MRI of tumor angiogenesis

Blind deconvolution decreases requirements on temporal resolution of DCE-MRI: Application to 2nd generation pharmacokinetic modeling

PURPOSE

Dynamic Contrast-Enhanced (DCE) MRI with 2nd generation pharmacokinetic models provides estimates of plasma flow and permeability surface-area product in contrast to the broadly used 1st generation models (e.g. the Tofts models). However, the use of 2nd generation models requires higher frequency with which the dynamic images are acquired (around 1.5 s per image). Blind deconvolution can decrease the demands on temporal resolution as shown previously for one of the 1st generation models. Here, the temporal-resolution requirements achievable for blind deconvolution with a 2nd generation model are studied.

METHODS

The 2nd generation model is formulated as the distributed-capillary adiabatic-tissue-homogeneity (DCATH) model. Blind deconvolution is based on Parker's model of the arterial input function. The accuracy and precision of the estimated arterial input functions and the perfusion parameters is evaluated on synthetic and real clinical datasets with different levels of the temporal resolution.

RESULTS

The estimated arterial input functions remained unchanged from their reference high-temporal-resolution estimates (obtained with the sampling interval around 1 s) when increasing the sampling interval up to about 5 s for synthetic data and up to 3.6-4.8 s for real data. Further increasing of the sampling intervals led to systematic distortions, such as lowering and broadening of the 1st pass peak. The resulting perfusion-parameter estimation error was below 10% for the sampling intervals up to 3 s (synthetic data), in line with the real data perfusion-parameter boxplots which remained unchanged up to the sampling interval 3.6 s.

CONCLUSION

We show that use of blind deconvolution decreases the demands on temporal resolution in DCE-MRI from about 1.5 s (in case of measured arterial input functions) to 3-4 s. This can be exploited in increased spatial resolution or larger organ coverage.

The Correlation between Morpho-Dynamic Contrast-Enhanced Mammography (CEM) Features and Prognostic Factors in Breast Cancer: A Single-Center Retrospective Analysis

Breast cancer, a major contributor to female mortality globally, presents challenges in detection, prompting exploration beyond digital mammography. Contrast-Enhanced Mammography (CEM), integrating morphological and functional information, emerges as a promising alternative, offering advantages in cost-effectiveness and reduced anxiety compared to MRI. This study investigates CEM's correlation with breast cancer prognostic factors, encompassing histology, grade, and molecular markers. In a retrospective analysis involving 114 women, CEM revealed diverse lesion characteristics. Statistical analyses identified correlations between specific CEM features, such as spiculated margins and irregular shape, and prognostic factors like tumor grade and molecular markers. Notably, spiculated margins predicted lower grade and HER2 status, while irregular shape correlated with PgR and Ki-67 status. The study emphasizes CEM's potential in predicting breast cancer prognosis, shedding light on tumor behavior. Despite the limitations, including sample size and single-observer analysis, the findings advocate for CEM's role in stratifying breast cancers based on biological characteristics. CEM features, particularly spiculated margins, irregular shape, and enhancement dynamics, may serve as valuable indicators for personalized treatment decisions. Further research is crucial to validate these correlations and enhance CEM's clinical utility in breast cancer assessment.

Exploring the potential of Physics-Informed Neural Networks to extract vascularization data from DCE-MRI in the presence of diffusion

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is widely used to assess tissue vascularization, particularly in oncological applications. However, the most widely used pharmacokinetic (PK) models do not account for contrast agent (CA) diffusion between neighboring voxels, which can limit the accuracy of the results, especially in cases of heterogeneous tumors. To address this issue, previous works have proposed algorithms that incorporate diffusion phenomena into the formulation. However, these algorithms often face convergence problems due to the ill-posed nature of the problem. In this work, we present a new approach to fitting DCE-MRI data that incorporates CA diffusion by using Physics-Informed Neural Networks (PINNs). PINNs can be trained to fit measured data obtained from DCE-MRI while ensuring the mass conservation equation from the PK model. We compare the performance of PINNs to previous algorithms on different 1D cases inspired by previous works from literature. Results show that PINNs retrieve vascularization parameters more accurately from diffusion-corrected tracer-kinetic models. Furthermore, we demonstrate the robustness of PINNs compared to other traditional algorithms when faced with noisy or incomplete data. Overall, our results suggest that PINNs can be a valuable tool for improving the accuracy of DCE-MRI data analysis, particularly in cases where CA diffusion plays a significant role.

Mutual interferences between SIAT aPET insert and a 3 T uMR 790 MRI scanner

Objective.Dual-modality small animal PET/MR imaging provides temporally correlated information on two biochemical processes of a living object. An magnetic resonance imaging (MRI)-compatible small animal PET insert named Shenzhen Institutes of Advanced Technology (SIAT) aPET was developed by using dual-ended readout depth encoding detectors to simultaneously achieve a uniform high spatial resolution and high sensitivity at the SIAT. In this work, the mutual interferences between SIAT aPET and the 3 T uMR 790 MRI scanner of United Imaging was quantitatively evaluated.Approach.To minimize the mutual interferences, only the PET detectors and the readout electronics were placed inside the MRI scanner, the major signal processing electronic was placed in the corner of the MRI room and the auxiliary unit was placed in the MRI technical room. A dedicated mouse radio fRequency (RF) coil with a transmitter and receiver was developed for the PET insert. The effects of PET scanner on theB₀andB₁field of the MRI scanner and the quality of the MRI images were measured. The effects of MRI imaging on the performance of both the PET detectors and scanner were also measured.Main results.The electronic and mechanical components of the PET insert affected the homogeneity of theB₀field. The PET insert had no effect on the homogeneity ofB₁produced by the dedicated mouse coil but slightly reduced the strength ofB₁. The mean and standard deviation of the RF noise map were increased by 2.2% and 11.6%, respectively, while the PET insert was placed in the MRI scanner and powered on. Eddy current was produced while the PET insert was placed in the MRI scanner, and it was further increased while the PET insert was powered on. Despite the above-mentioned interferences from the PET insert, the MR images of a uniform cylindrical water phantom showed that the changes in the signal-to-noise ratio (SNR) and homogeneity as the PET insert was placed in the MRI scanner were acceptable regardless of whether the PET insert was powered off or powered on. The maximum reduction of SNR was less than 11%, and the maximum reduction of homogeneity was less than 2.5% while the PET insert was placed inside the MRI scanner and powered on for five commonly used MRI sequences. MRI using gradient echo (GRE), spin echo (SE) and fast spin echo (FSE) sequences had negligible effects on the flood histograms and energy resolution of the PET detectors, as well as the spatial resolution and sensitivity of the PET scanner.Significance.The mutual interference between the SIAT aPET and the 3 T uMR 790 MRI scanner are acceptable. Simultaneous PET/MRI imaging of small animals can be performed with the two scanners.

Quantitative Ultrasound for Evaluation of Tumour Response to Ultrasound-Microbubbles and Hyperthermia

Objectives: Prior study has demonstrated the implementation of quantitative ultrasound (QUS) for determining the therapy response in breast tumour patients. Several QUS parameters quantified from the tumour region showed a significant correlation with the patient's clinical and pathological response. In this study, we aim to identify if there exists such a link between QUS parameters and changes in tumour morphology due to combined ultrasound-stimulated microbubbles (USMB) and hyperthermia (HT) using the breast xenograft model (MDA-MB-231). Method: Tumours grown in the hind leg of severe combined immuno-deficient mice were treated with permutations of USMB and HT. Ultrasound radiofrequency data were collected using a 25 MHz array transducer, from breast tumour-bearing mice prior and post-24-hour treatment. Result: Our result demonstrated an increase in the QUS parameters the mid-band fit and spectral 0-MHz intercept with an increase in HT duration combined with USMB which was found to be reflective of tissue structural changes and cell death detected using haematoxylin and eosin and terminal deoxynucleotidyl transferase dUTP nick end labelling stain. A significant decrease in QUS spectral parameters was observed at an HT duration of 60 minutes, which is possibly due to loss of nuclei by the majority of cells as confirmed using histology analysis. Morphological alterations within the tumour might have contributed to the decrease in backscatter parameters. Conclusion: The work here uses the QUS technique to assess the efficacy of cancer therapy and demonstrates that the changes in ultrasound backscatters mirrored changes in tissue morphology.

DCE-MRI and DWI can differentiate benign from malignant prostate tumors when serum PSA is ≥10 ng/ml

Background

This study investigated the diagnostic utility of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and diffusion-weighted imaging (DWI) parameters for distinguishing between benign and malignant prostate tumors when serum prostate-specific antigen (PSA) level is ≥10 ng/ml.

