Improved volume selective1H MR spectroscopic imaging of the prostate with gradient offset independent adiabaticity pulses at 3 tesla

A multivariate curve resolution analysis of multicenter proton spectroscopic imaging of the prostate for cancer localization and assessment of aggressiveness

In this study, we investigated the potential of the multivariate curve resolution alternating least squares (MCR-ALS) algorithm for analyzing three-dimensional (3D) 1 H-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 1 H-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 1 H-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.

Post-acquisition water-signal removal in 3D water-unsuppressed 1 H-MR spectroscopic imaging of the prostate

PURPOSE

To develop a robust processing procedure of raw signals from water-unsuppressed MRSI of the prostate for the mapping of absolute tissue concentrations of metabolites.

METHODS

Water-unsuppressed 3D MRSI data were acquired from a phantom, from healthy volunteers, and a patient with prostate cancer. Signal processing included sequential computation of the modulus of the FID to remove water sidebands, a Hilbert transformation, and k-space Hamming filtering. For the removal of the water signal, we compared Löwner tensor-based blind source separation (BSS) and Hankel Lanczos singular value decomposition techniques. Absolute metabolite levels were quantified with LCModel and the results were statistically analyzed to compare the water removal methods and conventional water-suppressed MRSI.

RESULTS

The post-processing algorithms successfully removed the water signal and its sidebands without affecting metabolite signals. The best water removal performance was achieved by Löwner tensor-based BSS. Absolute tissue concentrations of citrate in the peripheral zone derived from water-suppressed and unsuppressed ¹ H MRSI were the same and as expected from the known physiology of the healthy prostate. Maps for citrate and choline from water-unsuppressed 3D ¹ H-MRSI of the prostate showed expected spatial variations in metabolite levels.

CONCLUSION

We developed a robust relatively simple post-processing method of water-unsuppressed MRSI of the prostate to remove the water signal. Absolute quantification using the water signal, originating from the same location as the metabolite signals, avoids the acquisition of additional reference data.

Improving the Effective Spatial Resolution in 1H-MRSI of the Prostate with Three-Dimensional Overdiscretized Reconstructions

In in vivo ¹H-MRSI of the prostate, small matrix sizes can cause voxel bleeding extending to regions far from a voxel, dispersing a signal of interest outside that voxel and mixing extra-prostatic residual lipid signals into the prostate. To resolve this problem, we developed a three-dimensional overdiscretized reconstruction method. Without increasing the acquisition time from current 3D MRSI acquisition methods, this method is aimed to improve the localization of metabolite signals in the prostate without compromising on SNR. The proposed method consists of a 3D spatial overdiscretization of the MRSI grid, followed by noise decorrelation with small random spectral shifts and weighted spatial averaging to reach a final target spatial resolution. We successfully applied the three-dimensional overdiscretized reconstruction method to 3D prostate ¹H-MRSI data at 3T. Both in phantom and in vivo, the method proved to be superior to conventional weighted sampling with Hamming filtering of k-space. Compared with the latter, the overdiscretized reconstructed data with smaller voxel size showed up to 10% less voxel bleed while maintaining higher SNR by a factor of 1.87 and 1.45 in phantom measurements. For in vivo measurements, within the same acquisition time and without loss of SNR compared with weighted k-space sampling and Hamming filtering, we achieved increased spatial resolution and improved localization in metabolite maps.

Emerging MR methods for improved diagnosis of prostate cancer by multiparametric MRI

Current challenges of using serum prostate-specific antigen (PSA) level-based screening, such as the increased false positive rate, inability to detect clinically significant prostate cancer (PCa) with random biopsy, multifocality in PCa, and the molecular heterogeneity of PCa, can be addressed by integrating advanced multiparametric MR imaging (mpMRI) approaches into the diagnostic workup of PCa. The standard method for diagnosing PCa is a transrectal ultrasonography (TRUS)-guided systematic prostate biopsy, but it suffers from sampling errors and frequently fails to detect clinically significant PCa. mpMRI not only increases the detection of clinically significant PCa, but it also helps to reduce unnecessary biopsies because of its high negative predictive value. Furthermore, non-Cartesian image acquisition and compressed sensing have resulted in faster MR acquisition with improved signal-to-noise ratio, which can be used in quantitative MRI methods such as dynamic contrast-enhanced (DCE)-MRI. With the growing emphasis on the role of pre-biopsy mpMRI in the evaluation of PCa, there is an increased demand for innovative MRI methods that can improve PCa grading, detect clinically significant PCa, and biopsy guidance. To meet these demands, in addition to routine T1-weighted, T2-weighted, DCE-MRI, diffusion MRI, and MR spectroscopy, several new MR methods such as restriction spectrum imaging, vascular, extracellular, and restricted diffusion for cytometry in tumors (VERDICT) method, hybrid multi-dimensional MRI, luminal water imaging, and MR fingerprinting have been developed for a better characterization of the disease. Further, with the increasing interest in combining MR data with clinical and genomic data, there is a growing interest in utilizing radiomics and radiogenomics approaches. These big data can also be utilized in the development of computer-aided diagnostic tools, including automatic segmentation and the detection of clinically significant PCa using machine learning methods.

