Search

High acceleration factors in radial magnetic resonance fingerprinting (MRF) of the prostate lead to strong streak‐like artefacts from flow in the femoral blood vessels, possibly concealing important anatomical information. Region‐optimised virtual (ROVir) coils is a beamforming‐based framework to create virtual coils that maximise signal in a region of interest while minimising signal in a region of interference. In this study, the potential of removing femoral flow streak artefacts in prostate MRF using ROVir coils is demonstrated in silico and in vivo. The ROVir framework was applied to radial MRF k‐space data in an automated pipeline designed to maximise prostate signal while minimising signal from the femoral vessels. The method was tested in 15 asymptomatic volunteers at 3 T. The presence of streaks was visually assessed and measurements of whole prostate T1, T2 and signal‐to‐noise ratio (SNR) with and without streak correction were examined. In addition, a purpose‐built simulation framework in which blood flow through the femoral vessels can be turned on and off was used to quantitatively evaluate ROVir's ability to suppress streaks in radial prostate MRF. In vivo it was shown that removing selected ROVir coils visibly reduces streak‐like artefacts from the femoral blood flow, without increasing the reconstruction time. On average, 80% of the prostate SNR was retained. A similar reduction of streaks was also observed in silico, while the quantitative accuracy of T1 and T2 mapping was retained. In conclusion, ROVir coils efficiently suppress streaking artefacts from blood flow in radial MRF of the prostate, thereby improving the visual clarity of the images, without significant sacrifices to acquisition time, reconstruction time and accuracy of quantitative values. This is expected to help enable T1 and T2 mapping of prostate cancer in clinically viable times, aiding differentiation between prostate cancer from noncancer and healthy prostate tissue. [ABSTRACT FROM AUTHOR]

In this study, we investigated the potential of the multivariate curve resolution alternating least squares (MCR‐ALS) algorithm for analyzing three‐dimensional (3D) 1H‐MRSI data of the prostate in prostate cancer (PCa) patients. MCR‐ALS generates relative intensities of components representing spectral profiles derived from a large training set of patients, providing an interpretable model. Our objectives were to classify magnetic resonance (MR) spectra, differentiating tumor lesions from benign tissue, and to assess PCa aggressiveness. We included multicenter 3D 1H‐MRSI data from 106 PCa patients across eight centers. The patient cohort was divided into a training set (N = 63) and an independent test set (N = 43). Singular value decomposition determined that MR spectra were optimally represented by five components. The profiles of these components were extracted from the training set by MCR‐ALS and assigned to specific tissue types. Using these components, MCR‐ALS was applied to the test set for a quantitative analysis to discriminate tumor lesions from benign tissue and to assess tumor aggressiveness. Relative intensity maps of the components were reconstructed and compared with histopathology reports. The quantitative analysis demonstrated a significant separation between tumor and benign voxels (t‐test, p < 0.001). This result was achieved including voxels with low‐quality MR spectra. A receiver operating characteristic analysis of the relative intensity of the tumor component revealed that low‐ and high‐risk tumor lesions could be distinguished with an area under the curve of 0.88. Maps of this component properly identified the extent of tumor lesions. Our study demonstrated that MCR‐ALS analysis of 1H‐MRSI of the prostate can reliably identify tumor lesions and assess their aggressiveness. It handled multicenter data with minimal preprocessing and without using prior knowledge or quality control. These findings indicate that MCR‐ALS can serve as an automated tool to assess the presence, extent, and aggressiveness of tumor lesions in the prostate, enhancing diagnostic capabilities and treatment planning of PCa patients. [ABSTRACT FROM AUTHOR]

