Incorporating Oxygen-Enhanced MRI into Multi-Parametric Assessment of Human Prostate Cancer

Development and validation of a nomogram incorporating multi-parametric MRI and hematological indicators for discriminating benign from malignant central prostatic nodules: a retrospective analysis

BACKGROUND

Prostate cancer poses a significant risk to men's health. In this study, a model for differentiating benign and malignant nodules in the central region of the prostate was constructed by combining multi-parametric MRI and hematological lab values.

METHODS

This retrospective study analyzed the data acquired from Lianyungang First People's Hospital and The Second Affiliated Hospital of Hainan Medical College from January 2018 to December 2021. We included 310 MRI-confirmed prostatic nodule patients. The data were split into a training set (260 cases) and an external validation set (50 cases), with the latter exclusively from The Second Affiliated Hospital of Hainan Medical College to test the model's generalizability. Univariate and multivariate logistic regression identified critical measurements for differentiating prostate cancer (PCa) from benign prostatic hyperplasia (BPH), which were then integrated into a nomogram model.

RESULTS

The key indicators determined by multivariate logistic regression analysis included apparent diffusion coefficient (ADC), standard deviation (StDev), neutrophil to lymphocyte ratio (NLR), and prostate specific antigen (PSA). The nomogram's performance, as indicated by the area under the curve (AUC), was 0.844 (95% CI: 0.811-0.938) in the training set and 0.818 (95% CI: 0.644-0.980) in the external validation set. Calibration and decision curves demonstrated that the nomogram was well-calibrated and could serve as an effective tool in clinical practice.

CONCLUSION

The nomogram model based on ADC, StDev, NLR and PSA may be helpful to identify PCa and BPH.

Towards tumour hypoxia imaging: Incorporating relative oxygen extraction fraction mapping of prostate with multi-parametric quantitative MRI on a 1.5T MR-linac

Hypoxia plays a central role in tumour radioresistance. Reliable tumour hypoxia imaging would allow the monitoring of tumour response and a more personalized adaptation of radiotherapy planning. Here, we showed a proof of concept of the feasibility and repeatability of relative oxygen extraction fraction (rOEF) mapping of prostate using multi-parametric quantitative MRI (qMRI) achieved for the first time on a 1.5T MR-linac. T2, T2* relaxation times maps, and intra-voxel incoherent motion (IVIM) parametric maps mapping were computed on a 29 years old healthy volunteer. R2' and rOEF maps were calculated based on a multi-parametric model. Long-term repeatability and repeatability coefficient (RC) were determined for each parameter according to QIBA recommendations. Mean values for the entire healthy prostate were 0.99 ± 0.14 × 10-3  mm/s2 , 81 ± 2.1 × 10-3  mm/s2 , 21.6 ± 3.6%, 92.7 ± 19.7 ms and 62.4 ± 17.3 ms for Dslow , Dfast , f, T2 and T2*, respectively. R2' and rOEF in the prostate were 6.1 ± 3.4 s-1 and 18.2 ± 10.1% respectively. The RC of rOEF was 4.43%. Long-term repeatability of quantitative parameters based on a test-retest ranged from 2 to 18%. qMRI parameters are measurable and repeatable on 1.5T MR LINAC. From T2, T2* and IVIM parameters maps, we were able to obtain a rOEF mapping of the prostate. These results are the first step to a non-invasive imaging of tumour hypoxia during radiotherapy leading to a biological image-guided adaptive radiotherapy.

Advances in PET and MRI imaging of tumor hypoxia

Tumor hypoxia is a complex and evolving phenomenon both in time and space. Molecular imaging allows to approach these variations, but the tracers used have their own limitations. PET imaging has the disadvantage of low resolution and must take into account molecular biodistribution, but has the advantage of high targeting accuracy. The relationship between the signal in MRI imaging and oxygen is complex but hopefully it would lead to the detection of truly oxygen-depleted tissue. Different ways of imaging hypoxia are discussed in this review, with nuclear medicine tracers such as [¹⁸F]-FMISO, [¹⁸F]-FAZA, or [⁶⁴Cu]-ATSM but also with MRI techniques such as perfusion imaging, diffusion MRI or oxygen-enhanced MRI. Hypoxia is a pejorative factor regarding aggressiveness, tumor dissemination and resistance to treatments. Therefore, having accurate tools is particularly important.