Developments in proton MR spectroscopic imaging of prostate cancer

In this paper, we review the developments of 1H-MR spectroscopic imaging (MRSI) methods designed to investigate prostate cancer, covering key aspects such as specific hardware, dedicated pulse sequences for data acquisition and data processing and quantification techniques. Emphasis is given to recent advancements in MRSI methodologies, as well as future developments, which can lead to overcome difficulties associated with commonly employed MRSI approaches applied in clinical routine. This includes the replacement of standard PRESS sequences for volume selection, which we identified as inadequate for clinical applications, by sLASER sequences and implementation of 1H MRSI without water signal suppression. These may enable a new evaluation of the complementary role and significance of MRSI in prostate cancer management.

Ultra-high-field MR in Prostate cancer: Feasibility and Potential

Multiparametric MRI of the prostate at clinical magnetic field strengths (1.5/3 Tesla) has emerged as a reliable noninvasive imaging modality for identifying clinically significant cancer, enabling selective sampling of high-risk regions with MRI-targeted biopsies, and enabling minimally invasive focal treatment options. With increased sensitivity and spectral resolution, ultra-high-field (UHF) MRI (≥ 7 Tesla) holds the promise of imaging and spectroscopy of the prostate with unprecedented detail. However, exploiting the advantages of ultra-high magnetic field is challenging due to inhomogeneity of the radiofrequency field and high local specific absorption rates, raising local heating in the body as a safety concern. In this work, we review various coil designs and acquisition strategies to overcome these challenges and demonstrate the potential of UHF MRI in anatomical, functional and metabolic imaging of the prostate and pelvic lymph nodes. When difficulties with power deposition of many refocusing pulses are overcome and the full potential of metabolic spectroscopic imaging is used, UHF MR(S)I may aid in a better understanding of the development and progression of local prostate cancer. Together with large field-of-view and low-flip-angle anatomical 3D imaging, 7 T MRI can be used in its full strength to characterize different tumor stages and help explain the onset and spatial distribution of metastatic spread.

Three-dimensional nuclear magnetic resonance spectroscopy: a complementary tool to multiparametric magnetic resonance imaging in the identification of aggressive prostate cancer at 3.0T

Background

The limitations of the assessment of tumor aggressiveness by Prostate Imaging Reporting and Data System (PI-RADS) and biopsies suggest that the diagnostic algorithm could be improved by quantitative measurements in some chosen indications. We assessed the tumor high-risk predictive performance of 3.0 Tesla (3.0T) multiparametric magnetic resonance imaging (mp-MRI) combined with nuclear magnetic resonance spectroscopic sequences (NMR-S) in order to show that the metabolic analysis could bring out an evocative result for the aggressive form of prostate cancer.

Methods

We conducted a retrospective study of 26 patients (mean age, 62.4 years) who had surgery for prostate cancer between 2009 and 2016 after pre-therapeutic assessment with 3.0T mp-MRI and NMR-S. Groups within the intermediate range of the D'Amico risk classification were divided into two categories, low risk (n=20) and high risk (n=6), according to the International Society of Urological Pathology (ISUP) 2-3 limit. Histoprognostic discordances within various risk groups were compared with the corresponding predictive MRI values. The performance of predictive models was assessed based on sensitivity, specificity, and the area under the curve (AUC) of receiver operating characteristic (ROC) curves.

