7T CEST MRI: A potential imaging tool for the assessment of tumor grade and cell proliferation in breast cancer

Development and Validation of Four Different Methods to Improve MRI-CEST Tumor pH Mapping in Presence of Fat

CEST-MRI is an emerging imaging technique suitable for various in vivo applications, including the quantification of tumor acidosis. Traditionally, CEST contrast is calculated by asymmetry analysis, but the presence of fat signals leads to wrong contrast quantification and hence to inaccurate pH measurements. In this study, we investigated four post-processing approaches to overcome fat signal influences and enable correct CEST contrast calculations and tumor pH measurements using iopamidol. The proposed methods involve replacing the Z-spectrum region affected by fat peaks by (i) using a linear interpolation of the fat frequencies, (ii) applying water pool Lorentzian fitting, (iii) considering only the positive part of the Z-spectrum, or (iv) calculating a correction factor for the ratiometric value. In vitro and in vivo studies demonstrated the possibility of using these approaches to calculate CEST contrast and then to measure tumor pH, even in the presence of moderate to high fat fraction values. However, only the method based on the water pool Lorentzian fitting produced highly accurate results in terms of pH measurement in tumor-bearing mice with low and high fat contents.

Analysis of the Value of Quantitative Features in Multimodal MRI Images to Construct a Radio-Omics Model for Breast Cancer Diagnosis

Objective

To analyze the diagnostic value of quantitative features in multimodal magnetic resonance imaging (MRI) images to construct a radio-omics model for breast cancer.

Methods

Ninety-five patients with breast-related diseases from January 2020 to January 2021 were grouped into the benign group (n=57) and malignant group (n=38) according to the pathological findings. All cases were randomized as the training group (n=66) and validation group (n=29) in a 7:3 ratio based on the examination time. All subjects were examined by T1-weighted imaging (T1WI), T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), dynamic contrast enhancement (DCE), and apparent diffusion coefficient (ADC) multimodality MRI. The MRI findings were analyzed against pathological findings. A diagnostic breast cancer radiomics model was constructed. The diagnostic efficacy of the model in the validation group was analyzed, and the diagnostic efficacy was analyzed via the ROC curve.

Results

Fibroadenoma accounted for 49.12% of benign breast diseases, and invasive ductal carcinoma accounted for 73.68% of malignant breast diseases. The sensitivity of T1WI, T2WI, DWI, ADC, and DCE in diagnosing breast cancer was 61.14%, 66.67%, 73.30%, 78.95%, and 85.96%, using the four-fold table method. The area under the curves (AUCs) of T1WI, T2WI, DWI, ADC, and DCE for diagnosing breast cancer were 0.715, 0.769, 0.785, 0.835, and 0.792, respectively. The AUCs of plain scan, diffuse, enhanced, plain scan + diffuse, plain scan + enhanced, enhanced + diffuse, and plain scan + enhanced + diffuse for diagnosing breast cancer were 0.746, 0.798, 0.816, 0.839, 0.890, 0.906, and 0.927, respectively.

Conclusion

The construction of a radio-omics model by quantitative features in multimodal MRI images was valuable in the diagnosis of breast cancer. The value of radio-omics models such as plain scan + enhanced + diffuse was higher than the other models in diagnosing breast cancer and could be widely applied in clinical practice.

3D amide proton transfer-weighted imaging may be useful for diagnosing early-stage breast cancer: a prospective monocentric study

BACKGROUND

We investigated the value of three-dimensional amide proton transfer-weighted imaging (3D-APTWI) in the diagnosis of early-stage breast cancer (BC) and its correlation with the immunohistochemical characteristics of malignant lesions.

METHODS

Seventy-eight women underwent APTWI and dynamic contrast-enhanced (DCE)-MRI. Pathological results were categorized as either benign (n = 43) or malignant (n = 37) lesions. The parameters of APTWI and DCE-MRI were compared between the benign and malignant groups. The diagnostic value of 3D-APTWI was evaluated using the area under the receiver operating characteristic curve (ROC-AUC) to establish a diagnostic threshold. Pearson's correlation was used to analyze the correlation between the magnetization transfer asymmetry (MTRasym) and immunohistochemical characteristics.

RESULTS

The MTRasym and time-to-peak of malignancies were significantly lower than those of benign lesions (all p < 0.010). The volume transfer constant, rate constant, and wash-in and wash-out rates of malignancies were all significantly greater than those of benign lesions (all p < 0.010). ROC-AUCs of 3D-APTWI, DCE-MRI, and 3D-APTWI+DCE to differential diagnosis between early-stage BC and benign lesions were 0.816, 0.745, and 0.858, respectively. Only the difference between AUCAPT+DCE and AUCDCE was significant (p < 0.010). When a threshold of MTRasym for malignancy for 2.42%, the sensitivity and specificity of 3D-APTWI for BC diagnosis were 86.5% and 67.6%, respectively; MTRasym was modestly positively correlated with pathological grade (r = 0.476, p = 0.003) and Ki-67 (r = 0.419, p = 0.020).