Methods

Patients with prostate cancer (PCa) and benign prostatic hyperplasia (BPH) with serum PSA ≥10 ng/ml before treatment were recruited. Transrectal ultrasound-guided biopsy or surgery was performed for tumor classification and patients were stratified accordingly into PCa and BPH groups. Patients underwent DCE-MRI and DWI scanning and the transfer constant (K_trans), rate constant (K_ep), fractional volume of the extravascular extracellular space, plasma volume (V_p), and Prostate Imaging Reporting and Data System Version 2 (PI-RADS v2) score were determined. The apparent diffusion coefficient (ADC) was calculated from DWI. The diagnostic performance of these parameters was assessed by receiver operating characteristic (ROC) curve analysis, and those showing a significant difference between the PCa and BPH groups were combined into a multivariate logistic regression model for PCa diagnosis. Spearman's correlation was used to analyze the relationship between Gleason score and imaging parameters.

Results

The study enrolled 65 patients including 32 with PCa and 33 with BPH. Ktrans (P=0.006), Kep (P=0.001), and Vp (P=0.009) from DCE-MRI and ADC (P<0.001) from DWI could distinguish between the 2 groups when PSA was ≥10 ng/ml. PI-RADS score (area under the ROC curve [AUC]=0.705), Ktrans (AUC=0.700), Kep (AUC=0.737), Vp (AUC=0.688), and ADC (AUC=0.999) showed high diagnostic performance for discriminating PCa from BPH. A combined model based on PI-RADS score, Ktrans, Kep, Vp, and ADC had a higher AUC (1.000), with a sensitivity of 0.998 and specificity of 0.999. Imaging markers showed no significant correlation with Gleason score in PCa.

Conclusion

DCE-MRI and DWI parameters can distinguish between benign and malignant prostate tumors in patients with serum PSA ≥10 ng/ml.

Feasibility of Arterial Spin Labeling Magnetic Resonance Imaging for Musculoskeletal Tumors with Optimized Post-Labeling Delay

Arterial spin labeling (ASL) magnetic resonance imaging (MRI) is used to perform perfusion imaging without administration of contrast media. However, the reliability of ASL for musculoskeletal tumors and the influence of post-labeling delay (PLD) have not been fully clarified. This study aimed to evaluate the performance of ASL with different PLDs in the imaging of musculoskeletal tumors. Forty-five patients were enrolled and were divided into a malignant group, a hypervascular benign group, a hypovascular benign group and a control group. The tissue blood flow (TBF) of the lesions and normal muscles was measured and the lesion-to-muscle TBF ratio and differences were calculated. The results showed that both the TBF of lesions and muscles increased as the PLD increased, and the TBF of muscles correlated significantly and positively with the TBF of lesions (all p < 0.05). The TBF and lesion-to-muscle TBF differences of the malignant lesions were significantly higher than those of the hypovascular benign lesions and the control group in all PLD groups (all p < 0.0125) and only those of the hypervascular benign lesions in the longest PLD (3025 ms) group (p = 0.0120, 0.0116). In conclusion, ASL detects high TBF in malignant tumors and hypervascular benign lesions, and a longer PLD is recommended for ASL to differentiate musculoskeletal tumors.

Arterial spin labeling of nasopharyngeal carcinoma shows early therapy response

OBJECTIVE

This study aimed to determine the value of arterial spin labeling (ASL) perfusion imaging in assessing the early efficacy of chemoradiotherapy for nasopharyngeal carcinoma (NPC).

METHODS

Fifty-five patients with locoregionally advanced NPC underwent conventional 3.0-T magnetic resonance imaging (MRI) and ASL before and after chemoradiotherapy (prescribed dose reached 40 Gy). Based on the response evaluation criteria for solid tumors (RECIST 1.1), the patients were divided into the partial response and stable disease groups. MRI re-examination was performed one month after chemoradiotherapy completion, and patients were divided into residual and non-residual groups. We investigated inter-group differences in ASL-based tumor blood flow (TBF) parameters (pre-treatment tumor blood flow, post-treatment tumor blood flow, and changes in tumor blood flow, i.e., Pre-TBF, Post-TBF, ΔTBF), correlation between TBF parameters and tumor atrophy rate, and value of TBF parameters in predicting sensitivity to chemoradiotherapy.

RESULTS

There were differences in Pre-TBF, Post-TBF, and ΔTBF between the partial response and stable disease groups (p < 0.01). There were also differences in Pre-TBF and ΔTBF between the residual and non-residual groups (p < 0.01). Pre-TBF and ΔTBF were significantly correlated with the tumor atrophy rate; the correlation coefficients were 0.677 and 0.567, respectively (p < 0.01). Pre-TBF had high diagnostic efficacies in predicting sensitivity to chemoradiotherapy and residual tumors, with areas under the curve of 0.845 and 0.831, respectively.

CONCLUSION

ASL permits a noninvasive approach to predicting the early efficacy of chemoradiotherapy for NPC.

Dynamic contrast-enhanced magnetic resonance perfusion volumetrics can differentiate tuberculosis of the spine and vertebral malignancy

BACKGROUND

There is considerable overlap in radiologic features of tubercular and malignant spinal lesions on conventional magnetic resonance imaging (MRI).

PURPOSE

To evaluate the role of dynamic contrast-enhanced (DCE) MRI perfusion parameters in differentiating vertebral malignancy from spinal tuberculosis.

MATERIAL AND METHODS

This was a prospective study and we enrolled consecutive patients presenting with a clinical/radiologic evidence of vertebral lesions. DCE-MRI of the spine was performed using 3D volume interpolated breath-hold examination (VIBE) sequence after intravenously injecting 0.1 mmol/kg body weight of gadopentetate dimeglumine. We used Tofts model to calculate DCE parameters that included K^trans (transfer constant), k_ep (rate constant), v_e (fractional volume of extracellular extravascular space), and iAUC (initial area under the curve). We compared the mean value of each perfusion parameter by type of lesion (tubercular/malignant) at 0.05 significance level and performed receiver operating characteristic curve analysis.

RESULTS

We could confirm histologic/cytologic diagnosis in 35 of the 45 patients recruited. Of these, 19 were tubercular and 16 were malignant lesions. The mean (± standard deviation) of k_ep (min^-1) was significantly higher (2.89 ± 3.3) in malignant compared to tubercular lesions (0.81 ± 0.19), whereas v_e was significantly lower in malignant (0.27 ± 0.13 mL/g) compared to benign lesions (0.47 ± 0.12 mL/g) at 0.05 significance level. k_ep cutoff of ≥1.17 min^-1 had a sensitivity of 93.8% and specificity of 100% with a diagnostic accuracy of 94.4% in detecting malignant disease.

CONCLUSION

High k_ep is the single best predictor of malignant vertebral lesions. We recommend k_ep cutoff value of ≥1.17 min^-1 that has high diagnostic accuracy in identifying malignant lesions.

Molecular Imaging of Tumor Microenvironment to Assess the Effects of Locoregional Treatment for Hepatocellular Carcinoma

Liver cancer is one of the leading causes of cancer deaths worldwide. Among all primary liver cancers, hepatocellular carcinoma (HCC) is the most common type, representing 75%‐85% of all primary liver cancer cases. Median survival following diagnosis of HCC is approximately 6 to 20 months due to late diagnosis in its course and few effective treatment options. Interventional therapy with minimal invasiveness is recognized as a promising treatment for HCC. However, due to the heterogeneity of HCC and the complexity of the tumor microenvironment, the long‐term efficacy of treatment for HCC remains a challenge in the clinic. Tumor microenvironment, including factors such as hypoxia, angiogenesis, low extracellular pH, interstitial fluid pressure, aerobic glycolysis, and various immune responses, has emerged as a key contributor to tumor residual and progression after locoregional treatment for HCC. New approaches to noninvasively assess the treatment response and assist in the clinical decision‐making process are therefore urgently needed. Molecular imaging tools enabling such an assessment may significantly advance clinical practice by allowing real‐time optimization of treatment protocols for the individual patient. This review discusses recent advances in the application of molecular imaging technologies for noninvasively assessing changes occurring in the microenvironment of HCC after locoregional treatment.

Radiomic machine learning for predicting prognostic biomarkers and molecular subtypes of breast cancer using tumor heterogeneity and angiogenesis properties on MRI

OBJECTIVES

To investigate machine learning approaches for radiomics-based prediction of prognostic biomarkers and molecular subtypes of breast cancer using quantification of tumor heterogeneity and angiogenesis properties on magnetic resonance imaging (MRI).

METHODS

This prospective study examined 291 invasive cancers in 288 patients who underwent breast MRI at 3 T before treatment between May 2017 and July 2019. Texture and perfusion analyses were performed and a total of 160 parameters for each cancer were extracted. Relationships between MRI parameters and prognostic biomarkers were analyzed using five machine learning algorithms. Each model was built using only texture features, only perfusion features, or both. Model performance was compared using the area under the receiver-operating characteristic curve (AUC) and the DeLong method, and the importance of MRI parameters in prediction was derived.