Results

After prostatectomy, histological analysis reclassified 18 patients as high-risk, including 16 who were T3 MRI grade, of whom 13 (81.3%) were found to be pT3. Among the patients who had cT1 or cT2 digital rectal examinations, the T3 MRI factor multiplied by 8.7 [odds ratio (OR), 8.7; 95% confidence interval (CI), 1.3-56.2; P=0.024] the relative risk of being pT3 and by 5.8 (OR, 5.8; 95% CI, 0.95-35.7; P=0.05) the relative risk of being pGleason (pGS) > GS-prostate biopsy. Spectroscopic data showed that the choline concentration was significantly higher (P=0.001) in aggressive disease.

Conclusions

The predictive model of tumor aggressiveness combining mp-MRI plus NMR-S was better than the mp-MRI model alone (AUC, 0.95 vs. 0.86). Information obtained by mp-MRI coupled with spectroscopy may improve the detection of occult aggressive disease, helping in the discrimination of intermediate risks.

Diagnosis of transition zone prostate cancer by multiparametric MRI: added value of MR spectroscopic imaging with sLASER volume selection

Background

Current multiparametric MRI (mp-MRI) in routine clinical practice has poor-to-moderate diagnostic performance for transition zone prostate cancer. The aim of this study was to evaluate the potential diagnostic performance of novel ¹H magnetic resonance spectroscopic imaging (MRSI) using a semi-localized adiabatic selective refocusing (sLASER) sequence with gradient offset independent adiabaticity (GOIA) pulses in addition to the routine mp-MRI, including T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI) and quantitative dynamic contrast enhancement (DCE) for transition zone prostate cancer detection, localization and grading.

Methods

Forty-one transition zone prostate cancer patients underwent mp-MRI with an external phased-array coil. Normal and cancer regions were delineated by two radiologists and divided into low-risk, intermediate-risk, and high-risk categories based on TRUS guided biopsy results. Support vector machine models were built using different clinically applicable combinations of T2WI, DWI, DCE, and MRSI. The diagnostic performance of each model in cancer detection was evaluated using the area under curve (AUC) of the receiver operating characteristic diagram. Then accuracy, sensitivity and specificity of each model were calculated. Furthermore, the correlation of mp-MRI parameters with low-risk, intermediate-risk and high-risk cancers were calculated using the Spearman correlation coefficient.

Results

The addition of MRSI to T2WI + DWI and T2WI + DWI + DCE improved the accuracy, sensitivity and specificity for cancer detection. The best performance was achieved with T2WI + DWI + MRSI where the addition of MRSI improved the AUC, accuracy, sensitivity and specificity from 0.86 to 0.99, 0.83 to 0.96, 0.80 to 0.95, and 0.85 to 0.97 respectively. The (choline + spermine + creatine)/citrate ratio of MRSI showed the highest correlation with cancer risk groups (r = 0.64, p < 0.01).

Conclusion

The inclusion of GOIA-sLASER MRSI into conventional mp-MRI significantly improves the diagnostic accuracy of the detection and aggressiveness assessment of transition zone prostate cancer.

ECLIPSE utilizing gradient-modulated offset-independent adiabaticity (GOIA) pulses for highly selective human brain proton MRSI

A multitude of extracranial lipid suppression methods exist for proton MRSI acquisitions. Popular and emerging lipid suppression methods each have their inherent set of advantages and disadvantages related to the achievable level of lipid suppression, RF power deposition, insensitivity to B₁⁺ field and lipid T₁ heterogeneity, brain coverage, spatial selectivity, chemical shift displacement (CSD) errors and the reliability of spectroscopic data spanning the observed 0.9-4.7 ppm band. The utility of elliptical localization with pulsed second order fields (ECLIPSE) was previously demonstrated with a greater than 100-fold in extracranial lipid suppression and low power requirements utilizing 3 kHz bandwidth AFP pulses. Like all gradient-based localization methods, ECLIPSE is sensitive to CSD errors, resulting in a modified metabolic profile in edge-of-ROI voxels. In this work, ECLIPSE is extended with 15 kHz bandwidth second order gradient-modulated RF pulses based on the gradient offset-independent adiabaticity (GOIA) algorithm to greatly reduce CSD and improve spatial selectivity. An adiabatic double spin-echo ECLIPSE inner volume selection (TE = 45 ms) MRSI method and an ECLIPSE outer volume suppression (TE = 3.2 ms) FID-MRSI method were implemented. Both GOIA-ECLIPSE MRSI sequences provided artifact-free metabolite spectra in vivo, with a greater than 100-fold in lipid suppression and less than 2.6 mm in-plane CSD and less than 3.3 mm transition width for edge-of-ROI voxels, representing an ~5-fold improvement compared with the parent, nongradient-modulated method. Despite the 5-fold larger bandwidth, GOIA-ECLIPSE only required a 1.9-fold increase in RF power. The highly robust lipid suppression combined with low CSD and sharp ROI edge transitions make GOIA-ECLIPSE an attractive alternative to commonly employed lipid suppression methods. Furthermore, the low RF power deposition demonstrates that GOIA-ECLIPSE is very well suited for high field (≥3 T) MRSI applications.