CONCLUSIONS

3D-APTWI may be used as a supplementary method for patients with contraindications of DCE-MRI. MTRasym can imply the proliferation activities of early-stage BC.

RELEVANCE STATEMENT

3D-APTWI can be an alternative diagnostic method for patients with early-stage BC who are not suitable for contrast injection.

KEY POINTS

• 3D-APTWI reflects the changes in the microenvironment of early-stage breast cancer. • Combined 3D-APTWI is superior to DCE-MRI alone for early-stage breast cancer diagnosis. • 3D-APTWI improves the diagnostic accuracy of early-stage breast cancer.

Predicting histopathological types and molecular subtype of breast tumors: A comparative study using amide proton transfer-weighted imaging, intravoxel incoherent motion and diffusion kurtosis imaging

PURPOSE

To evaluate the predictive performance of multiparameter and histogram features derived from amide proton transfer-weighted imaging (APTWI), intravoxel incoherent motion (IVIM) and diffusion kurtosis imaging (DKI) for histopathological types of breast tumors.

METHODS

Region of interest (ROI) was delineated by outlining the largest slice of the tumor on the false-color images of the DKI, IVIM and APTWI parameters, and extracted the histogram features. Receiver operating characteristic (ROC) curve was used to evaluate the performance of parameters in predicting benign and malignant breast lesions, molecular prognostic biomarkers, lymph node status, and subtypes of breast lesions. The Spearman correlation coefficient was used to determine the correlations between each parameter and clinical-pathological factors.

RESULTS

All 52 breast lesions were enrolled in this prospective study, including 8 benign lesions and 44 breast cancers. To diagnose malignant and benign breast lesions, the value of APT (min) performed best, with the AUC reaching 0.983. According to the different imaging methods, the APTWI performed best. To predict the positive status of ER, PR, Ki67, the value of Dapp (uniformity), Dapp (uniformity), f (entropy) performed best, with the AUC values reaching 0.743, 0.770, 0.848, respectively. For the identification of Luminal B, HER2-enriched, and TNBC breast cancers, Kapp (max), f (kurtosis), and Dapp (uniformity) performed best, with AUC values reaching 0.679, 0.826, 0.771, respectively.

CONCLUSION

This study found the APTWI, IVIM and DKI parameters could diagnose breast cancer. The histogram features of DKI and IVIM, based on tumor heterogeneity, may help to predict breast cancer subtypes.

Breast-lesion assessment using amide proton transfer-weighted imaging and dynamic contrast-enhanced MR imaging

BACKGROUND

Previous studies have indicated that amide proton transfer-weighted imaging (APTWI) could be utilized for differentiating benign and malignant tumors. The APTWI technology has increasingly being applied to breast tumor research in recent years. However, according to the latest literature retrieval, no relevant previous studies compared the value of APTWI and dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) in distinguishing benign lesions from malignant lesions. In the present study, the application of APTWI and DCE for differentiating the benign and malignant breast lesions was investigated.

PATIENTS AND METHODS

APTWI was performed on 40 patients (42 lesions) who were enrolled in this prospective study. The lesions were split into two groups, one with malignant breast lesions (n = 28) and the other with benign breast lesions (n = 14), based on the results of the histology. The measured image characteristics (APT value, apparent diffusion coefficient [ADC] value, and time-of-intensity-curve [TIC] type) were compared between the two groups, and the ROC curve was used to quantify the diagnostic performance on the basis of these factors. The correlation between the APT values and the estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER-2), and Ki-67 expression levels and histological grades was examined using Spearman's correlation coefficient.

RESULTS

The measured APT and ADC values showed a strong inter-observer agreement according to the intraclass correlation coefficients (0.954 and 0.825). Compared to benign lesions, malignant lesions had significantly higher APT values (3.18 ± 1.07 and 2.01 ± 0.51, p < 0.001). Based on APTWI, DCE, diffusion-weighted imaging (DWI), and ADC + APTWI, ADC + DCE, and DCE + APTWI, the area-under-the-curve values were 0.915, 0.815, 0.878, 0.921, 0.916, and 0.936, respectively.

CONCLUSIONS

APTWI is a potentially promising method in differentiating benign and malignant breast lesions, and may it become a great substitute for DCE examination in the future.