Radiomic Analysis for Pretreatment Prediction of Recurrence Post-Radiotherapy in Cervical Squamous Cell Carcinoma Cancer

Background: The current study aims to predict the recurrence of cervical cancer patients treated with radiotherapy from radiomics features on pretreatment T1- and T2-weighted MR images. Methods: A total of 89 patients were split into model training (63 patients) and model testing (26 patients). The predictors of recurrence were selected using the least absolute shrinkage and selection operator (LASSO) regression. The machine learning used neural network classifiers. Results: Using LASSO analysis of radiomics, we found 25 features from the T1-weighted and 4 features from T2-weighted MR images, respectively. The accuracy was highest with the combination of T1- and T2-weighted MR images. The model performances with T1- or T2-weighted MR images were 86.4% or 89.4% accuracy, 74.9% or 38.1% sensitivity, 81.8% or 72.2% specificity, and 0.89 or 0.69 of the area under the curve (AUC). The model performance with the combination of T1- and T2-weighted MR images was 93.1% accuracy, 81.6% sensitivity, 88.7% specificity, and 0.94 of AUC. Conclusions: The radiomics analysis with T1- and T2-weighted MR images could highly predict the recurrence of cervix cancer after radiotherapy. The variation of the distribution and the difference in the pixel number at the peripheral and the center were important predictors.

Virtual Biopsy in Soft Tissue Sarcoma. How Close Are We?

A shift in radiology to a data-driven specialty has been unlocked by synergistic developments in imaging biomarkers (IB) and computational science. This is advancing the capability to deliver "virtual biopsies" within oncology. The ability to non-invasively probe tumour biology both spatially and temporally would fulfil the potential of imaging to inform management of complex tumours; improving diagnostic accuracy, providing new insights into inter- and intra-tumoral heterogeneity and individualised treatment planning and monitoring. Soft tissue sarcomas (STS) are rare tumours of mesenchymal origin with over 150 histological subtypes and notorious heterogeneity. The combination of inter- and intra-tumoural heterogeneity and the rarity of the disease remain major barriers to effective treatments. We provide an overview of the process of successful IB development, the key imaging and computational advancements in STS including quantitative magnetic resonance imaging, radiomics and artificial intelligence, and the studies to date that have explored the potential biological surrogates to imaging metrics. We discuss the promising future directions of IBs in STS and illustrate how the routine clinical implementation of a virtual biopsy has the potential to revolutionise the management of this group of complex cancers and improve clinical outcomes.

Blood oxygenation level-dependent MRI at 3T for differentiating prostate cancer from benign tissue: a preliminary experience

OBJECTIVE

Blood oxygenation-level dependent (BOLD) MRI may identify or quantify the regional distribution of hypoxia within a tumor. We aimed to evaluate the feasibility of BOLD MRI at 3 T in differentiating prostate cancer from benign tissue.

METHODS

A total of 145 patients with biopsy-proven prostate cancer underwent BOLD MRI at 3 T. BOLD MRI was performed using a multiple fast field echo sequence to acquire 12 T₂*-weighted images. The R2* value (rate of relaxation, s^-1) was measured in the index tumor, and benign peripheral (PZ) and transition zone (TZ), and the results were compared. The variability of R2* measurements was evaluated.

RESULTS

Tumor R2* values (25.95 s^-1) were significantly different from the benign PZ (27.83 s^-1) and benign TZ (21.66 s^-1) (p < 0.001). For identifying the tumor, the area under the receiver operating characteristic of R2* was 0.606, with an optimal cut-off value of 22.8 s^-1 resulting in 73.8% sensitivity and 52% specificity. In the Bland-Altman test, the mean differences in R2* values were 8.5% for tumors, 13.3% for benign PZ, and 6.8% for benign TZ. No associations between tumor R2* value and Gleason score, age, prostate volume, prostate-specific antigen, or tumor size.