RESULTS

Texture parameters were associated with the status of hormone receptors, human epidermal growth factor receptor 2, and Ki67, tumor size, grade, and molecular subtypes (p < 0.002). Perfusion parameters were associated with the status of hormone receptors and Ki67, grade, and molecular subtypes (p < 0.003). The random forest model integrating texture and perfusion parameters showed the highest performance (AUC = 0.75). The performance of the random forest model was the best with a special scale filter of 0 (AUC = 0.80). The important parameters for prediction were texture irregularity (entropy) and relative extracellular extravascular space (V_e).

CONCLUSIONS

Radiomic machine learning that integrates tumor heterogeneity and angiogenesis properties on MRI has the potential to noninvasively predict prognostic factors of breast cancer.

KEY POINTS

• Machine learning, integrating tumor heterogeneity and angiogenesis properties on MRI, can be applied to predict prognostic biomarkers and molecular subtypes in breast cancer. • The random forest model showed the best predictive performance among the five machine learning models (logistic regression, decision tree, naïve Bayes, random forest, and artificial neural network). • The most important MRI parameters for predicting prognostic factors in breast cancer were texture irregularity (entropy) among texture parameters and relative extracellular extravascular space (V_e) among perfusion parameters.

Imaging methods to evaluate tumor microenvironment factors affecting nanoparticle drug delivery and antitumor response

Standard small molecule and nanoparticulate chemotherapies are used for cancer treatment; however, their effectiveness remains highly variable. One reason for this variable response is hypothesized to be due to nonspecific drug distribution and heterogeneity of the tumor microenvironment, which affect tumor delivery of the agents. Nanoparticle drugs have many theoretical advantages, but due to variability in tumor microenvironment (TME) factors, the overall drug delivery to tumors and associated antitumor response are low. The nanotechnology field would greatly benefit from a thorough analysis of the TME factors that create these physiological barriers to tumor delivery and treatment in preclinical models and in patients. Thus, there is a need to develop methods that can be used to reveal the content of the TME, determine how these TME factors affect drug delivery, and modulate TME factors to increase the tumor delivery and efficacy of nanoparticles. In this review, we will discuss TME factors involved in drug delivery, and how biomedical imaging tools can be used to evaluate tumor barriers and predict drug delivery to tumors and antitumor response.

Inter-Reader Agreement of Diffusion-Weighted Magnetic Resonance Imaging for Breast Cancer Detection: A Multi-Reader Retrospective Study

PURPOSE

In order to evaluate the use of un-enhanced magnetic resonance imaging (MRI) for detecting breast cancer, we evaluated the accuracy and the agreement of diffusion-weighted imaging (DWI) through the inter-reader reproducibility between expert and non-expert readers.

MATERIAL AND METHODS

Consecutive breast MRI performed in a single centre were retrospectively evaluated by four radiologists with different levels of experience. The per-breast standard of reference was the histological diagnosis from needle biopsy or surgical excision, or at least one-year negative follow-up on imaging. The agreement across readers (by inter-reader reproducibility) was examined for each breast examined using Cohen's and Fleiss' kappa (κ) statistics. The Wald test was used to test the difference in inter-reader agreement between expert and non-expert readers.

RESULTS

Of 1131 examinations, according to our inclusion and exclusion criteria, 382 women were included (49.5 ± 12 years old), 40 of them with unilateral mastectomy, totaling 724 breasts. Overall inter-reader reproducibility was substantial (κ = 0.74) for expert readers and poor (κ = 0.37) for non- expert readers. Pairwise agreement between expert readers and non-expert readers was moderate (κ = 0.60) and showed a statistically superior agreement of the expert readers over the non-expert readers (p = 0.003).

CONCLUSIONS

DWI showed substantial inter-reader reproducibility among expert-level readers. Pairwise comparison showed superior agreement of the expert readers over the non-expert readers, with the expert readers having higher inter-reader reproducibility than the non-expert readers. These findings open new perspectives for prospective studies investigating the actual role of DWI as a stand-alone method for un-enhanced breast MRI.

Using arterial spin labeling blood flow and its histogram analysis to distinguish early-stage nasopharyngeal carcinoma from lymphoid hyperplasia

ABSTRACT

To investigate the feasibility of arterial spin labeling (ASL) blood flow (BF) and its histogram analysis to distinguish early-stage nasopharyngeal carcinoma (NPC) from nasopharyngeal lymphoid hyperplasia (NPLH).Sixty-three stage T1 NPC patients and benign NPLH patients underwent ASL on a 3.0-T magnetic resonance imaging system. BF histogram parameters were derived automatically, including the mean, median, maximum, minimum, kurtosis, skewness, and variance. Absolute values were obtained for skewness and kurtosis (absolute value of skewness [AVS] and absolute value of kurtosis [AVK], respectively). The Mann-Whitney U test, receiver operating characteristic curve, and multiple logistic regression models were used for statistical analysis.The mean, maximum, and variance of ASL BF values were significantly higher in early-stage NPC than in NPLH (all P < 0.0001), while the median and AVK values of early-stage NPC were also significantly higher than those of NPLH (all P < 0.001). No significant difference was found between the minimum and AVS values in early-stage NPC compared with NPLH (P = 0.125 and P = 0.084, respectively). The area under the curve (AUC) of the maximum was significantly higher than those of the mean and median (P < 0.05). The AUC of variance was significantly higher than those of the other parameters (all P < 0.05). Multivariate analysis showed that variance was the only independent predictor of outcome (P < 0.05).ASL BF and its histogram analysis could distinguish early-stage NPC from NPLH, and the variance value was a unique independent predictor.

Current landscape and future perspectives in preclinical MR and PET imaging of brain metastasis

Brain metastasis (BM) is a major cause of cancer patient morbidity. Clinical magnetic resonance imaging (MRI) and positron emission tomography (PET) represent important resources to assess tumor progression and treatment responses. In preclinical research, anatomical MRI and to some extent functional MRI have frequently been used to assess tumor progression. In contrast, PET has only to a limited extent been used in animal BM research. A considerable culprit is that results from most preclinical studies have shown little impact on the implementation of new treatment strategies in the clinic. This emphasizes the need for the development of robust, high-quality preclinical imaging strategies with potential for clinical translation. This review focuses on advanced preclinical MRI and PET imaging methods for BM, describing their applications in the context of what has been done in the clinic. The strengths and shortcomings of each technology are presented, and recommendations for future directions in the development of the individual imaging modalities are suggested. Finally, we highlight recent developments in quantitative MRI and PET, the use of radiomics and multimodal imaging, and the need for a standardization of imaging technologies and protocols between preclinical centers.

Current Concepts in Multi-Modality Imaging of Solid Tumor Angiogenesis

Simple Summary

The recent increase in the use of targeted molecular therapy including anti-angiogenetic agents in cancer treatment necessitate the use of robust tools to assess and guide treatment. Angiogenesis, the formation of new disorganized blood vessels, is used by tumor cells to grow and spread using different mechanisms that could be targeted by anti-angiogenetic agents. In this review, we discuss the biological principles of tumor angiogenesis and the imaging modalities that could provide information beyond gross tumor size and morphology to capture the efficacy of anti-angiogenetic therapeutic response.

Abstract

There have been rapid advancements in cancer treatment in recent years, including targeted molecular therapy and the emergence of anti-angiogenic agents, which necessitate the need to quickly and accurately assess treatment response. The ideal tool is robust and non-invasive so that the treatment can be rapidly adjusted or discontinued based on efficacy. Since targeted therapies primarily affect tumor angiogenesis, morphological assessment based on tumor size alone may be insufficient, and other imaging modalities and features may be more helpful in assessing response. This review aims to discuss the biological principles of tumor angiogenesis and the multi-modality imaging evaluation of anti-angiogenic therapeutic responses.

Dynamic contrast-enhanced magnetic resonance imaging and diffusion-weighted imaging in the activity staging of terminal ileum Crohn's disease

BACKGROUND

The activity staging of Crohn’s disease (CD) in the terminal ileum is critical in developing an accurate clinical treatment plan. The activity of terminal ileum CD is associated with the microcirculation of involved bowel walls. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and diffusion-weighted imaging (DWI) can reflect perfusion and permeability of bowel walls by providing microcirculation information. As such, we hypothesize that DCE-MRI and DWI parameters can assess terminal ileum CD, thereby providing an opportunity to stage CD activity.

AIM

To evaluate the value of DCE-MRI and DWI in assessing activity of terminal ileum CD.