Nuclear magnetic resonance spectroscopy of human body fluids and in vivo magnetic resonance spectroscopy: Potential role in the diagnosis and management of prostate cancer

Prostate cancer is the most common solid organ cancer in men, and the second most common cause of male cancer-related mortality. It has few effective therapies, and is difficult to diagnose accurately. Prostate-specific antigen (PSA), which is currently the most effective diagnostic tool available, cannot reliably discriminate between different pathologies, and in fact only around 30% of patients found to have elevated levels of PSA are subsequently confirmed to actually have prostate cancer. As such, there is a desperate need for more reliable diagnostic tools that will allow the early detection of prostate cancer so that the appropriate interventions can be applied. Nuclear magnetic resonance (NMR) spectroscopy and magnetic resonance spectroscopy (MRS) are 2 high throughput, noninvasive analytical procedures that have the potential to enable differentiation of prostate cancer from other pathologies using metabolomics, by focusing specifically on certain metabolites which are associated with the development of prostate cancer cells and its progression. The value that this type of approach has for the early detection, diagnosis, prognosis, and personalized treatment of prostate cancer is becoming increasingly apparent. Recent years have seen many promising developments in the fields of NMR spectroscopy and MRS, with improvements having been made to hardware as well as to techniques associated with the acquisition, processing, and analysis of related data. This review focuses firstly on proton NMR spectroscopy of blood serum, urine, and expressed prostatic secretions in vitro, and then on 1- and 2-dimensional proton MRS of the prostate in vivo. Major advances in these fields and methodological principles of data collection, acquisition, processing, and analysis are described along with some discussion of related challenges, before prospects that proton MRS has for future improvements to the clinical management of prostate cancer are considered.

Advanced single voxel 1 H magnetic resonance spectroscopy techniques in humans: Experts' consensus recommendations

Conventional proton MRS has been successfully utilized to noninvasively assess tissue biochemistry in conditions that result in large changes in metabolite levels. For more challenging applications, namely, in conditions which result in subtle metabolite changes, the limitations of vendor-provided MRS protocols are increasingly recognized, especially when used at high fields (≥3 T) where chemical shift displacement errors, B0 and B1 inhomogeneities and limitations in the transmit B1 field become prominent. To overcome the limitations of conventional MRS protocols at 3 and 7 T, the use of advanced MRS methodology, including pulse sequences and adjustment procedures, is recommended. Specifically, the semiadiabatic LASER sequence is recommended when TE values of 25-30 ms are acceptable, and the semiadiabatic SPECIAL sequence is suggested as an alternative when shorter TE values are critical. The magnetic field B0 homogeneity should be optimized and RF pulses should be calibrated for each voxel. Unsuppressed water signal should be acquired for eddy current correction and preferably also for metabolite quantification. Metabolite and water data should be saved in single shots to facilitate phase and frequency alignment and to exclude motion-corrupted shots. Final averaged spectra should be evaluated for SNR, linewidth, water suppression efficiency and the presence of unwanted coherences. Spectra that do not fit predefined quality criteria should be excluded from further analysis. Commercially available tools to acquire all data in consistent anatomical locations are recommended for voxel prescriptions, in particular in longitudinal studies. To enable the larger MRS community to take advantage of these advanced methods, a list of resources for these advanced protocols on the major clinical platforms is provided. Finally, a set of recommendations are provided for vendors to enable development of advanced MRS on standard platforms, including implementation of advanced localization sequences, tools for quality assurance on the scanner, and tools for prospective volume tracking and dynamic linear shim corrections.