CEST-MRI for body oncologic imaging: are we there yet?

Chemical exchange saturation transfer (CEST) MRI has gained recognition as a valuable addition to the molecular imaging and quantitative biomarker arsenal, especially for characterization of brain tumors. There is also increasing interest in the use of CEST-MRI for applications beyond the brain. However, its translation to body oncology applications lags behind those in neuro-oncology. The slower migration of CEST-MRI to non-neurologic applications reflects the technical challenges inherent to imaging of the torso. In this review, we discuss the application of CEST-MRI to oncologic conditions of the breast and torso (i.e., body imaging), emphasizing the challenges and potential solutions to address them. While data are still limited, reported studies suggest that CEST signal is associated with important histology markers such as tumor grade, receptor status, and proliferation index, some of which are often associated with prognosis and response to therapy. However, further technical development is still needed to make CEST a reliable clinical application for body imaging and establish its role as a predictive and prognostic biomarker.

Amide proton transfer (APT) imaging of breast cancers and its correlation with biological status

PURPOSE

To assess the usefulness of amide proton transfer (APT) imaging to predict the biological status of breast cancers.

METHOD

Sixty-six patients (age range 31-85 years, mean 58.9 years) with histopathologically proven invasive ductal carcinomas of 2 cm or larger in diameter were included in this study. 3D APT weighted imaging was conducted on a 3 T scanner. Mean APT signal intensity (SI) was analyzed in relation to biological subtypes, Ki-67 labeling index, and nuclear grades (NGs).

RESULTS

The triple-negative (TN) cancers (n = 10; 2.75 ± 0.42%) showed significantly higher APT SI than the luminal type cancers (n = 48; 1.74 ± 0.83) and HER2 cancers (n = 8; 1.83 ± 0.21) (P = 0.0007, 0.03). APT SI had weakly positive correlation with the Ki-67 labeling index (r = 0.38, P = 0.002). The mean APT SIs were significantly higher for high-Ki-67 (>30%) (n = 31; 2.25 ± 0.70) than low-Ki-67 (≤30%) cancers (n = 35; 1.60 ± 0.79) (P = 0.0007). There was no significant difference in the APT SIs between NG 1-2 (n = 31; 1.71 ± 0.84) and NG 3 (n = 35; 2.08 ± 0.76%) cancers (P = 0.06).

CONCLUSIONS

TN and high-Ki-67 breast cancers showed high APT SIs. APT imaging can help to predict the biological status of breast cancers.

Breast Amide Proton Transfer Imaging at 3 T: Diagnostic Performance and Association With Pathologic Characteristics

BACKGROUND

Amide proton transfer (APT) imaging has been increasingly applied in tumor characterization. However, its value in evaluating breast cancer remains undetermined.

PURPOSE

To assess the diagnostic performance of APT imaging in breast cancer and its association with prognostic histopathologic characteristics.

STUDY TYPE

Prospective.

SUBJECTS

Eighty-four patients with breast lesions.

FIELD STRENGTH/SEQUENCE

A 3.0 T/single-shot fast spin echo APT imaging.

ASSESSMENT

APTw signal in breast lesion was quantified. Lesion malignancy, T stage, grades, Ki-67 index, molecular biomarkers (estrogen receptor [ER] expression, progesterone receptor [PR] expression, human epidermal growth factor receptor [HER-2] expression), molecular subtypes (luminal A, luminal B, triple negative, and HER-2 enriched) were determined.

STATISTICAL TESTS

Student t-test, one-way analysis of variance, receiver operating characteristic analysis, and Pearson's correlation with P < 0.05 as statistical significance.

RESULTS

APTw signal was significantly higher in malignant lesions (1.55% ± 1.24%) than in benign lesions (0.54% ± 1.13%), and in grade III lesions than in grade II lesions (1.65% ± 0.84% vs. 0.96% ± 0.96%), and in T2- (1.57% ± 0.64%) and T3-stage lesions (1.54% ± 0.63%) than in T1-stage lesions (0.81% ± 0.64%) for invasive breast carcinoma of no special type. APTw signal significantly correlated with Ki-67 index (r = 0.364) but showed no significant difference in groups of ER (P = 0.069), PR (P = 0.069), HER-2 (P = 0.961), and among molecular subtypes (P = 0.073).

DATA CONCLUSION

APT imaging shows potential in differentiating breast lesion malignancy and associates with prognosis-related tumor grade, T stage, and proliferative activity.