METHODS

Forty-eight patients with CD who underwent DCE-MRI and DWI were enrolled. The patients’ activity was graded as remission, mild and moderate-severe. The transfer constant (K^trans), wash-out constant (K_ep), and extravascular extracellular volume fraction (V_e) were calculated from DCE-MRI and the apparent diffusion coefficient (ADC) was obtained from DWI. Magnetic Resonance Index of Activity (MaRIA) was calculated from magnetic resonance enterography. Differences in these quantitative parameters were compared between normal ileal loop (NIL) and inflamed terminal ileum (ITI) and among different activity grades. The correlations between these parameters, MaRIA, the Crohn’s Disease Activity Index (CDAI), and Crohn’s Disease Endoscopic Index of Severity (CDEIS) were examined. Receiver operating characteristic curve analyses were used to determine the diagnostic performance of these parameters in differentiating between CD activity levels.

RESULTS

Higher K^trans (0.07 ± 0.04 vs 0.01 ± 0.01), K_ep (0.24 ± 0.11 vs 0.15 ± 0.05) and V_e (0.27 ± 0.07 vs 0.08 ± 0.03), but lower ADC (1.41 ± 0.26 vs 2.41 ± 0.30) values were found in ITI than in NIL (all P < 0.001). The K^trans, K_ep, V_e and MaRIA increased with disease activity, whereas the ADC decreased (all P < 0.001). The K^trans, K_ep, V_e and MaRIA showed positive correlations with the CDAI (r = 0.866 for K^trans, 0.870 for K_ep, 0.858 for V_e, 0.890 for MaRIA, all P < 0.001) and CDEIS (r = 0.563 for K^trans, 0.567 for K_ep, 0.571 for V_e, 0.842 for MaRIA, all P < 0.001), while the ADC showed negative correlations with the CDAI (r = -0.857, P < 0.001) and CDEIS (r = -0.536, P < 0.001). The areas under the curve (AUC) for the K^trans, K_ep, V_e, ADC and MaRIA values ranged from 0.68 to 0.91 for differentiating inactive CD (CD remission) from active CD (mild to severe CD). The AUC when combining the K^trans, K_ep and V_e was 0.80, while combining DCE-MRI parameters and ADC values yielded the highest AUC of 0.95.

CONCLUSION

DCE-MRI and DWI parameters all serve as measures to stage CD activity. When they are combined, the assessment performance is improved and better than MaRIA.

Preclinical Applications of Magnetic Resonance Imaging in Oncology

The evolving possibilities of molecular imaging (MI) are fundamentally changing the way we look at cancer, with imaging paradigms now shifting away from basic morphological measures toward the longitudinal assessment of functional, metabolic, cellular, and molecular information in vivo. Recent developments of imaging methodology and probe molecules utilizing the vast number of novel animal models of human cancers have enhanced our ability to non-invasively characterize neoplastic tissue and follow anticancer treatments. While preclinical molecular imaging offers a whole palette of excellent methodology to choose from, we will focus on magnetic resonance imaging (MRI) techniques, since they provide excellent molecular imaging capabilities and bear high potential for clinical translation. Prerequisites and consequences of using animal models as surrogates of human cancers in preclinical molecular imaging are outlined. We present physical principles, values, and limitations of MRI as molecular imaging modality and comment on its high potential to non-invasively assess information on metabolism, hypoxia, angiogenesis, and cell trafficking in preclinical cancer research.

Distinguishing metastatic triple-negative breast cancer from nonmetastatic breast cancer using second harmonic generation imaging and resonance Raman spectroscopy

Triple-negative breast cancer (TNBC) is an aggressive subset of breast cancer that is more common in African-American and Hispanic women. Early detection followed by intensive treatment is critical to improving poor survival rates. The current standard to diagnose TNBC from histopathology of biopsy samples is invasive and time-consuming. Imaging methods such as mammography and magnetic resonance (MR) imaging, while covering the entire breast, lack the spatial resolution and specificity to capture the molecular features that identify TNBC. Two nonlinear optical modalities of second harmonic generation (SHG) imaging of collagen, and resonance Raman spectroscopy (RRS) potentially offer novel rapid, label-free detection of molecular and morphological features that characterize cancerous breast tissue at subcellular resolution. In this study, we first applied MR methods to measure the whole-tumor characteristics of metastatic TNBC (4T1) and nonmetastatic estrogen receptor positive breast cancer (67NR) models, including tumor lactate concentration and vascularity. Subsequently, we employed for the first time in vivo SHG imaging of collagen and ex vivo RRS of biomolecules to detect different microenvironmental features of these two tumor models. We achieved high sensitivity and accuracy for discrimination between these two cancer types by quantitative morphometric analysis and nonnegative matrix factorization along with support vector machine. Our study proposes a new method to combine SHG and RRS together as a promising novel photonic and optical method for early detection of TNBC.

Evaluating angioarchitectural characteristics of glial and metastatic brain tumors with conventional magnetic resonance imaging

Primary and metastatic brain tumors can overlap in traditional imaging features detected on preoperative conventional magnetic resonance imaging (MRI). The research objective was to determine whether morphological vascular characteristics present in routine preoperative imaging using traditional MRI sequences are predictive of primary versus metastatic brain tumors; secondarily to determine association of conventional and vascular-related imaging parameters with intraoperative blood loss, pathological invasion, and World Health Organization (WHO) tumor grade. A retrospective review analyzed 100 consecutive intracranial tumor surgeries, 50 WHO grade II-IV gliomas and 50 intracranial metastases. Two blinded expert readers independently evaluated preoperative MRIs, obtained via standard morphological imaging sequences, for adjacent or intra-tumoral arterial aneurysm, peritumoral venous ectasia, prominence, or engorgement ("aberrant peritumoral vessels"), and prominent intra-tumoral flow voids. Multivariate analysis was performed to develop models predictive of glioma and glioblastoma (GBM). Aberrant peritumoral vessels and prominent intra-tumoral flow voids were statistically significant predictors of glioma in univariate analyses (p = 0.048, p = 0.001, respectively) and when combined in multivariate analysis (OR = 5.23, p = 0.001), particularly for GBM (OR = 9.08, p < 0.001). Multivariate modeling identified prominent intra-tumoral flow voids and FLAIR invasion as the strongest combined predictors of gliomas and GBM. Aberrant peritumoral vessels and larger tumor volume predicted higher intraoperative blood loss in all analyses. No vascular-related parameters predicted pathological invasion on multivariate analysis. Aberrant peritumoral vessels and prominent intra-tumoral flow voids were predictive of gliomas, specifically GBM. These vascular characteristics, evaluated on routine clinical preoperative MRI imaging, may aid in distinguishinggliomafrom brainmetastases andmay predict intraoperative blood loss.

Correlation of Tumor Perfusion Between Carbon-13 Imaging with Hyperpolarized Pyruvate and Dynamic Susceptibility Contrast MRI in Pre-Clinical Model of Glioblastoma

PURPOSE

The purpose of this study was to compare C-13 imaging parameters with hyperpolarized [1-¹³C]pyruvate with conventional gadolinium (Gd)-based perfusion weighted imaging using an orthotopic xenograft model of human glioblastoma multiforme (GBM).

PROCEDURES

C-13 3D magnetic resonance spectroscopic imaging (MRSI) data were obtained from 14 tumor-bearing rats after the injection of hyperpolarized [1-¹³C]pyruvate at a 3T scanner. Dynamic susceptibility contrast (DSC) perfusion-weighted MR images were obtained following intravenous administration of Gd-DTPA. Normalized lactate, pyruvate, total carbon, and lactate to pyruvate ratio from C-13 MRSI data were compared with normalized peak height and percent recovery of ΔR2* curve from the DSC images in the voxels containing tumor using a Pearson's linear correlation.

RESULTS

Normalized peak height from DSC imaging showed substantial correlations with normalized lactate (r = 0.6, p = 0.02) and total carbon (r = 0.6, p = 0.02) from hyperpolarized C-13 MRSI data.

CONCLUSIONS

Since the peak height in the ΔR2* curve from DSC data is related to the extent of blood volume, these hyperpolarized C-13 imaging parameters may be used to assess blood volume in rodent intracranial xenograft models of GBM.

Preoperative assessment of breast cancer: Multireader comparison of contrast-enhanced MRI versus the combination of unenhanced MRI and digital breast tomosynthesis

PURPOSE

To compare the sensitivity for breast cancer (BC) and BC size estimation of preoperative contrast-enhanced magnetic resonance imaging (CEMRI) versus combined unenhanced magnetic resonance imaging (UMRI) and digital breast tomosynthesis (DBT).

PATIENTS AND METHODS

We retrospectively included 56 women who underwent DBT and preoperative 1.5 T CEMRI between January 2016-February 2017. Three readers with 2-10 years of experience in CEMRI and DBT, blinded to pathology, independently reviewed CEMRI (diffusion-weighted imaging [DWI], T2-weighted imaging, pre- and post-contrast T1-weighted imaging) and a combination of UMRI (DWI and pre-contrast T1-weighted imaging) and DBT. We calculated per-lesion sensitivity of CEMRI and UMRI + DBT, and the agreement between CEMRI, UMRI and DBT versus pathology in assessing cancer size (Bland-Altman analysis). Logistic regression was performed to assess features predictive of cancer missing.