Lost in translation: lessons learned from the "demise" of MRSI of the prostate

At times, technologies fail for reasons other than an inability to deliver on their promises. The iconic Blackberry, for example, was once coined "Research in Motion", sold tens of millions of units, and then "disappeared" from the market because it did not accompany the new trends in design. Promising technologies may also "disappear" in the medical field. What follows is the tale of the rise and fall of proton magnetic resonance spectroscopic imaging (¹H MRSI) of the prostate.

Methodological consensus on clinical proton MRS of the brain: Review and recommendations

Proton MRS (1 H MRS) provides noninvasive, quantitative metabolite profiles of tissue and has been shown to aid the clinical management of several brain diseases. Although most modern clinical MR scanners support MRS capabilities, routine use is largely restricted to specialized centers with good access to MR research support. Widespread adoption has been slow for several reasons, and technical challenges toward obtaining reliable good-quality results have been identified as a contributing factor. Considerable progress has been made by the research community to address many of these challenges, and in this paper a consensus is presented on deficiencies in widely available MRS methodology and validated improvements that are currently in routine use at several clinical research institutions. In particular, the localization error for the PRESS localization sequence was found to be unacceptably high at 3 T, and use of the semi-adiabatic localization by adiabatic selective refocusing sequence is a recommended solution. Incorporation of simulated metabolite basis sets into analysis routines is recommended for reliably capturing the full spectral detail available from short TE acquisitions. In addition, the importance of achieving a highly homogenous static magnetic field (B0 ) in the acquisition region is emphasized, and the limitations of current methods and hardware are discussed. Most recommendations require only software improvements, greatly enhancing the capabilities of clinical MRS on existing hardware. Implementation of these recommendations should strengthen current clinical applications and advance progress toward developing and validating new MRS biomarkers for clinical use.

Supervised risk predictor of central gland lesions in prostate cancer using 1 H MR spectroscopic imaging with gradient offset-independent adiabaticity pulses

BACKGROUND

Due to the histological heterogeneity of the central gland, accurate detection of central gland prostate cancer remains a challenge.

PURPOSE

To evaluate the efficacy of in vivo 3D ¹ H MR spectroscopic imaging (3D ¹ H MRSI) with a semi-localized adiabatic selective refocusing (sLASER) sequence and gradient-modulated offset-independent adiabatic (GOIA) pulses for detection of central gland prostate cancer. Additionally four risk models were developed to differentiate 1) normal vs. cancer, 2) low- vs. high-risk cancer, 3) low- vs. intermediate-risk cancer, and 4) intermediate- vs. high-risk cancer voxels.

STUDY TYPE

Prospective.

SUBJECTS

Thirty-six patients with biopsy-proven central gland prostate cancer.

FIELD STRENGTH/SEQUENCE

3T MRI / 3D ¹ H MRSI using GOIA-sLASER.

ASSESSMENT

Cancer and normal regions of interest (ROIs) were selected by an experienced radiologist and ¹ H MRSI voxels were placed within the ROIs to calculate seven metabolite signal ratios. Voxels were split into two subsets, 80% for model training and 20% for testing.

STATISTICAL TESTS

Four support vector machine (SVM) models were built using the training dataset. The accuracy, sensitivity, and specificity for each model were calculated for the testing dataset.

RESULTS

High-quality MR spectra were obtained for the whole central gland of the prostate. The normal vs. cancer diagnostic model achieved the highest predictive performance with an accuracy, sensitivity, and specificity of 96.2%, 95.8%, and 93.1%, respectively. The accuracy, sensitivity, and specificity of the low- vs. high-risk cancer and low- vs. intermediate-risk cancer models were 82.5%, 89.2%, 70.2%, and 73.0%, 84.7%, 60.8%, respectively. The intermediate- vs. high-risk cancer model yielded an accuracy, sensitivity, and specificity lower than 55%.

DATA CONCLUSION

The GOIA-sLASER sequence with an external phased-array coil allows for fast assessment of central gland prostate cancer. The classification offers a promising diagnostic tool for discriminating normal vs. cancer, low- vs. high-risk cancer, and low- vs. intermediate-risk cancer.

LEVEL OF EVIDENCE

2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;50:1926-1936.