EVIDENCE LEVEL

2 TECHNICAL EFFICACY: Stage 2.

Advanced Magnetic Resonance Imaging Modalities for Breast Cancer Diagnosis: An Overview of Recent Findings and Perspectives

Breast cancer is the most prevalent cancer among women and the leading cause of death. Diffusion-weighted imaging (DWI) and diffusion tensor imaging (DTI) are advanced magnetic resonance imaging (MRI) procedures that are widely used in the diagnostic and treatment evaluation of breast cancer. This review article describes the characteristics of new MRI methods and reviews recent findings on breast cancer diagnosis. This review study was performed on the literature sourced from scientific citation websites such as Google Scholar, PubMed, and Web of Science until July 2021. All relevant works published on the mentioned scientific citation websites were investigated. Because of the propensity of malignancies to limit diffusion, DWI can improve MRI diagnostic specificity. Diffusion tensor imaging gives additional information about diffusion directionality and anisotropy over traditional DWI. Recent findings showed that DWI and DTI and their characteristics may facilitate earlier and more accurate diagnosis, followed by better treatment. Overall, with the development of instruments and novel MRI modalities, it may be possible to diagnose breast cancer more effectively in the early stages.

Assessing the influence of the menstrual cycle on APT CEST-MRI in the human breast

PURPOSE

In fibroglandular breast tissue, conventional dynamic contrast-enhanced MR-mammography is known to be affected by water content changes during the menstrual cycle. Likewise, amide proton transfer (APT) chemical exchange saturation transfer (CEST)-MRI might be inherently prone to the menstrual cycle, as CEST signals are indirectly detected via the water signal. The purpose of this study was to investigate the influence of the menstrual cycle on APT CEST-MRI in fibroglandular breast tissue.

METHOD

Ten healthy premenopausal women (19-34 years) were included in this IRB approved prospective study and examined twice during their menstrual cycle. Examination one and two were performed during the first half (day 2-8) and the second half (day 15-21) of the menstrual cycle, respectively. As a reference for the APT signal in malignant breast tumor tissue, previously reported data of nine breast cancer patients were included in this study. CEST-MRI (B₁ = 0.7μT) was performed on a 7 T whole-body scanner followed by a multi-Lorentzian fit analysis. The APT signal was corrected for B₀/B₁-field inhomogeneities, fat signal contribution, and relaxation effects of the water signal and evaluated in the fibroglandular breast tissue. Intra-individual APT signal differences between examination one and two were compared using the Wilcoxon signed-rank test. The level of significance was set at p < 0.05.

RESULTS

The APT signal showed no significant difference in the fibroglandular breast tissue of healthy premenopausal volunteers throughout the menstrual cycle (p = 1.00) (examination 1 vs. examination 2: mean and standard deviation = 3.24 ± 0.68%Hz vs. 3.30 ± 0.73%Hz, median and IQR = 3.36%Hz and 0.87%Hz vs. 3.38%Hz and 0.71%Hz).

CONCLUSION

The present study provides an important basis for the clinical application of APT CEST-MRI as an additional contrast mechanism in MR-mammography, as menstrual cycle-related APT signal fluctuations seem to be negligible compared to the APT signal increase in breast cancer tissue.

Chemical Exchange Saturation Transfer for Pancreatic Ductal Adenocarcinoma Evaluation

OBJECTIVES

The aims of the study are to evaluate the feasibility of using pH-sensitive magnetic resonance imaging, chemical exchange saturation transfer (CEST) in pancreatic imaging and to differentiate pancreatic ductal adenocarcinoma (PDAC) with the nontumor pancreas (upstream and downstream) and normal control pancreas.

METHODS

Sixteen CEST images with PDAC and 12 CEST images with normal volunteers were acquired and magnetization transfer ratio with asymmetric analysis were measured in areas of PDAC, upstream, downstream, and normal control pancreas. One-way analysis of variance and receiver operating characteristic curve were used to differentiate tumor from nontumor pancreas.

RESULTS

Areas with PDAC showed higher signal intensity than upstream and downstream on CEST images. The mean (standard deviation) values of magnetization transfer ratio with asymmetric analysis were 0.015 (0.034), -0.044 (0.030), -0.019 (0.027), and -0.037 (0.031), respectively, in PDAC area, upstream, downstream, and nontumor area in patient group and -0.008 (0.024) in normal pancreas. Significant differences were found between PDAC and upstream ( P < 0.001), between upstream and normal pancreas ( P = 0.04). Area under curve is 0.857 in differentiating PDAC with nontumor pancreas.

CONCLUSIONS

pH-sensitive CEST MRI is feasible in pancreatic imaging and can be used to differentiate PDAC from nontumor pancreas. This provides a novel metabolic imaging method in PDAC.