RESULTS

We included 70 lesions (64% invasive BC, 36% ductal carcinoma in situ or invasive BC with in situ component). UMRI + DBT showed lower sensitivity (86-89%) than CEMRI (94-100%), with a significant difference for the most experienced reader only (p = 0.008). False-positives were fewer with UMRI + DBT (4-5) than with CEMRI (18-25), regardless of the reader (p = 0.001-0.005). For lesion size, UMRI showed closer limits of agreement with pathology than CEMRI or DBT. Cancer size ≤1 cm was the only independent predictor for cancer missing for both imaging strategies (Odds ratio 8.62 for CEMRI and 19.16 for UMRI + DBT).

CONCLUSIONS

UMRI + DBT showed comparable sensitivity and less false-positives than CEMRI in the preoperative assessment of BC. UMRI was the most accurate tool to assess cancer size.

Improved Drug Delivery to Brain Metastases by Peptide-Mediated Permeabilization of the Blood-Brain Barrier

Patients with melanoma have a high risk of developing brain metastasis, which is associated with a dismal prognosis. During early stages of metastasis development, the blood-brain barrier (BBB) is likely intact, which inhibits sufficient drug delivery into the metastatic lesions. We investigated the ability of the peptide, K16ApoE, to permeabilize the BBB for improved treatment with targeted therapies preclinically. Dynamic contrast enhanced MRI (DCE-MRI) was carried out on NOD/SCID mice to study the therapeutic window of peptide-mediated BBB permeabilization. Further, both in vivo and in vitro assays were used to determine K16ApoE toxicity and to obtain mechanistic insight into its action on the BBB. The therapeutic impact of K16ApoE on metastases was evaluated combined with the mitogen-activated protein kinase pathway inhibitor dabrafenib, targeting BRAF mutated melanoma cells, which is otherwise known not to cross the intact BBB. Our results from the DCE-MRI experiments showed effective K16ApoE-mediated BBB permeabilization lasting for up to 1 hour. Mechanistic studies showed a dose-dependent effect of K16ApoE caused by induction of endocytosis. At concentrations above IC₅₀, the peptide additionally showed nonspecific disturbances on plasma membranes. Combined treatment with K16ApoE and dabrafenib reduced the brain metastatic burden in mice and increased animal survival, and PET/CT showed that the peptide also facilitated the delivery of compounds with molecular weights as large as 150 kDa into the brain. To conclude, we demonstrate a transient permeabilization of the BBB, caused by K16ApoE, that facilitates enhanced drug delivery into the brain. This improves the efficacy of drugs that otherwise do not cross the intact BBB.

The Continuing Evolution of Molecular Functional Imaging in Clinical Oncology: The Road to Precision Medicine and Radiogenomics (Part II)

The present era of precision medicine sees "cancer" as a consequence of molecular derangements occurring at the commencement of the disease process, with morphological changes happening much later in the process of tumourigenesis. Conventional imaging techniques, such as computed tomography (CT), ultrasound (US) and magnetic resonance imaging (MRI) play an integral role in the detection of disease at the macroscopic level. However, molecular functional imaging (MFI) techniques entail the visualisation and quantification of biochemical and physiological processes occurring during tumourigenesis. MFI has the potential to play a key role in heralding the transition from the concept of "one-size-fits-all" treatment to "precision medicine". Integration of MFI with other fields of tumour biology such as genomics has spawned a novel concept called "radiogenomics", which could serve as an indispensable tool in translational cancer research. With recent advances in medical image processing, such as texture analysis, deep learning and artificial intelligence, the future seems promising; however, their clinical utility remains unproven at present. Despite the emergence of novel imaging biomarkers, the majority of these require validation before clinical translation is possible. In this two part review, we discuss the systematic collaboration across structural, anatomical and molecular imaging techniques that constitute MFI. Part I reviews positron emission tomography, radiogenomics, AI, and optical imaging, while part II reviews MRI, CT and ultrasound, their current status, and recent advances in the field of precision oncology.

Dynamic Contrast-Enhanced MRI to Differentiate Parotid Neoplasms Using Golden-Angle Radial Sparse Parallel Imaging

BACKGROUND AND PURPOSE

Conventional imaging frequently shows overlapping features between benign and malignant parotid neoplasms. We investigated dynamic contrast-enhanced MR imaging using golden-angle radial sparse parallel imaging in differentiating parotid neoplasms.

MATERIALS AND METHODS

For this retrospective study, 41 consecutive parotid neoplasms were imaged with dynamic contrast-enhanced MR imaging with golden-angle radial sparse parallel imaging using 1-mm in-plane resolution. The temporal resolution was 3.4 seconds for 78.2 seconds and 8.8 seconds for the remaining acquisition. Three readers retrospectively and independently created and classified time-intensity curves as follows: 1) continuous wash-in; 2) rapid wash-in, subsequent plateau; and 3) rapid wash-in with washout. Additionally, time-intensity curve-derived semiquantitative metrics normalized to the ipsilateral common carotid artery were recorded. Diagnostic performance for the prediction of neoplasm type and malignancy was assessed. Subset multivariate analysis (n = 32) combined semiquantitative time-intensity curve metrics with ADC values.

RESULTS

Independent time-intensity curve classification of the 41 neoplasms produced moderate-to-substantial interreader agreement (κ = 0.50-0.79). The time-intensity curve classification threshold of ≥2 predicted malignancy with a positive predictive value of 56.0%-66.7%, and a negative predictive value of 92.0%-100%. The time-intensity curve classification threshold of <2 predicted pleomorphic adenoma with a positive predictive value of 87.0%-95.0% and a negative predictive value of 76.0%-95.0%. For all readers, type 2 and 3 curves were associated with malignant neoplasms (P < .001), and type 1 curves, with pleomorphic adenomas (P < .001). Semiquantitative analysis for malignancy prediction yielded an area under the receiver operating characteristic curve of 0.85 (95% CI, 0.73-0.99). Combining time-to-maximum and ADC predicts pleomorphic adenoma better than either metric alone (P < .001).

CONCLUSIONS

Golden-angle radial sparse parallel MR imaging allows high spatial and temporal resolution permeability characterization of parotid neoplasms, with a high negative predictive value for malignancy prediction. Combining time-to-maximum and ADC improves pleomorphic adenoma prediction compared with either metric alone.

Tumor vasculature remodeling by radiation therapy increases doxorubicin distribution and efficacy

The tumor microenvironment regulates cancer initiation, progression and response to treatment. In particular, the immature tumor vasculature may impede drugs from reaching tumor cells at a lethal concentration. We and others have shown that radiation therapy (RT) induces pericyte recruitment, resembling vascular normalization. Here, we asked whether radiation-induced vascular remodeling translates into improved tissue distribution and efficacy of chemotherapy. First, RT induced vascular remodeling, accompanied by decreased hypoxia and/or increased Hoechst perfusion in prostate PC3 and LNCaP and Lewis lung carcinoma. These results were independent of the RT regimen, respectively 10 × 2 Gy and 2 × 12 Gy, suggesting a common effect. Next, using doxorubicin as a fluorescent reporter, we observed that RT improves intra-tumoral chemotherapy distribution. These effects were not hindered by anti-angiogenic sunitinib. Moreover, sub-optimal doses of doxorubicin had almost no effect alone, but significantly delayed tumor growth after RT. These data demonstrate that RT favors the efficacy of chemotherapy by improving tissue distribution, and could be an alternative chemosensitizing strategy.

Role of advanced magnetic resonance imaging in the assessment of malignancies of the mediastinum

In the new era of functional magnetic resonance imaging (MRI), the utility of chest MRI is increasing exponentially due to several advances, including absence of ionizing radiation, excellent tissue contrast and high capability for lesion characterization and treatment monitoring. The application of several of these diagnostic weapons in a multiparametric fashion enables to better characterize thymic epithelial tumors and other mediastinal tumoral lesions, accurate assessment of the invasion of adjacent structures and detection of pathologic lymph nodes and metastasis. Also, “do not touch lesions” could be identified with the associated impact in the management of those patients. One of the hot-spots of the multiparametric chest MR is its ability to detect with acuity early response to treatment in patients with mediastinal malignant neoplasms. This has been related with higher rates of overall survival and progression free survival. Therefore, in this review we will analyze the current functional imaging techniques available (¹⁸F-Fluorodeoxiglucose positron emission tomography/computed tomography, diffusion-weighted imaging, dynamic contrast-enhanced MRI, diffusion tensor imaging and MR spectroscopy) for the evaluation of mediastinal lesions, with a focus in their correct acquisition and post-processing. Also, to review the clinical applications of these techniques in the diagnostic approach of benign and malignant conditions of the mediastinum.