Background: The dual upregulation of TOP2A and EZH2 gene expression has been proposed as a biomarker for recurrence in prostate cancer patients to be treated with radical prostatectomy. A low tissue level of the metabolite citrate has additionally been connected to aggressive disease and recurrence in this patient group. However, for radiotherapy prostate cancer patients, few prognostic biomarkers have been suggested. The main aim of this study was to use an integrated tissue analysis to evaluate metabolites and expression of TOP2A and EZH2 as predictors for recurrence among radiotherapy patients. Methods: From 90 prostate cancer patients (56 received neoadjuvant hormonal treatment), 172 transrectal ultrasound‐guided (TRUS) biopsies were collected prior to radiotherapy. Metabolic profiles were acquired from fresh frozen TRUS biopsies using high resolution‐magic angle spinning MRS. Histopathology and immunohistochemistry staining for TOP2A and EZH2 were performed on TRUS biopsies containing cancer cells (n = 65) from 46 patients, where 24 of these patients (n = 31 samples) received hormonal treatment. Eleven radical prostatectomy cohorts of a total of 2059 patients were used for validation in a meta‐analysis. Results: Among radiotherapy patients with up to 11 years of follow‐up, a low level of citrate was found to predict recurrence, p = 0.001 (C‐index = 0.74). Citrate had a higher predictive ability compared with individual clinical variables, highlighting its strength as a potential biomarker for recurrence. The dual upregulation of TOP2A and EZH2 was suggested as a biomarker for recurrence, particularly for patients not receiving neoadjuvant hormonal treatment, p = 0.001 (C‐index = 0.84). While citrate was a statistically significant biomarker independent of hormonal treatment status, the current study indicated a potential of glutamine, glutamate and choline as biomarkers for recurrence among patients receiving neoadjuvant hormonal treatment, and glucose among patients not receiving neoadjuvant hormonal treatment. Conclusion: Using an integrated approach, our study shows the potential of citrate and the dual upregulation of TOP2A and EZH2 as biomarkers for recurrence among radiotherapy patients. [ABSTRACT FROM AUTHOR]

Patient‐derived cancer cells cultured in vitro are a cornerstone of cancer metabolism research. More recently, the introduction of organoids has provided the research community with a more versatile model system. Physiological structure and organization of the cell source tissue are maintained in organoids, representing a closer link to in vivo tumor models. High‐resolution magic angle spinning magnetic resonance spectroscopy (HR MAS MRS) is a commonly applied analytical approach for metabolic profiling of intact tissue, but its use has not been reported for organoids. The aim of the current work was to compare the performance of HR MAS MRS and extraction‐based nuclear magnetic resonance (NMR) in metabolic profiling of wild‐type and tumor progression organoids (TPOs) from human colon cancer, and further to investigate how the sequentially increased genetic alterations of the TPOs affect the metabolic profile. Sixteen metabolites were reliably identified and quantified both in spectra based on NMR of extracts and HR MAS MRS of intact organoids. The metabolite concentrations from the two approaches were highly correlated (r = 0.94), and both approaches were able to capture the systematic changes in metabolic features introduced by the genetic alterations characteristic of colorectal cancer progression (e.g., increased levels of lactate and decreased levels of myo‐inositol and phosphocholine with an increasing number of mutations). The current work highlights that HR MAS MRS is a well‐suited method for metabolic profiling of intact organoids, with the additional benefit that the nondestructive nature of HR MAS enables subsequent recovery of the organoids for further analyses based on nucleic acids or proteins. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this study was to investigate the effects of echo time dependence in IVIM quantification of the pseudo‐diffusion fraction in breast cancer and whether correcting for the echo time dependence offers added clinical value. Materials and methods: Fifteen patients with biopsy‐proven breast cancer underwent a 3 T MRI examination with an extended DWI protocol at two different echo times (TE = 53 ms, b = 0, 50 s/mm2; TE = 77 ms, b = 0, 50, 120, 200, 400, 700 s/mm2). Volumes of interest were delineated around the tumors. In addition, simulated MRI data were generated for different levels of signal‐to‐noise ratio and two values for the blood T2 relaxation time (T2p = 100 ms and 150 ms). The pseudo‐diffusion signal fraction was estimated from the simulated and in vivo tumor data using both the standard IVIM model and an extended IVIM model that accounts for the echo time dependence arising from distinct transverse relaxation times. Results: Simulations showed that the standard IVIM model overestimated the pseudo‐diffusion fraction by 25% (T2p = 100 ms) and 60 % (T2p = 150 ms) (p < 0.0001 at SNR = 50). In vivo, the estimated apparent T2 value at b = 50 s/mm2 was around 8% lower than at b = 0 s/mm2 (p = 0.01) demonstrating a removal of the signal contribution from blood with long T2 associated with pseudo‐diffusion. Using two different fixed values for T2p = 100, 150 ms, the pseudo‐diffusion fraction was 15% and 46% higher in the standard model compared with the echo‐time‐corrected model (p < 0.01). Conclusion: The standard IVIM model was found to overestimate the pseudo‐diffusion fraction by 15% to 46% compared with the echo‐time‐corrected model in breast tumor DWI data acquired at 3 T. Our results suggest that a corrected model may give more accurate results in terms of signal fractions, but may not justify the added time needed to acquire the additional data in terms of clinical value. [ABSTRACT FROM AUTHOR]