Investigation of breast cancer microstructure and microvasculature from time-dependent DWI and CEST in correlation with histological biomarkers

We investigated the associations of time-dependent DWI, non-Gaussian DWI, and CEST parameters with histological biomarkers in a breast cancer xenograft model. 22 xenograft mice (7 MCF-7 and 15 MDA-MB-231) were scanned at 4 diffusion times [T_d = 2.5/5 ms with 11 b-values (0–600 s/mm²) and T_d = 9/27.6 ms with 17 b-values (0–3000 s/mm²), respectively]. The apparent diffusion coefficient (ADC) was estimated using 2 b-values in different combinations (ADC^0–600 using b = 0 and 600 s/mm² and shifted ADC [sADC^200–1500] using b = 200 and 1500 s/mm²) at each of those diffusion times. Then the change (Δ) in ADC/sADC between diffusion times was evaluated. Non-Gaussian diffusion and intravoxel incoherent motion (IVIM) parameters (ADC₀, the virtual ADC at b = 0; K, Kurtosis from non-Gaussian diffusion; f, the IVIM perfusion fraction) were estimated. CEST images were acquired and the amide proton transfer signal intensity (APT SI) were measured. The ΔsADC_9–27.6 (between \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\text{sADC}}_{{9\,{\text{ms}}}}^{200{-}1500}$$\end{document}sADC9ms200-1500 and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\text{sADC}}_{{27.6\,{\text{ms}}}}^{200{-}1500}$$\end{document}sADC27.6ms200-1500 and ΔADC_2.5_sADC_27.6 (between \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\text{ADC}}_{{2.5\, {\text{ms}}}}^{0{-}600}$$\end{document}ADC2.5ms0-600 and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\text{sADC}}_{{27.6\,{\text{ms}}}}^{200{-}1500}$$\end{document}sADC27.6ms200-1500) was significantly larger for MCF-7 groups, and ΔADC_2.5_sADC_27.6 was positively correlated with Ki67_max and APT SI. ADC₀ decreased significantly in MDA-MB-231 group and K increased significantly with T_d in MCF-7 group. APT SI and cellular area had a moderately strong positive correlation in MDA-MB-231 and MCF-7 tumors combined, and there was a positive correlation in MDA-MB-231 tumors. There was a significant negative correlation between APT SI and the Ki-67-positive ratio in MDA-MB-231 tumors and when combined with MCF-7 tumors. The associations of ΔADC_2.5_sADC_27.6 and API SI with Ki-67 parameters indicate that the T_d-dependent DW and CEST parameters are useful to predict the histological markers of breast cancers.

7 Tesla and Beyond: Advanced Methods and Clinical Applications in Magnetic Resonance Imaging

ABSTRACT

Ultrahigh magnetic fields offer significantly higher signal-to-noise ratio, and several magnetic resonance applications additionally benefit from a higher contrast-to-noise ratio, with static magnetic field strengths of B0 ≥ 7 T currently being referred to as ultrahigh fields (UHFs). The advantages of UHF can be used to resolve structures more precisely or to visualize physiological/pathophysiological effects that would be difficult or even impossible to detect at lower field strengths. However, with these advantages also come challenges, such as inhomogeneities applying standard radiofrequency excitation techniques, higher energy deposition in the human body, and enhanced B0 field inhomogeneities. The advantages but also the challenges of UHF as well as promising advanced methodological developments and clinical applications that particularly benefit from UHF are discussed in this review article.

A Brief History and Future Prospects of CEST MRI in Clinical Non-Brain Tumor Imaging

Chemical exchange saturation transfer (CEST) MRI is a promising molecular imaging tool which allows the specific detection of metabolites that contain exchangeable amide, amine, and hydroxyl protons. Decades of development have progressed CEST imaging from an initial concept to a clinical imaging tool that is used to assess tumor metabolism. The first translation efforts involved brain imaging, but this has now progressed to imaging other body tissues. In this review, we summarize studies using CEST MRI to image a range of tumor types, including breast cancer, pelvic tumors, digestive tumors, and lung cancer. Approximately two thirds of the published studies involved breast or pelvic tumors which are sites that are less affected by body motion. Most studies conclude that CEST shows good potential for the differentiation of malignant from benign lesions with a number of reports now extending to compare different histological classifications along with the effects of anti-cancer treatments. Despite CEST being a unique 'label-free' approach with a higher sensitivity than MR spectroscopy, there are still some obstacles for implementing its clinical use. Future research is now focused on overcoming these challenges. Vigorous ongoing development and further clinical trials are expected to see CEST technology become more widely implemented as a mainstream imaging technology.

[Chemical exchange saturation transfer (CEST) : Magnetic resonance imaging in diagnostic oncology]

BACKGROUND

Contrast generation by chemical exchange saturation transfer (CEST) is a recently emerging magnetic resonance imaging (MRI) research field with high clinical potential.