Hypoxia, angiogenesis, and metabolism in the hereditary kidney cancers

The field of hereditary kidney cancer has begun to mature following the identification of several germline syndromes that define genetic and molecular features of this cancer. Molecular defects within these hereditary syndromes demonstrate consistent deficits in angiogenesis and metabolic signaling, largely driven by altered hypoxia signaling. The classical mutation, loss of function of the von Hippel-Lindau (VHL) tumor suppressor, provides a human pathogenesis model for critical aspects of pseudohypoxia. These features are mimicked in a less common hereditary renal tumor syndrome, known as hereditary leiomyomatosis and renal cell carcinoma. Here, we review renal tumor angiogenesis and metabolism from a HIF-centric perspective, considering alterations in the hypoxic landscape, and molecular deviations resulting from high levels of HIF family members. Mutations underlying HIF deregulation drive multifactorial aberrations in angiogenic signals and metabolism. The mechanisms by which these defects drive tumor growth are still emerging. However, the distinctive patterns of angiogenesis and glycolysis-/glutamine-dependent bioenergetics provide insight into the cellular environment of these cancers. The result is a scenario permissive for aggressive tumorigenesis especially within the proximal renal tubule. These features of tumorigenesis have been highly actionable in kidney cancer treatments, and will likely continue as central tenets of kidney cancer therapeutics.

Sampling arterial input function (AIF) from peripheral arteries: Comparison of a temporospatial-feature based method against conventional manual method

It is often difficult to accurately localize small arteries in images of peripheral organs, and even more so with vascular abnormality vasculatures, including collateral arteries, in peripheral artery disease (PAD). This poses a challenge for manually sampling arterial input function (AIF) in quantifying dynamic contrast-enhanced (DCE) MRI data of peripheral organs. In this study, we designed a multi-step screening approach that utilizes both the temporal and spatial information of the dynamic images, and is presumably suitable for localizing small and unpredictable peripheral arteries. In 41 DCE MRI datasets acquired from human calf muscles, the proposed method took <5 s on average for sampling AIF for each case, much more efficient than the manual sampling method; AIFs by the two methods were comparable, with Pearson's correlation coefficient of 0.983 ± 0.004 (p-value < 0.01) and relative difference of 2.4% ± 2.6%. In conclusion, the proposed temporospatial-feature based method enables efficient and accurate sampling of AIF from peripheral arteries, and would improve measurement precision and inter-observer consistency for quantitative DCE MRI of peripheral tissues.

Molecular Beacon Gold Nanosensors for Leucine-Rich Alpha-2-Glycoprotein-1 Detection in Pathological Angiogenesis

Leucine-rich alpha-2-glycoprotein-1 (Lrg1) is an emerging biomarker for angiogenesis. Its expression in ocular tissues is up-regulated in both human patients with proliferative diabetic retinopathy and rodent models of pathological angiogenesis. However, there is no existing sensor that allows visualization and monitoring of Lrg1 expression noninvasively and in real time. Herein, we report a nucleic acid-gold nanorod-based nanosensor for the noninvasive monitoring of cellular Lrg1 expression in angiogenesis. Specifically, this platform is constructed by covalently conjugating molecular beacons onto gold nanorods, which prequench the fluorophores on the molecular beacons. Upon intracellular entry and endosomal escape, the complexes interact with cellular Lrg1 mRNA through hybridization of the loop area of the molecular beacons. This complexation distances the fluorophores from nanorod and restores the prequenched fluorescence. The reliability of this platform is confirmed by examining the increased Lrg1 expression in migrating keratinocytes and the Lrg1 gene changes in different postnatal stages of mouse retinal vasculature growth in the mouse retina model.

Acoustically modulated magnetic resonance imaging of gas-filled protein nanostructures

Non-invasive biological imaging requires materials capable of interacting with deeply penetrant forms of energy such as magnetic fields and sound waves. Here, we show that gas vesicles (GVs), a unique class of gas-filled protein nanostructures with differential magnetic susceptibility relative to water, can produce robust contrast in magnetic resonance imaging (MRI) at sub-nanomolar concentrations, and that this contrast can be inactivated with ultrasound in situ to enable background-free imaging. We demonstrate this capability in vitro, in cells expressing these nanostructures as genetically encoded reporters, and in three model in vivo scenarios. Genetic variants of GVs, differing in their magnetic or mechanical phenotypes, allow multiplexed imaging using parametric MRI and differential acoustic sensitivity. Additionally, clustering-induced changes in MRI contrast enable the design of dynamic molecular sensors. By coupling the complementary physics of MRI and ultrasound, this nanomaterial gives rise to a distinct modality for molecular imaging with unique advantages and capabilities.

Tumor Tissue Detection using Blood-Oxygen-Level-Dependent Functional MRI based on Independent Component Analysis

Accurate delineation of gliomas from the surrounding normal brain areas helps maximize tumor resection and improves outcome. Blood-oxygen-level-dependent (BOLD) functional MRI (fMRI) has been routinely adopted for presurgical mapping of the surrounding functional areas. For completely utilizing such imaging data, here we show the feasibility of using presurgical fMRI for tumor delineation. In particular, we introduce a novel method dedicated to tumor detection based on independent component analysis (ICA) of resting-state fMRI (rs-fMRI) with automatic tumor component identification. Multi-center rs-fMRI data of 32 glioma patients from three centers, plus the additional proof-of-concept data of 28 patients from the fourth center with non-brain musculoskeletal tumors, are fed into individual ICA with different total number of components (TNCs). The best-fitted tumor-related components derived from the optimized TNCs setting are automatically determined based on a new template-matching algorithm. The success rates are 100%, 100% and 93.75% for glioma tissue detection for the three centers, respectively, and 85.19% for musculoskeletal tumor detection. We propose that the high success rate could come from the previously overlooked ability of BOLD rs-fMRI in characterizing the abnormal vascularization, vasomotion and perfusion caused by tumors. Our findings suggest an additional usage of the rs-fMRI for comprehensive presurgical assessment.

Nilotinib Enhances Tumor Angiogenesis and Counteracts VEGFR2 Blockade in an Orthotopic Breast Cancer Xenograft Model with Desmoplastic Response

Vascular endothelial growth factor (VEGF)/VEGF receptor (VEGFR)-targeted therapies predominantly affect nascent, immature tumor vessels. Since platelet-derived growth factor receptor (PDGFR) blockade inhibits vessel maturation and thus increases the amount of immature tumor vessels, we evaluated whether the combined PDGFR inhibition by nilotinib and VEGFR2 blockade by DC101 has synergistic therapy effects in a desmoplastic breast cancer xenograft model. In this context, besides immunohistological evaluation, molecular ultrasound imaging with BR55, the clinically used VEGFR2-targeted microbubbles, was applied to monitor VEGFR2-positive vessels noninvasively and to assess the therapy effects on tumor angiogenesis. DC101 treatment alone inhibited tumor angiogenesis, resulting in lower tumor growth and in significantly lower vessel density than in the control group after 14 days of therapy. In contrast, nilotinib inhibited vessel maturation but enhanced VEGFR2 expression, leading to markedly increased tumor volumes and a significantly higher vessel density. The combination of both drugs led to an almost similar tumor growth as in the DC101 treatment group, but VEGFR2 expression and microvessel density were higher and comparable to the controls. Further analyses revealed significantly higher levels of tumor cell–derived VEGF in nilotinib-treated tumors. In line with this, nilotinib, especially in low doses, induced an upregulation of VEGF and IL-6 mRNA in the tumor cells in vitro, thus providing an explanation for the enhanced angiogenesis observed in nilotinib-treated tumors in vivo. These findings suggest that nilotinib inhibits vessel maturation but counteracts the effects of antiangiogenic co-therapy by enhancing VEGF expression by the tumor cells and stimulating tumor angiogenesis.

Nano-sized and other improved reporters for magnetic resonance imaging of angiogenesis

Magnetic Resonance Imaging (MRI) enables to provide anatomical, functional and molecular information of pathological angiogenesis when used with properly tailored imaging probes. Functional studies have been the domain of Dynamic Contrast Enhancement (DCE) -MRI protocols from which it is possible to extract quantitative estimations on key parameters such as the volumes of vascular and extracellular compartments and the rates of the bidirectional exchange of the imaging reporters across the endothelial barrier. Whereas paramagnetic Gd-complexes able to reversibly bind to serum albumin act better than the clinically used small-sized, hydrophilic species, new findings suggest that an accurate assessment of the vascular volume is possible by analyzing images acquired upon the i.v. administration of Gd-labelled Red Blood Cells (RBCs). As far as it concerns molecular MRI, among the many available biomarkers, α_vβ₃ integrins are the most investigated ones. The low expression of these targets makes mandatory the use of nano-sized systems endowed with the proper signal enhancing capabilities. A number of targeted nano-particles have been investigated including micelles, liposomes, iron oxides and perfluorocarbon containing systems. Finally, a growing attention is devoted to the design and testing of "theranostic" agents based on the exploitation of MRI to monitor drug delivery processes and therapeutic outcome.