CONCLUSION

BOLD MRI at 3 T appears to be a feasible tool for differentiating between prostate cancer and benign tissue. However, further studies are required for a direct clinical application.

ADVANCES IN KNOWLEDGE

The R2* values are significantly different among prostate cancer, benign PZ, and benign TZ.

Textured-Based Deep Learning in Prostate Cancer Classification with 3T Multiparametric MRI: Comparison with PI-RADS-Based Classification

The current standardized scheme for interpreting MRI requires a high level of expertise and exhibits a significant degree of inter-reader and intra-reader variability. An automated prostate cancer (PCa) classification can improve the ability of MRI to assess the spectrum of PCa. The purpose of the study was to evaluate the performance of a texture-based deep learning model (Textured-DL) for differentiating between clinically significant PCa (csPCa) and non-csPCa and to compare the Textured-DL with Prostate Imaging Reporting and Data System (PI-RADS)-based classification (PI-RADS-CLA), where a threshold of PI-RADS ≥ 4, representing highly suspicious lesions for csPCa, was applied. The study cohort included 402 patients (60% (n = 239) of patients for training, 10% (n = 42) for validation, and 30% (n = 121) for testing) with 3T multiparametric MRI matched with whole-mount histopathology after radical prostatectomy. For a given suspicious prostate lesion, the volumetric patches of T2-Weighted MRI and apparent diffusion coefficient images were cropped and used as the input to Textured-DL, consisting of a 3D gray-level co-occurrence matrix extractor and a CNN. PI-RADS-CLA by an expert reader served as a baseline to compare classification performance with Textured-DL in differentiating csPCa from non-csPCa. Sensitivity and specificity comparisons were performed using Mcnemar's test. Bootstrapping with 1000 samples was performed to estimate the 95% confidence interval (CI) for AUC. CIs of sensitivity and specificity were calculated by the Wald method. The Textured-DL model achieved an AUC of 0.85 (CI [0.79, 0.91]), which was significantly higher than the PI-RADS-CLA (AUC of 0.73 (CI [0.65, 0.80]); p < 0.05) for PCa classification, and the specificity was significantly different between Textured-DL and PI-RADS-CLA (0.70 (CI [0.59, 0.82]) vs. 0.47 (CI [0.35, 0.59]); p < 0.05). In sub-analyses, Textured-DL demonstrated significantly higher specificities in the peripheral zone (PZ) and solitary tumor lesions compared to the PI-RADS-CLA (0.78 (CI [0.66, 0.90]) vs. 0.42 (CI [0.28, 0.57]); 0.75 (CI [0.54, 0.96]) vs. 0.38 [0.14, 0.61]; all p values < 0.05). Moreover, Textured-DL demonstrated a high negative predictive value of 92% while maintaining a high positive predictive value of 58% among the lesions with a PI-RADS score of 3. In conclusion, the Textured-DL model was superior to the PI-RADS-CLA in the classification of PCa. In addition, Textured-DL demonstrated superior performance in the specificities for the peripheral zone and solitary tumors compared with PI-RADS-based risk assessment.

Oxygen-Sensitive MRI: A Predictive Imaging Biomarker for Tumor Radiation Response?

PURPOSE

To develop a noninvasive prognostic imaging biomarker related to hypoxia to predict SABR tumor control.

METHODS AND MATERIALS

A total of 145 subcutaneous syngeneic Dunning prostate R3327-AT1 rat tumors were focally irradiated once using cone beam computed tomography guidance on a small animal irradiator at 225 kV. Various doses in the range of 0 to 100 Gy were administered, while rats breathed air or oxygen, and tumor control was assessed up to 200 days. Oxygen-sensitive magnetic resonance imaging (MRI) (T₁-weighted, ΔR₁, ΔR₂*) was applied to 79 of these tumors at 4.7 T to assess response to an oxygen gas breathing challenge on the day before irradiation as a probe of tumor hypoxia.