METHODS

This review covers the methodological principles and summarizes the clinical experience of CEST imaging studies in diagnostic oncology performed to date.

RESULTS AND CONCLUSION

CEST enables the detection of lowly concentrated metabolites, such as peptides and glucose, through selective saturation of metabolite-bound protons and subsequent magnetization transfer to free water. This technology yields additional information about metabolic activity and the tissue microenvironment without the need for conventional contrast agents or radioactive tracers. Various studies, mainly conducted in patients with neuro-oncolgic diseases, suggest that this technology may aid to assess tumor malignancy as well as therapeutic response prior to and in the first follow-up after intervention.

KEY POINTS

CEST-MRI enables the indirect detection of metabolites without radioactive tracers or contrast agents. Clinical experience exists especially in the setting of neuro-oncologic imaging. In oncologic imaging, CEST-MRI may improve assessment of prognosis and therapy response.

Does perfusion computed tomography correlate to pathology in colorectal liver metastases?

Introduction

Targeted therapy against tumor angiogenesis is widely used in clinical practice for patients with colorectal liver metastases (CRLM). Possible predictive biomarkers for tumor angiogenesis, such as, microvessel density (MVD), hypoxia and cell proliferation, can be determined using immunohistochemical staining. However, patients ineligible for surgical treatment need to undergo invasive diagnostic interventions in order to determine these biomarkers. CT perfusion (CTP) is an emerging functional imaging technique, which can non-invasively determine vascular properties of solid tumors. The purpose of this study was to evaluate CTP with histological biomarkers in CRLM.

Material and methods

Patients with CRLM underwent CTP one day before liver surgery. CTP analysis was performed on the entire volume of the largest metastases in each patient. Dual-input maximum slope analysis was used and data concerning arterial flow (AF), portal flow (PF) and perfusion index (PI) were recorded. Immunohistochemical staining with CD34, M75/CA-IX and MIB-1 was performed on the rim in the midsection of the tumor to determine respectively MVD, hypoxia and cell proliferation.

Results

Twenty CRLM in 20 patients were studied. Mean size of the largest CRLM was 37 mm (95% CI 21–54 mm). Mean AF and PF were respectively 64 ml/min/100ml (95% CI 48–79) and 30 ml/min/100ml (95% CI 22–38). Mean PI was 68% (95% CI 62–73). No significant correlation was found between tumor growth patterns and CTP (p = 0.95). MVD did not significantly correlate to AF (r = 0.05; p = 0.84), PF (r = 0.17; p = 0.47) and PI (r = -0.12; p = 0.63). Cell proliferation also did not significantly correlate to AF (r = 0.07; p = 0.78), PF (r = -0.01; p = 0.95) and PI (r = 0.15; p = 0.52). Hypoxia did not significantly correlate to AF (r = -0.05; p = 0.83), however, significantly to PF (r = 0.51; p = 0.02) and a trend to negative correlation with PF (r = -0.43; p = 0.06). However, after controlling the false discovery rate, no significant correlation between CTP and used immunohistochemical biomarkers was found.

Conclusion

In conclusion, this feasibility study found a trend to negative correlation between PI and hypoxia, CTP might therefore possibly evaluate this prognostic marker in CRLM non-invasively. However, CTP is not an appropriate technique for the assessment of microvessels or cell proliferation in CRLM.

A fast multislice sequence for 3D MRI-CEST pH imaging

Purpose

Chemical exchange saturation transfer MRI can provide accurate pH images, but the slow scan time (due to long saturation periods and multiple offsets sampling) reduce both the volume coverage and spatial resolution capability, hence the possibility to interrogate the heterogeneity in tumors and organs. To overcome these limitations, we propose a fast multislice CEST‐MRI sequence with high pH accuracy and spatial resolution.

Methods

The sequence first uses a long saturation pulse to induce the steady‐state CEST contrast and a second short saturation pulse repeated after each image acquisition to compensate for signal losses based on an uneven irradiation scheme combined with a single‐shot rapid acquisition with refocusing echoes readout. Sequence sensitivity and accuracy in measuring pH was optimized by simulation and assessed by in vitro studies in pH‐varying phantoms. In vivo validation was performed in two applications by acquiring multislice pH images covering the whole tumors and kidneys after iopamidol injection.

Results

Simulated and in vivo data showed comparable contrast efficiency and pH responsiveness by reducing saturation time. The experimental data from a homogeneous, pH‐varying, iopamidol‐containing phantom show that the sequence produced a uniform CEST contrast across slices and accurate values across slices in less than 10 minutes. In vivo measurements allowed us to quantify the 3D pH gradients of tumors and kidneys, with pH ranges comparable with the literature.