Differentiation between Treatment-Induced Necrosis and Recurrent Tumors in Patients with Metastatic Brain Tumors: Comparison among 11C-Methionine-PET, FDG-PET, MR Permeability Imaging, and MRI-ADC-Preliminary Results

BACKGROUND AND PURPOSE

In patients with metastatic brain tumors after gamma knife radiosurgery, the superiority of PET using ¹¹C-methionine for differentiating radiation necrosis and recurrent tumors has been accepted. To evaluate the feasibility of MR permeability imaging, it was compared with PET using ¹¹C-methionine, FDG-PET, and DWI for differentiating radiation necrosis from recurrent tumors.

MATERIALS AND METHODS

The study analyzed 18 lesions from 15 patients with metastatic brain tumors who underwent gamma knife radiosurgery. Ten lesions were identified as recurrent tumors by an operation. In MR permeability imaging, the transfer constant between intra- and extravascular extracellular spaces (/minute), extravascular extracellular space, the transfer constant from the extravascular extracellular space to plasma (/minute), the initial area under the signal intensity-time curve, contrast-enhancement ratio, bolus arrival time (seconds), maximum slope of increase (millimole/second), and fractional plasma volume were calculated. ADC was also acquired. On both PET using ¹¹C-methionine and FDG-PET, the ratio of the maximum standard uptake value of the lesion divided by the maximum standard uptake value of the symmetric site in the contralateral cerebral hemisphere was measured (¹¹C-methionine ratio and FDG ratio, respectively). The receiver operating characteristic curve was used for analysis.

RESULTS

The area under the receiver operating characteristic curve for differentiating radiation necrosis from recurrent tumors was the best for the ¹¹C-methionine ratio (0.90) followed by the contrast-enhancement ratio (0.81), maximum slope of increase (millimole/second) (0.80), the initial area under the signal intensity-time curve (0.78), fractional plasma volume (0.76), bolus arrival time (seconds) (0.76), the transfer constant between intra- and extravascular extracellular spaces (/minute) (0.74), extravascular extracellular space (0.68), minimum ADC (0.60), the transfer constant from the extravascular extracellular space to plasma (/minute) (0.55), and the FDG-ratio (0.53). A significant difference in the ¹¹C-methionine ratio (P < .01), contrast-enhancement ratio (P < .01), maximum slope of increase (millimole/second) (P < .05), and the initial area under the signal intensity-time curve (P < .05) was evident between radiation necrosis and recurrent tumor.

CONCLUSIONS

The present study suggests that PET using ¹¹C-methionine may be superior to MR permeability imaging, ADC, and FDG-PET for differentiating radiation necrosis from recurrent tumors after gamma knife radiosurgery for metastatic brain tumors.

Whole-body MRI, dynamic contrast-enhanced MRI, and diffusion-weighted imaging for the staging of multiple myeloma

Magnetic resonance imaging (MRI) is the most sensitive imaging technique for the detection of bone marrow infiltration, and has therefore recently been included in the new diagnostic myeloma criteria, as proposed by the International Myeloma Working Group. Nevertheless, conventional MRI only provides anatomical information and is therefore only of limited use in the response assessment of patients with multiple myeloma. The additional information from functional MRI techniques, such as diffusion-weighted imaging and dynamic contrast-enhanced MRI, can improve the detection rate of bone marrow infiltration and the assessment of response. This can further enhance the sensitivity and specificity of MRI in the staging of multiple myeloma patients. This article provides an overview of the technical aspects of conventional and functional MRI techniques with practical recommendations. It reviews the diagnostic performance, prognostic value, and role in therapy assessment in multiple myeloma and its precursor stages.

Characterization of the Tumor Microenvironment and Tumor-Stroma Interaction by Non-invasive Preclinical Imaging

Tumors are often characterized by hypoxia, vascular abnormalities, low extracellular pH, increased interstitial fluid pressure, altered choline-phospholipid metabolism, and aerobic glycolysis (Warburg effect). The impact of these tumor characteristics has been investigated extensively in the context of tumor development, progression, and treatment response, resulting in a number of non-invasive imaging biomarkers. More recent evidence suggests that cancer cells undergo metabolic reprograming, beyond aerobic glycolysis, in the course of tumor development and progression. The resulting altered metabolic content in tumors has the ability to affect cell signaling and block cellular differentiation. Additional emerging evidence reveals that the interaction between tumor and stroma cells can alter tumor metabolism (leading to metabolic reprograming) as well as tumor growth and vascular features. This review will summarize previous and current preclinical, non-invasive, multimodal imaging efforts to characterize the tumor microenvironment, including its stromal components and understand tumor-stroma interaction in cancer development, progression, and treatment response.

Diffusion-compensated tofts model suggests contrast leakage through aneurysm wall

PURPOSE

The purpose of this study was to investigate the diffusional transport of contrast agent and its effects on kinetic modeling of dynamic contrast enhanced (DCE) images.

METHODS

We performed simulations of our diffusion-compensated model and compared these results to human intracranial aneurysms (IAs). We derive an easy-to-use parameterization of diffusional effects that can provide an accurate estimate of diffusion corrected contrast agent leakage rates (k^trans ). Finally, we performed re-ansalysis of an existing data set to determine whether diffusion-corrected kinetic parameters improve the identification of high-risk IAs, thereby providing a new MRI-based imaging metric of IA stability based on wall integrity.

RESULTS

Probability distributions of simulated versus measured data show contrast leakage away from the aneurysm wall. Parameterization of diffusional effects on k^trans showed high correlation with long-chain methods in both surrounding tissue and near the aneurysm wall (r²  = 0.91 and r²  = 0.90, respectively). Finally, size, k^trans , and ( ktrans-kDCtrans) showed significant univariate relationships with rupture risk (P < 0.05).

CONCLUSIONS

We report the first evidence of diffusion-compensated permeability modeling in intracranial aneurysms and propose a parameterization of diffusional effects on k^trans . Furthermore, a comparison of measured versus simulated data suggests that contrast leakage occurs across the aneurysm wall. Magn Reson Med 78:2388-2398, 2017. © 2017 International Society for Magnetic Resonance in Medicine.

Assessing tumor vascularization as a potential biomarker of imatinib resistance in gastrointestinal stromal tumors by dynamic contrast-enhanced magnetic resonance imaging

BACKGROUND

Most metastatic gastrointestinal stromal tumors (GISTs) develop resistance to the first-line imatinib treatment. Recently, increased vessel density and angiogenic markers were reported in GISTs with a poor prognosis, suggesting that angiogenesis is implicated in GIST tumor progression and resistance. The purpose of this study was to investigate the relationship between tumor vasculature and imatinib resistance in different GIST mouse models using a noninvasive magnetic resonance imaging (MRI) functional approach.

METHODS

Immunodeficient mice (n = 8 for each cell line) were grafted with imatinib-sensitive (GIST882 and GIST-T1) and imatinib-resistant (GIST430) human cell lines. Dynamic contrast-enhanced MRI (DCE-MRI) was performed on GIST xenografts to quantify tumor vessel permeability (K ^trans) and vascular volume fraction (v _p). Microvessel density (MVD), permeability (mean dextran density, MDD), and angiogenic markers were evaluated by immunofluorescence and western blot assays.

RESULTS

Dynamic contrast-enhanced magnetic resonance imaging showed significantly increased vessel density (P < 0.0001) and permeability (P = 0.0002) in imatinib-resistant tumors compared to imatinib-sensitive ones. Strong positive correlations were observed between MRI estimates, K ^trans and v _p, and their related ex vivo values, MVD (r = 0.78 for K ^trans and r = 0.82 for v _p) and MDD (r = 0.77 for K ^trans and r = 0.94 for v _p). In addition, higher expression of vascular endothelial growth factor receptors (VEGFR2 and VEFGR3) was seen in GIST430.

CONCLUSIONS

Dynamic contrast-enhanced magnetic resonance imaging highlighted marked differences in tumor vasculature and microenvironment properties between imatinib-resistant and imatinib-sensitive GISTs, as also confirmed by ex vivo assays. These results provide new insights into the role that DCE-MRI could play in GIST characterization and response to GIST treatment. Validation studies are needed to confirm these findings.