Purpose This study aimed to evaluate whether MR metabolic profiling can be used for prediction of long-term survival and monitoring of treatment response in locally advanced breast cancer patients during neoadjuvant chemotherapy (NAC). Methods: High resolution magic angle spinning (HR MAS) MR spectra of pre- and post-treatment biopsies from 33 patients were acquired. Tissue concentrations of choline-containing metabolites (tCho), glycine and taurine were assessed using electronic reference to access in vivo concentration (ERETIC) of the signal and receiver operating characteristic (ROC) curves was used to define their potential to predict patient survival and treatment response. The metabolite profiles obtained by HR MAS spectroscopy were related to long-term survival and treatment response by genetic algorithm partial least squares discriminant analysis (GA PLS-DA). Results Different pre-treatment MR metabolic profiles characterized by higher levels of tCho and lower levels of lactate were observed in patients with long-term survival (≥5 years, survivors) compared to patients who died of cancer recurrence (<5 years, non-survivors). A significant decrease in glycerophosphocholine (GPC) post-treatment was associated with long-term survival ( p = 0.046) and partial response ( p = 0.014) to NAC. Long-term survival was best predicted by GPC using ROC analyses (sens. 66.7%, spec. 62.5%), while taurine had the best predictive value of treatment response (sens. 72.7%, spec. 63.2%). GA PLS-DA multivariate classification models successfully discriminated between survivors and non-survivors, resulting in 82.7% and 90.2% cross-validation (CV) classification accuracy, pre- and post-treatment, respectively. Classification of treatment response using GA PLS-DA was not successful for this patient cohort. Conclusions Our results demonstrate that HR MAS MR metabolic profiles consisting of important metabolic characteristics of breast cancer tumors could potentially assist the classification and prediction of long-term survival in locally advanced breast cancer patients, in addition to being used as an adjunct for evaluation of treatment response to NAC. Copyright © 2011 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The purpose of this study was to evaluate the use of dynamic contrast-enhanced (DCE) MRI, in vivo 1H MRS and ex vivo high resolution magic angle spinning (HR MAS) MRS of tissue samples as methods to detect early treatment effects of docetaxel in a breast cancer xenograft model (MCF-7) in mice. MCF-7 cells were implanted subcutaneously in athymic mice and treated with docetaxel (20, 30, and 40 mg/kg) or saline six weeks later. DCE-MRI and in vivo 1H MRS were performed on a 7 T MR system three days after treatment. The dynamic images were used as input for a two-compartment model, yielding the vascular parameters Ktrans and ve. HR MAS MRS, histology, and immunohistochemical staining for proliferation (Ki-67), apoptosis (M30 cytodeath), and vascular/endothelial cells (CD31) were performed on excised tumor tissue. Both in vivo spectra and HR MAS spectra were used as input for multivariate analysis (principal component analysis (PCA) and partial least squares regression analysis (PLS)) to compare controls to treated tumors. Tumor growth was suppressed in docetaxel-treated mice compared to the controls. The anti-tumor effect led to an increase in Ktrans and ve values in all the treated groups. Furthermore, in vivo MRS and HR MAS MRS revealed a significant decrease in choline metabolite levels for the treated groups, in accordance with reduced proliferative index as seen on Ki-67 stained sections. In this study DCE-MRI, in vivo MRS and ex vivo HR MAS MRS have been used to demonstrate that docetaxel treatment of a human breast cancer xenograft model results in changes in the vascular dynamics and metabolic profile of the tumors. This indicates that these MR methods could be used to monitor intra-tumoral treatment effects. Copyright © 2009 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