Conclusion

The proposed fast multislice CEST‐MRI sequence allows volumetric acquisitions with good pH sensitivity, accuracy, and spatial resolution for several in vivo pH imaging applications.

A comparative study of the value of amide proton transfer-weighted imaging and diffusion kurtosis imaging in the diagnosis and evaluation of breast cancer

OBJECTIVES

To compare the value of amide proton transfer-weighted imaging (APTWI) and diffusion kurtosis imaging (DKI) in differentiating benign and malignant breast lesions and analyze the correlations between the derived parameters and prognostic factors of breast cancer.

METHODS

One hundred thirty-five women underwent breast APTWI and DKI. The magnetization transfer ratio asymmetry (MTRasym (3.5 ppm)), apparent kurtosis coefficient (K_app), and non-Gaussian diffusion coefficient (D_app) were calculated according to the histological subtype, grade, and prognostic factors (Ki-67, estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor-2 (HER-2), lymph node metastasis, and maximum lesion diameter). The differences, efficacy, and correlation between the parameters were determined.

RESULTS

The K_app value was higher and the D_app and MTRasym (3.5 ppm) values were lower in the malignant group than in the benign group (all p < 0.001; AUC (K_app) = 0.913, AUC (D_app) = 0.910, and AUC (MTRasym (3.5 ppm)) = 0.796). The differences in the AUC between K_app and MTRasym (3.5 ppm) and between D_app and MTRasym (3.5 ppm) were significant (p = 0.023, 0.046). K_app was moderately correlated with the pathological grade (|r| = 0.724) and mildly correlated with Ki-67 and HER-2 expression (|r| = 0.454, 0.333). D_app was moderately correlated with the pathological grade (|r| = 0.648) and mildly correlated with Ki-67 expression (|r| = 0.400). MTRasym (3.5 ppm) was only mildly correlated with the pathological grade (|r| = 0.468).

CONCLUSION

DKI is superior to APTWI in differentiating between benign and malignant breast lesions. Each parameter is correlated with some prognostic factors to a certain extent.

KEY POINTS

• DKI and APTWI provide valuable information regarding lesion characterization. • K_app, D_app, and MTRasym (3.5 ppm) are valid parameters for the characterization of tissue microstructure. • DKI is superior to APTWI in the study of breast cancer.

Relaxation-compensated CEST (chemical exchange saturation transfer) imaging in breast cancer diagnostics at 7T

PURPOSE

To investigate whether fat-corrected and relaxation-compensated amide proton transfer (APT) and guanidyl CEST-MRI enables the detection of signal intensity differences between breast tumors and normal-appearing fibroglandular tissue in patients with newly-diagnosed breast cancer.

METHOD

Ten patients with newly-diagnosed breast cancer and seven healthy volunteers were included in this prospective IRB-approved study. CEST-MRI was performed on a 7 T-whole-body scanner followed by a multi-Lorentzian fit analysis. APT and guanidyl CEST signal intensities were quantified in the tumor and in healthy fibroglandular tissue after correction of B₀/B₁-field inhomogeneities, fat signal contribution, T₁- and T₂-relaxation; signal intensity differences of APT and guanidyl resonances were compared using Mann-Whitney-U-tests. Pearson correlations between tumor CEST signal intensities and the proliferation index Ki-67 were performed.

RESULTS

APT CEST signal in tumor tissue (6.70 ± 1.38%Hz) was increased compared to normal-appearing fibroglandular tissue of patients (3.56 ± 0.54%Hz, p = 0.001) and healthy volunteers (3.70 ± 0.68%Hz, p = 0.001). Further, a moderate positive correlation was found between the APT signal and the proliferation index Ki-67 (R² = 0.367, r = 0.606, p = 0.11). Guanidyl CEST signal was also increased in tumor tissue (5.24 ± 1.85%Hz) compared to patients' (2.42 ± 0.45%Hz, p = 0.006) and volunteers' (2.36 ± 0.54%Hz, p < 0.001) normal-appearing fibroglandular tissue and a positive correlation with the Ki-67 level was observed (R² = 0.365, r = 0.604, p = 0.11). APT and guanidyl CEST signal in normal-appearing fibroglandular tissue was not different between patients and healthy volunteers (p = 0.88; p = 0.93).

CONCLUSION

Relaxation-compensated and fat-corrected CEST-MRI allowed a non-invasive differentiation of breast cancer and normal-appearing breast tissue. Thus, this approach represents a contrast agent-free method that may help to increase diagnostic accuracy in MR-mammography.