RESULTS

Increasing radiation dose in the range of 0 to 90 Gy enhanced tumor control of air-breathing rats with a TCD₅₀ estimated at 59.6 ± 1.5 Gy. Control was significantly improved at some doses when rats breathed oxygen during irradiation (eg, 40 Gy; P < .05), and overall there was a modest left shift in the control curve: TCD₅₀(oxygen) = 53.1 ± 3.1 Gy (P < .05 vs air). Oxygen-sensitive MRI showed variable response to oxygen gas breathing challenge; the magnitude of T₁-weighted signal response (%ΔSI) allowed stratification of tumors in terms of local control at 40 Gy. Tumors showing %ΔSI >0.922 with O₂-gas breathing challenge showed significantly better control at 40 Gy during irradiation while breathing oxygen (75% vs 0%, P < .01). In addition, increased radiation dose (50 Gy) substantially overcame resistance, with 50% control for poorly oxygenated tumors. Stratification of dose-response curves based on %ΔSI >0.922 revealed different survival curves, with TCD₅₀ = 36.2 ± 3.2 Gy for tumors responsive to oxygen gas breathing challenge; this was significantly less than the 54.7 ± 2.4 Gy for unresponsive tumors (P < .005), irrespective of the gas inhaled during tumor irradiation.

CONCLUSIONS

Oxygen-sensitive MRI allowed stratification of tumors in terms of local control at 40 Gy, indicating its use as a potential predictive imaging biomarker. Increasing dose to 50 Gy overcame radiation resistance attributable to hypoxia in 50% of tumors.

Deep Learning-Based Post-Processing of Real-Time MRI to Assess and Quantify Dynamic Wrist Movement in Health and Disease

While morphologic magnetic resonance imaging (MRI) is the imaging modality of choice for the evaluation of ligamentous wrist injuries, it is merely static and incapable of diagnosing dynamic wrist instability. Based on real-time MRI and algorithm-based image post-processing in terms of convolutional neural networks (CNNs), this study aims to develop and validate an automatic technique to quantify wrist movement. A total of 56 bilateral wrists (28 healthy volunteers) were imaged during continuous and alternating maximum ulnar and radial abduction. Following CNN-based automatic segmentations of carpal bone contours, scapholunate and lunotriquetral gap widths were quantified based on dedicated algorithms and as a function of wrist position. Automatic segmentations were in excellent agreement with manual reference segmentations performed by two radiologists as indicated by Dice similarity coefficients of 0.96 ± 0.02 and consistent and unskewed Bland–Altman plots. Clinical applicability of the framework was assessed in a patient with diagnosed scapholunate ligament injury. Considerable increases in scapholunate gap widths across the range-of-motion were found. In conclusion, the combination of real-time wrist MRI and the present framework provides a powerful diagnostic tool for dynamic assessment of wrist function and, if confirmed in clinical trials, dynamic carpal instability that may elude static assessment using clinical-standard imaging modalities.

Impact of Chronic Prostatitis on the PI-RADS Score 3: Proposal for the Addition of a Novel Binary Suffix

We examined the impact of chronic prostatitis on the diagnostic performance of multiparametric magnetic resonance imaging (mpMRI). In this retrospective study, 63 men underwent 3T mpMRI followed by MRI/ultrasound fusion biopsy to exclude/confirm clinically significant prostate cancer (csPCa). A total of 93 lesions were included for evaluation. Images were assessed by two radiologists. Prostatitis was graded visually on T2-weighted and contrast-enhanced sequences. The correlation of prostatitis features with the assigned Prostate Imaging Reporting and Data System (PI-RADS) and the presence of csPCa were assessed, and the clinical and functional imaging parameters for differentiating between prostatitis and significant tumors were examined. Histopathological analysis was used as the reference standard. The rate of PI-RADS 3 scores tended to be higher in the presence of radiologically severe prostatitis compared with no/discrete prostatitis (n = 52 vs. n = 9; p = 0.225). In severe prostatitis, csPCa was determined in only 7.7% (4/52) of PI-RADS 3 lesions. In severe chronic prostatitis, a binary prostatitis suffix (e.g., PI-RADS 3 i+ versus i−) within the radiological report may help assess the limitations of mpMRI interpretability because of severe prostatitis and avoid unnecessary biopsies. Mean apparent diffusion coefficient (ADC_mean) was the best marker (cutoff 0.93 × 10⁻³ mm²/s) to differentiate between csPCa/non csPCa in severe prostatitis.