Noninvasive Assessment of Losartan-Induced Increase in Functional Microvasculature and Drug Delivery in Pancreatic Ductal Adenocarcinoma

PURPOSE: Losartan, an angiotensin II receptor blocker, can reduce desmoplasia and enhance drug delivery and efficacy through improving interstitial transport and vascular perfusion in pancreatic ductal adenocarcinoma (PDAC) models in mice. The purpose of this study was to determine whether magnetic resonance imaging (MRI) of magnetic iron oxide nanoparticles (MNPs) and micro–positron emission tomography (PET) measurements could respectively detect improvements in tumor vascular parameters and drug uptake in orthotopic PDAC in mice treated with losartan. METHOD AND MATERIALS: All experiments were approved by the local Institutional Animal Care and Use Committee. FVB mice with orthotopic PDAC were treated daily with an i.p. injection of losartan (70 mg/kg) or saline (control vehicle) for 5 days. In order to calculate the fractional blood volume, vessel size index, and vessel density index, MRI was performed at 4.7 T following the injection of 3 mg/kg iron ferumoxytol (i.v.). Dynamic PET images were also acquired for 60 minutes using an ¹⁸F-5FU tracer dose of 200 μCi and analyzed for time activity curves normalized to muscle. Statistical analyses compared both cohorts using an unpaired two-tailed t test. RESULTS: In comparison to the control treatment, the losartan administration significantly increased the fractional blood volume (mean ± SEM) [12.1 ± 1.7 (n = 19) vs 6.7 ± 1.1 (n = 20); P < .02] and vessel size index (128.2 ± 35.6 vs 57.5 ± 18; P < .05). Losartan also induced a significant increase in the intratumoral uptake of ¹⁸F-5FU by 53% (P < .0001). CONCLUSION: MRI using FDA-approved MNPs provides a noninvasive, translatable means of assaying microvascular parameters induced by losartan in pancreatic cancer. PET measurements demonstrated that losartan significantly increased the uptake of ¹⁸F-5FU.

Targeting T1 and T2 dual modality enhanced magnetic resonance imaging of tumor vascular endothelial cells based on peptides-conjugated manganese ferrite nanomicelles

Tumor angiogenesis plays very important roles for tumorigenesis, tumor development, metastasis, and prognosis. Targeting T₁/T₂ dual modality magnetic resonance (MR) imaging of the tumor vascular endothelial cells (TVECs) with MR molecular probes can greatly improve diagnostic sensitivity and specificity, as well as helping to make an early diagnosis of tumor at the preclinical stage. In this study, a new T₁ and T₂ dual modality nanoprobe was successfully fabricated. The prepared nanoprobe comprise peptides CL 1555, poly(ε-caprolactone)-block-poly(ethylene glycol) amphiphilic copolymer shell, and dozens of manganese ferrite (MnFe₂O₄) nanoparticle core. The results showed that the hydrophobic MnFe₂O₄ nanoparticles were of uniform spheroidal appearance and narrow size distribution. Due to the self-assembled nanomicelles structure, the prepared probes were of high relaxivity of 281.7 mM⁻¹ s⁻¹, which was much higher than that of MnFe₂O₄ nanoparticles (67.5 mM 1 s⁻¹). After being grafted with the targeted CD105 peptide CL 1555, the nanomicelles can combine TVECs specifically and make the labeled TVECs dark in T₂-weighted MR imaging. With the passage on, the Mn²⁺ ions were released from MnFe₂O₄ and the size decreased gradually, making the signal intensity of the second and third passage of labeled TVECs increased in T₁-weighted MR imaging. Our results demonstrate that CL-poly(ethylene glycol)-MnFe₂O₄ can conjugate TVECs and induce dark and bright contrast in MR imaging, and act as a novel molecular probe for T₁- and T₂-enhanced MR imaging of tumor angiogenesis.

Noninvasively detecting Isocitrate dehydrogenase 1 gene status in astrocytoma by dynamic susceptibility contrast MRI

PURPOSE

To investigate the value of dynamic susceptibility contrast (DSC) magnetic resonance imaging (MRI) in the noninvasive evaluation of isocitrate dehydrogenase (IDH) 1 gene status in astrocytoma.

MATERIALS AND METHODS

The preoperative DSC MRI data of 91 lesions with pathologically confirmed astrocytoma were retrospectively analyzed. MR examination was performed on a 3T MRI scanner. The normalized maximum ratios of relative cerebral blood volume (rCBV ratio) of tumor parenchyma were measured. The enrolled astrocytoma patients were divided into six groups according to the World Health Organization (WHO) classification method and IDH1 gene status. The differences in the rCBV ratio of tumor parenchyma between the IDH1 gene mutant and wildtype groups of WHO grade II, III, and IV were compared and plotted receiver operating characteristic (ROC) curves were drawn.

RESULTS

The IDH1 gene mutant and wildtype groups of WHO grade II, III, and IV astrocytoma showed differences in the rCBV ratio (P = 0.005, 0.045, and 0.005, respectively). In WHO grade II, III, and IV astrocytoma, the area under the ROC curve was respectively 0.83, 0.86, and 0.94. The cutoff value of the rCBV ratio was respectively 2.20, 3.14, and 5.63.

CONCLUSION

The rCBV ratio value provided by DSC MRI provides a new potential imaging method for the noninvasive evaluation of the IDH1 status in astrocytoma.

LEVEL OF EVIDENCE

3 J. Magn. Reson. Imaging 2017;45:492-499.

Mathematical Models of Contrast Transport Kinetics for Cancer Diagnostic Imaging: A Review

Angiogenesis plays a fundamental role in cancer growth and the formation of metastasis. Novel cancer therapies aimed at inhibiting angiogenic processes and/or disrupting angiogenic tumor vasculature are currently being developed and clinically tested. The need for earlier and improved cancer diagnosis, and for early evaluation and monitoring of therapeutic response to angiogenic treatment, have led to the development of several imaging methods for in vivo noninvasive assessment of angiogenesis. The combination of dynamic contrast-enhanced imaging with mathematical modeling of the contrast agent kinetics enables quantitative assessment of the structural and functional changes in the microvasculature that are associated with tumor angiogenesis. In this paper, we review quantitative imaging of angiogenesis with dynamic contrast-enhanced magnetic resonance imaging, computed tomography, and ultrasound.

Functional assessment of glioma pathogenesis by in vivo multi-parametric magnetic resonance imaging and in vitro analyses

Gliomas are aggressive brain tumors with poor prognosis. In this study, we report a novel approach combining both in vivo multi-parametric MRI and in vitro cell culture assessments to evaluate the pathogenic development of gliomas. Osteopontin (OPN), a pleiotropic factor, has been implicated in the formation and progression of various human cancers, including gliomas, through its functions in regulating cell proliferation, survival, angiogenesis, and migration. Using rat C6 glioma model, the combined approach successfully monitors the acquisition and decrease of cancer hallmarks. We show that knockdown of the expression of OPN reduces C6 cell proliferation, survival, viability and clonogenicity in vitro, and reduces tumor burden and prolongs animal survival in syngeneic rats. OPN depletion is associated with reduced tumor growth, decreased angiogenesis, and an increase of tumor-associated metabolites, as revealed by T2-weighted images, diffusion-weighted images, K^trans maps, and 1H-MRS, respectively. These strategies allow us to define an important role of OPN in conferring cancer hallmarks, which can be further applied to assess the functional roles of other candidate genes in glioma. In particular, the non-invasive multi-parametric MRI measurement of cancer hallmarks related to proliferation, angiogenesis and altered metabolism may serve as a useful tool for diagnosis and for patient management.

Dynamic Contrast-enhanced MR Imaging of Advanced Hepatocellular Carcinoma: Comparison with the Liver Parenchyma and Correlation with the Survival of Patients Receiving Systemic Therapy

Purpose To retrospectively compare the perfusion parameters of advanced hepatocellular carcinoma (HCC) measured with dynamic contrast material-enhanced (DCE) magnetic resonance (MR) imaging with surrounding liver parenchyma to determine the relationship between these parameters and uncensored overall survival (OS). Materials and Methods This retrospective study had institutional review board approval, and informed consent was waived. DCE MR imaging was performed in 92 patients with advanced HCC before systemic treatment was administered (19 patients received a placebo). Three semiquantitative (peak, slope, and area under the gadolinium concentration-time curve [AUC]) and six quantitative (arterial fraction, arterial flow, portal flow, total blood flow, distribution volume, and mean transit time) parameters were calculated by placing regions of interest in the largest area of the tumor and background liver parenchyma. The DCE MR imaging parameters between the tumor and normal liver were compared with paired Wilcoxon test. By using the Cox proportional hazards model for univariate and multivariate analyses, the association of DCE MR imaging parameters and OS was investigated. Results HCC demonstrated significantly higher peak, slope, AUC, arterial fraction, and arterial flow but lower portal flow, distribution volume, and mean transit time than did the background liver (all P < .05). Patients with high peak in the tumor had longer OS (P = .005) than did those with low peak. Cox multivariate analysis identified peak as an independent predictor of OS (P = .032) after adjusting for age, sex, treatment, tumor size, and portal vein thrombosis. Conclusion DCE MR imaging parameters can be used to differentiate advanced HCC from the background liver, and peak, a semiquantitative parameter, is associated with outcome in patients with advanced HCC before systemic therapy. ^© RSNA, 2016 An earlier incorrect version of this article appeared online. This article was corrected on July 22, 2016.