In this work, we introduce spatial and chemical saturation options for artefact reduction in magnetic resonance fingerprinting (MRF) and assess their impact on T 1 and T 2 mapping accuracy. An existing radial MRF pulse sequence was modified to enable spatial and chemical saturation. Phantom experiments were performed to demonstrate flow artefact reduction and evaluate the accuracy of the T 1 and T 2 maps. As an in vivo demonstration, MRF of the prostate was performed on an asymptomatic volunteer using saturation modules to reduce flow-related artefacts. T 1 , T 2 and B 1 + maps obtained with and without saturation modules were compared. Application of spatial saturation in prostate MRF reduced streaking artefacts from the femoral vessels. When saturation is enabled T 1 accuracy is preserved, and T 2 accuracy remains acceptable up to approximately 100 ms. Chemical and spatial saturation can be incorporated into MRF sequences with limited impact on T 1 accuracy. Further sequence optimisation may be needed to accurately estimate long T 2 components. Spatial saturation modules have potential in prostate MRF applications as a means to reduce flow-related artefacts., (© 2025 The Author(s). NMR in Biomedicine published by John Wiley & Sons Ltd.)

The purpose of this study was to evaluate the use of dynamic contrast-enhanced (DCE) MRI, in vivo (1)H MRS and ex vivo high resolution magic angle spinning (HR MAS) MRS of tissue samples as methods to detect early treatment effects of docetaxel in a breast cancer xenograft model (MCF-7) in mice. MCF-7 cells were implanted subcutaneously in athymic mice and treated with docetaxel (20, 30, and 40 mg/kg) or saline six weeks later. DCE-MRI and in vivo (1)H MRS were performed on a 7 T MR system three days after treatment. The dynamic images were used as input for a two-compartment model, yielding the vascular parameters K(trans) and v(e). HR MAS MRS, histology, and immunohistochemical staining for proliferation (Ki-67), apoptosis (M30 cytodeath), and vascular/endothelial cells (CD31) were performed on excised tumor tissue. Both in vivo spectra and HR MAS spectra were used as input for multivariate analysis (principal component analysis (PCA) and partial least squares regression analysis (PLS)) to compare controls to treated tumors. Tumor growth was suppressed in docetaxel-treated mice compared to the controls. The anti-tumor effect led to an increase in K(trans) and v(e) values in all the treated groups. Furthermore, in vivo MRS and HR MAS MRS revealed a significant decrease in choline metabolite levels for the treated groups, in accordance with reduced proliferative index as seen on Ki-67 stained sections. In this study DCE-MRI, in vivo MRS and ex vivo HR MAS MRS have been used to demonstrate that docetaxel treatment of a human breast cancer xenograft model results in changes in the vascular dynamics and metabolic profile of the tumors. This indicates that these MR methods could be used to monitor intra-tumoral treatment effects.

The objectives of this study were to (a) explore the spectral characteristics of brain metastases, focusing on the origin of the primary cancer, and (b) evaluate the correlation with clinical outcome using multivariate analysis. High-resolution magic angle spinning (HR-MAS) MR spectra (n = 26) were obtained from 16 patients with brain metastases using a Bruker Avance DRX600 instrument. Standard pulse-acquired and spin-echo (TE 32 and 285 ms) (1)H spectra were obtained. These were examined using principal component analysis (PCA) and partial least squares regression analysis (PLS) relating spectral data to clinical outcome. The PCA score plot of pulse-acquired HR-MAS spectra showed a trend of clustering due to the origin of the metastases, mainly based on differences in the lipid signals at 1.3 and 0.9 ppm. With PLS, spectra of patients who died less than 5 months after surgery appeared to cluster in the lower left quadrant of the score plot. These preliminary results on brain metastasis classification and prediction of survival must be validated in a larger patient cohort. However, the possibility of differentiating metastases according to origin and predicting survival on the basis of HR-MAS spectra suggests that this method may be useful for diagnosing and planning treatment for brain metastases and also for guiding decisions about terminating further treatment.