Comparative Study of Amide Proton Transfer-Weighted Imaging and Intravoxel Incoherent Motion Imaging in Breast Cancer Diagnosis and Evaluation

BACKGROUND

Amide proton transfer-weighted imaging (APTWI) and intravoxel incoherent motion imaging (IVIM) are valuable MRI techniques applied to cancer.

PURPOSE

To compare APTWI and IVIM in the diagnosis of benign and malignant breast lesions and to evaluate the correlations between different parameters (MTRasym [3.5 ppm], D, D*, and f) and prognostic factors for breast cancer.

STUDY TYPE

Retrospective.

POPULATION

In all, 123 breast lesions were studied before treatment, including 58 benign lesions and 65 malignant lesions.

FIELD STRENGTH/SEQUENCE

Conventional MRI (T₁ WI, T₂ WI, and diffusion-weighted imaging [DWI]), APTWI, and IVIM MRI at 3T.

ASSESSMENT

The magnetization transfer ratio asymmetry at 3.5 ppm (MTRasym [3.5 ppm]), diffusion coefficient (D), pseudo diffusion coefficient (D*), and perfusion fraction (f) values were compared between the benign and malignant groups and between groups with different expression levels of prognostic factors.

STATISTICAL TESTS

Individual sample t-test, χ² test, Spearman correlation, logistic regression, and the Delong test.

RESULTS

The D and MTRasym (3.5 ppm) values of the malignant group were lower than those of the benign group; however, D* and f values were higher than those of the benign group (all P < 0.05). The areas under the curve (AUCs) of D, MTRasym (3.5 ppm), D*, and f were 0.809, 0.778, 0.670, and 0.766, respectively; however, only the difference between AUC (D) and AUC (D*) was significant (Z = 2.374, P < 0.05). The D value showed a low correlation with the pathological grade and Ki-67 expression (| r | = 0.294, 0.367); the f value showed a low correlation with estrogen receptor (ER) expression (| r | = 0.382); and the MTRasym (3.5 ppm) value showed a low correlation with pathological grade (| r | = 0.371).

DATA CONCLUSION

This analysis revealed that both IVIM and APTWI could be used for the differential diagnosis of benign and malignant breast lesions, and APTWI-derived MTRasym (3.5 ppm), IVIM-derived D, D*, and f values showed correlations with some prognostic factors for breast cancer.

LEVEL OF EVIDENCE

2 TECHNICAL EFFICACY STAGE: 2 J. Magn. Reson. Imaging 2020;52:1175-1186.

Novel nanomedicine with a chemical-exchange saturation transfer effect for breast cancer treatment in vivo

BACKGROUND

Nanomedicine is a promising new approach to cancer treatment that avoids the disadvantages of traditional chemotherapy and improves therapeutic indices. However, the lack of a real-time visualization imaging technology to monitor drug distribution greatly limits its clinical application. Image-tracked drug delivery is of great clinical interest; it is useful for identifying those patients for whom the therapy is more likely to be beneficial. This paper discusses a novel nanomedicine that displays features of nanoparticles and facilitates functional magnetic resonance imaging but is challenging to prepare.

RESULTS

To achieve this goal, we synthesized an acylamino-containing amphiphilic block copolymer (polyethylene glycol-polyacrylamide-polyacetonitrile, PEG-b-P(AM-co-AN)) by reversible addition-fragmentation chain transfer (RAFT) polymerization. The PEG-b-P(AM-co-AN) has chemical exchange saturation transfer (CEST) effects, which enable the use of CEST imaging for monitoring nanocarrier accumulation and providing molecular information of pathological tissues. Based on PEG-b-P(AM-co-AN), a new nanomedicine PEG-PAM-PAN@DOX was constructed by nano-precipitation. The self-assembling nature of PEG-PAM-PAN@DOX made the synthesis effective, straightforward, and biocompatible. In vitro studies demonstrate decreased cytotoxicity of PEG-PAM-PAN@DOX compared to free doxorubicin (half-maximal inhibitory concentration (IC50), mean ~ 0.62 μg/mL vs. ~ 5 μg/mL), and the nanomedicine more efficiently entered the cytoplasm and nucleus of cancer cells to kill them. Further, in vivo animal experiments showed that the nanomedicine developed was not only effective against breast cancer, but also displayed an excellent sensitive CEST effect for monitoring drug accumulation (at about 0.5 ppm) in tumor areas. The CEST signal of post-injection 2 h was significantly higher than that of pre-injection (2.17 ± 0.88% vs. 0. 09 ± 0.75%, p < 0.01).

CONCLUSIONS

The nanomedicine with CEST imaging reflects the characterization of tumors and therapeutic functions has great potential medical applications.