Preclinical Applications of Multi-Platform Imaging in Animal Models of Cancer

In animal models of cancer, oncologic imaging has evolved from a simple assessment of tumor location and size to sophisticated multimodality exploration of molecular, physiologic, genetic, immunologic, and biochemical events at microscopic to macroscopic levels, performed noninvasively and sometimes in real time. Here, we briefly review animal imaging technology and molecular imaging probes together with selected applications from recent literature. Fast and sensitive optical imaging is primarily used to track luciferase-expressing tumor cells, image molecular targets with fluorescence probes, and to report on metabolic and physiologic phenotypes using smart switchable luminescent probes. MicroPET/single-photon emission CT have proven to be two of the most translational modalities for molecular and metabolic imaging of cancers: immuno-PET is a promising and rapidly evolving area of imaging research. Sophisticated MRI techniques provide high-resolution images of small metastases, tumor inflammation, perfusion, oxygenation, and acidity. Disseminated tumors to the bone and lung are easily detected by microCT, while ultrasound provides real-time visualization of tumor vasculature and perfusion. Recently available photoacoustic imaging provides real-time evaluation of vascular patency, oxygenation, and nanoparticle distributions. New hybrid instruments, such as PET-MRI, promise more convenient combination of the capabilities of each modality, enabling enhanced research efficacy and throughput.

Immune and metabolic checkpoints blockade: Dual wielding against tumors

Recent advances in cancer immunotherapy have raised hopes for treating cancers that are resistant to conventional therapies. Among the various immunotherapy methods, the immune checkpoint (IC) blockers were more promising and have paved their way to the clinic. Tumor cells induce the expression of ICs on the immune cells and derive them to a hyporesponsive exhausted phenotype. IC blockers could hinder immune exhaustion in the tumor microenvironment and reinvigorate immune cells for an efficient antitumor response. Despite the primary success of IC blockers in the clinic, the growing numbers of refractory cases require an in-depth study of the cellular and molecular mechanisms underlying IC expression and function. Immunometabolism is recently found to be a key factor in the regulation of immune responses. Activated or exhausted immune cells exploit different metabolic pathways. Tumor cells can suppress antitumor responses via immunometabolism alteration. Therefore, it is expected that concurrent targeting of ICs and immunometabolism pathways can cause immune cells to restore their antitumor activity. In this review, we dissected the reciprocal interactions of immune cell metabolism with expression and signaling of ICs in the tumor microenvironment. Recent findings on dual targeting of ICs and metabolic checkpoints have also been discussed.

Optical and magnetic resonance imaging approaches for investigating the tumour microenvironment: state-of-the-art review and future trends

The tumour microenvironment (TME) strongly influences tumorigenesis and metastasis. Two of the most characterized properties of the TME are acidosis and hypoxia, both of which are considered hallmarks of tumours as well as critical factors in response to anticancer treatments. Currently, various imaging approaches exist to measure acidosis and hypoxia in the TME, including magnetic resonance imaging (MRI), positron emission tomography and optical imaging. In this review, we will focus on the latest fluorescent-based methods for optical sensing of cell metabolism and MRI as diagnostic imaging tools applied both in vitro and in vivo. The primary emphasis will be on describing the current and future uses of systems that can measure intra- and extra-cellular pH and oxygen changes at high spatial and temporal resolution. In addition, the suitability of these approaches for mapping tumour heterogeneity, and assessing response or failure to therapeutics will also be covered.

MRI and Active Surveillance for Prostate Cancer

Since the introduction of Prostate-Specific Antigen (PSA) screening, prostate cancer mortality has decreased [...]

