), histological analyses, and flow cytometry results were compared. FMISO-PET imaging revealed differences in tumor biology between treatment groups prior to tumor volume changes. 4T1 responders showed SUVmean 1.6-fold lower (p = 0.02) and 1.8-fold lower (p = 0.02) than non-responders on days 6 and 12, respectively. E0771 responders showed SUVmean 3.6-fold lower (p = 0.001) and 2.7-fold lower (p = 0.03) than non-responders on days 6 and 12, respectively. Immunohistochemical analyses revealed IMT plus PTX decreased hypoxia and proliferation and increased vascularity compared to control. Combination IMT/PTX recovered the loss of CD4+ T-cells observed with single-agent therapies. PET imaging can provide timely, longitudinal data on the TNBC tumor microenvironment, specifically intratumoral hypoxia, predicting therapeutic response to IMT plus chemotherapy.

Differentiation of Glioblastoma and Brain Metastases by MRI-Based Oxygen Metabolomic Radiomics and Deep Learning

Glioblastoma (GB) and brain metastasis (BM) are the most frequent types of brain tumors in adults. Their therapeutic management is quite different and a quick and reliable initial characterization has a significant impact on clinical outcomes. However, the differentiation of GB and BM remains a major challenge in today's clinical neurooncology due to their very similar appearance in conventional magnetic resonance imaging (MRI). Novel metabolic neuroimaging has proven useful for improving diagnostic performance but requires artificial intelligence for implementation in clinical routines. Here; we investigated whether the combination of radiomic features from MR-based oxygen metabolism ("oxygen metabolic radiomics") and deep convolutional neural networks (CNNs) can support reliably pre-therapeutic differentiation of GB and BM in a clinical setting. A self-developed one-dimensional CNN combined with radiomic features from the cerebral metabolic rate of oxygen (CMRO₂) was clearly superior to human reading in all parameters for classification performance. The radiomic features for tissue oxygen saturation (mitoPO₂; i.e., tissue hypoxia) also showed better diagnostic performance compared to the radiologists. Interestingly, both the mean and median values for quantitative CMRO₂ and mitoPO₂ values did not differ significantly between GB and BM. This demonstrates that the combination of radiomic features and DL algorithms is more efficient for class differentiation than the comparison of mean or median values. Oxygen metabolic radiomics and deep neural networks provide insights into brain tumor phenotype that may have important diagnostic implications and helpful in clinical routine diagnosis.

Radiophysiomics: Brain Tumors Classification by Machine Learning and Physiological MRI Data

The precise initial characterization of contrast-enhancing brain tumors has significant consequences for clinical outcomes. Various novel neuroimaging methods have been developed to increase the specificity of conventional magnetic resonance imaging (cMRI) but also the increased complexity of data analysis. Artificial intelligence offers new options to manage this challenge in clinical settings. Here, we investigated whether multiclass machine learning (ML) algorithms applied to a high-dimensional panel of radiomic features from advanced MRI (advMRI) and physiological MRI (phyMRI; thus, radiophysiomics) could reliably classify contrast-enhancing brain tumors. The recently developed phyMRI technique enables the quantitative assessment of microvascular architecture, neovascularization, oxygen metabolism, and tissue hypoxia. A training cohort of 167 patients suffering from one of the five most common brain tumor entities (glioblastoma, anaplastic glioma, meningioma, primary CNS lymphoma, or brain metastasis), combined with nine common ML algorithms, was used to develop overall 135 classifiers. Multiclass classification performance was investigated using tenfold cross-validation and an independent test cohort. Adaptive boosting and random forest in combination with advMRI and phyMRI data were superior to human reading in accuracy (0.875 vs. 0.850), precision (0.862 vs. 0.798), F-score (0.774 vs. 0.740), AUROC (0.886 vs. 0.813), and classification error (5 vs. 6). The radiologists, however, showed a higher sensitivity (0.767 vs. 0.750) and specificity (0.925 vs. 0.902). We demonstrated that ML-based radiophysiomics could be helpful in the clinical routine diagnosis of contrast-enhancing brain tumors; however, a high expenditure of time and work for data preprocessing requires the inclusion of deep neural networks.

Lattice or Oxygen-Guided Radiotherapy: What If They Converge? Possible Future Directions in the Era of Immunotherapy

Palliative radiotherapy has a great role in the treatment of large tumor masses. However, treating a bulky disease could be difficult, especially in critical anatomical areas. In daily clinical practice, short course hypofractionated radiotherapy is delivered in order to control the symptomatic disease. Radiation fields generally encompass the entire tumor mass, which is homogeneously irradiated. Recent technological advances enable delivering a higher radiation dose in small areas within a large mass. This goal, previously achieved thanks to the GRID approach, is now achievable using the newest concept of LATTICE radiotherapy (LT-RT). This kind of treatment allows exploiting various radiation effects, such as bystander and abscopal effects. These events may be enhanced by the concomitant use of immunotherapy, with the latter being ever more successfully delivered in cancer patients. Moreover, a critical issue in the treatment of large masses is the inhomogeneous intratumoral distribution of well-oxygenated and hypo-oxygenated areas. It is well known that hypoxic areas are more resistant to the killing effect of radiation, hence the need to target them with higher aggressive doses. This concept introduces the "oxygen-guided radiation therapy" (OGRT), which means looking for suitable hypoxic markers to implement in PET/CT and Magnetic Resonance Imaging. Future treatment strategies are likely to involve combinations of LT-RT, OGRT, and immunotherapy. In this paper, we review the radiobiological rationale behind a potential benefit of LT-RT and OGRT, and we summarize the results reported in the few clinical trials published so far regarding these issues. Lastly, we suggest what future perspectives may emerge by combining immunotherapy with LT-RT/OGRT.