In vivo Monitoring of Oxygen Levels in Human Brain Tumor Between Fractionated Radiotherapy Using Oxygen-enhanced MR Imaging

BACKGROUND

It was known that the response of tumor cells to radiation is closely related to tissue oxygen level and fractionated radiotherapy allows reoxygenation of hypoxic tumor cells. Non-invasive mapping of tissue oxygen level may hold great importance in clinic.

OBJECTIVE

The aim of this study is to evaluate the role of oxygen-enhanced MR imaging in the detection of tissue oxygen levels between fractionated radiotherapy.

METHODS

A cohort of 10 patients with brain metastasis was recruited. Quantitative oxygen enhanced MR imaging was performed prior to, 30 minutes and 22 hours after first fractionated radiotherapy.

RESULTS

The ΔR1 (the difference of longitudinal relaxivity between 100% oxygen breathing and air breathing) increased in the ipsilateral tumor site and normal tissue by 242% and 152%, respectively, 30 minutes after first fractionated radiation compared to pre-radiation levels. Significant recovery of ΔR1 in the contralateral normal tissue (p < 0.05) was observed 22 hours compared to 30 minutes after radiation levels.

CONCLUSION

R1-based oxygen-enhanced MR imaging may provide a sensitive endogenous marker for oxygen changes in the brain tissue between fractionated radiotherapy.

Molecular and functional imaging insights into the role of hypoxia in cancer aggression

Hypoxia in cancers has evoked significant interest since 1955 when Thomlinson and Gray postulated the presence of hypoxia in human lung cancers, based on the observation of necrosis occurring at the diffusion limit of oxygen from the nearest blood vessel, and identified the implication of these observations for radiation therapy. Coupled with discoveries in 1953 by Gray and others that anoxic cells were resistant to radiation damage, these observations have led to an entire field of research focused on exploiting oxygenation and hypoxia to improve the outcome of radiation therapy. Almost 65 years later, tumor heterogeneity of nearly every parameter measured including tumor oxygenation, and the dynamic landscape of cancers and their microenvironments are clearly evident, providing a strong rationale for cancer personalized medicine. Since hypoxia is a major cause of extracellular acidosis in tumors, here, we have focused on the applications of imaging to understand the effects of hypoxia in tumors and to target hypoxia in theranostic strategies. Molecular and functional imaging have critically important roles to play in personalized medicine through the detection of hypoxia, both spatially and temporally, and by providing new understanding of the role of hypoxia in cancer aggressiveness. With the discovery of the hypoxia-inducible factor (HIF), the intervening years have also seen significant progress in understanding the transcriptional regulation of hypoxia-induced genes. These advances have provided the ability to silence HIF and understand the associated molecular and functional consequences to expand our understanding of hypoxia and its role in cancer aggressiveness. Most recently, the development of hypoxia-based theranostic strategies that combine detection and therapy are further establishing imaging-based treatment strategies for precision medicine of cancer.

Translating preclinical MRI methods to clinical oncology

The complexity of modern in vivo magnetic resonance imaging (MRI) methods in oncology has dramatically changed in the last 10 years. The field has long since moved passed its (unparalleled) ability to form images with exquisite soft-tissue contrast and morphology, allowing for the enhanced identification of primary tumors and metastatic disease. Currently, it is not uncommon to acquire images related to blood flow, cellularity, and macromolecular content in the clinical setting. The acquisition of images related to metabolism, hypoxia, pH, and tissue stiffness are also becoming common. All of these techniques have had some component of their invention, development, refinement, validation, and initial applications in the preclinical setting using in vivo animal models of cancer. In this review, we discuss the genesis of quantitative MRI methods that have been successfully translated from preclinical research and developed into clinical applications. These include methods that interrogate perfusion, diffusion, pH, hypoxia, macromolecular content, and tissue mechanical properties for improving detection, staging, and response monitoring of cancer. For each of these techniques, we summarize the 1) underlying biological mechanism(s); 2) preclinical applications; 3) available repeatability and reproducibility data; 4) clinical applications; and 5) limitations of the technique. We conclude with a discussion of lessons learned from translating MRI methods from the preclinical to clinical setting, and a presentation of four fundamental problems in cancer imaging that, if solved, would result in a profound improvement in the lives of oncology patients. Level of Evidence: 5 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2019;50:1377-1392.

Oxygen-sensitive MRI assessment of tumor response to hypoxic gas breathing challenge

Oxygen-sensitive MRI has been extensively used to investigate tumor oxygenation based on the response (R₂ * and/or R₁ ) to a gas breathing challenge. Most studies have reported response to hyperoxic gas indicating potential biomarkers of hypoxia. Few studies have examined hypoxic gas breathing and we have now evaluated acute dynamic changes in rat breast tumors. Rats bearing syngeneic subcutaneous (n = 15) or orthotopic (n = 7) 13762NF breast tumors were exposed to a 16% O₂ gas breathing challenge and monitored using blood oxygen level dependent (BOLD) R₂ * and tissue oxygen level dependent (TOLD) T₁ -weighted measurements at 4.7 T. As a control, we used a traditional hyperoxic gas breathing challenge with 100% O₂ on a subset of the subcutaneous tumor bearing rats (n = 6). Tumor subregions identified as responsive on the basis of R₂ * dynamics coincided with the viable tumor area as judged by subsequent H&E staining. As expected, R₂ * decreased and T₁ -weighted signal increased in response to 100% O₂ breathing challenge. Meanwhile, 16% O₂ breathing elicited an increase in R₂ *, but divergent response (increase or decrease) in T₁ -weighted signal. The T₁ -weighted signal increase may signify a dominating BOLD effect triggered by 16% O₂ in the relatively more hypoxic tumors, whereby the influence of increased paramagnetic deoxyhemoglobin outweighs decreased pO₂ . The results emphasize the importance of combined BOLD and TOLD measurements for the correct interpretation of tumor oxygenation properties.

Kinetics-Based Measurement of Hypoxia in Living Cells and Animals Using an Acetoxymethyl Ester Chemiluminescent Probe

Oxygenation and tissue hypoxia play critical roles in mammalian biology and contribute to aggressive phenotypes in cancerous tumors, driving research to develop accurate and easy-to-implement methods for monitoring hypoxia in living cells and animal models. This study reports the chemiluminescent probe HyCL-4-AM, which contains a nitroaromatic sensing moiety and, importantly, an acetoxymethyl (AM) ester that dramatically improves operation in cells and animals. HyCL-4-AM provides a selective 60 000-fold increase in luminescence emission in the presence of rat liver microsomes (RLM). For cellular operation, the chemiluminescence response kinetics is sharply dependent on oxygen levels, enabling highly significant and reproducible measurement of hypoxia in living cells. Whole animal imaging experiments in muscle tissue and tumor xenografts show that HyCL-4-AM can differentiate between well oxygenated muscle tissue and hypoxic tumors, demonstrating potential for monitoring tumor reoxygenation via hyperoxic treatment.

Imaging tumour hypoxia with oxygen-enhanced MRI and BOLD MRI

Hypoxia is known to be a poor prognostic indicator for nearly all solid tumours and also is predictive of treatment failure for radiotherapy, chemotherapy, surgery and targeted therapies. Imaging has potential to identify, spatially map and quantify tumour hypoxia prior to therapy, as well as track changes in hypoxia on treatment. At present no hypoxia imaging methods are available for routine clinical use. Research has largely focused on positron emission tomography (PET)-based techniques, but there is gathering evidence that MRI techniques may provide a practical and more readily translational alternative. In this review we focus on the potential for imaging hypoxia by measuring changes in longitudinal relaxation [R1; termed oxygen-enhanced MRI or tumour oxygenation level dependent (TOLD) MRI] and effective transverse relaxation [R2*; termed blood oxygenation level dependent (BOLD) MRI], induced by inhalation of either 100% oxygen or the radiosensitising hyperoxic gas carbogen. We explain the scientific principles behind oxygen-enhanced MRI and BOLD and discuss significant studies and their limitations. All imaging biomarkers require rigorous validation in order to translate into clinical use and the steps required to further develop oxygen-enhanced MRI and BOLD MRI into decision-making tools are discussed.