Levels of choline-containing compounds in normal liver and liver metastases of colorectal cancer as recorded by 1 H MRS

PURPOSE

A relatively high signal for choline-containing compounds (total choline, tCho) is commonly found in ¹ H MR spectra of malignant tumors, but it is unclear if this also occurs in tumors in the liver. We evaluated the potential of the tCho signal in single voxel ¹ H MR spectra of the human liver to assess metastases of colorectal cancers.

EXPERIMENT

MR spectra of an 8 cm³ PRESS-localized voxel were obtained at 3 T from the livers of 12 healthy volunteers and from metastatic lesions in 20 patients in two different sessions. To correct for motion artifacts, sequentially recorded spectra were individually phased and frequency aligned before averaging. Spectra were analyzed using LCModel and tissue levels estimated by water referencing. Repeatability was assessed with Bland-Altman analyses. To estimate tumor necrosis, diffusion-weighted imaging of the liver was performed. High resolution magic angle spinning (HRMAS) spectra of tumor and normal liver samples were obtained at 11.7 T.

RESULTS

With increasing tumor volumes, tCho levels decreased, indicating a partial volume effect. Mean tCho content in tumors larger than the PRESS voxel (>8 cm³ ) was significantly lower (p < 0.01) than for normal liver: 1.6 (range 0.0-3.4) versus 6.9 (range 4.9-11.1) mmol/kg wet weight, while it was comparable for tumors smaller than 8 cm³ : 7.0 (range 3.8-9.3) mmol/kg. The higher 90th percentile apparent diffusion coefficient value in the larger lesions indicates more necrosis. Measurement repeatability was average in normal livers and poor in tumors. HRMAS did not show substantial differences in choline-containing compounds between normal liver and metastasis.

CONCLUSION

An increased tCho content was not observed in ¹ H MR spectra of liver metastasis of colorectal cancer, compared with normal liver. This may be due to the background of a high tCho signal in spectra of normal liver or to an intrinsic lower tCho content in these tumors, but is most likely the result of necrosis in metastatic tumor tissue.

Simple and broadly applicable automatic quality control for 3D 1 H MR spectroscopic imaging data of the prostate

PURPOSE

Quality control (QC) is a prerequisite for clinical MR spectroscopic imaging (MRSI) to avoid that bad spectra hamper data interpretation. The aim of this work was to present a simple automatic QC for prostate ¹ H MRSI that can handle data obtained with different commonly used pulse sequences, echo times, field strengths, and MR platforms.

METHODS

A QC method was developed with a ratio (Qratio) where the numerator and the denominator are functions of several signal heights, logically combined for their positive or negative contribution to spectral quality. This Qratio was tested on 4 data sets obtained at 1.5, 3, and 7T, with and without endorectal coil and different localization sequences and echo times. Spectra of 25,248 voxels in 26 prostates were labeled as acceptable or unacceptable by MRS experts as gold standard. A threshold value was determined for Qratio from a subset of voxels, labeled in consensus by 4 experts, for an optimal accuracy to separate spectra.

RESULTS

Applying this Qratio threshold to the remaining test voxels, an automatic separation of good and bad spectra was possible with an accuracy of 0.88, similar to manual separation between the 2 classes. Qratio values were used to generate maps representing spectral quality on a binary or continuous scale.

CONCLUSION

Automated QC of prostate ¹ H MRSI by Qratio is fast, simple, easily transferable and more practical than supervised feature extraction methods and therefore easy to integrate into different clinical MR systems. Moreover, quality maps can be generated to read the reliability of spectra in each voxel.

Simultaneous 18F-fluciclovine Positron Emission Tomography and Magnetic Resonance Spectroscopic Imaging of Prostate Cancer

Purpose: To investigate the associations of metabolite levels derived from magnetic resonance spectroscopic imaging (MRSI) and ¹⁸F-fluciclovine positron emission tomography (PET) with prostate tissue characteristics.

Methods: In a cohort of 19 high-risk prostate cancer patients that underwent simultaneous PET/MRI, we evaluated the diagnostic performance of MRSI and PET for discrimination of aggressive cancer lesions from healthy tissue and benign lesions. Data analysis comprised calculations of correlations of mean standardized uptake values (SUV_mean), maximum SUV (SUV_max), and the MRSI-derived ratio of (total choline + spermine + creatine) to citrate (CSC/C). Whole-mount histopathology was used as gold standard.

Results: The results showed a moderate significant correlation between both SUVmean and SUVmax with CSC/C ratio.

Conclusions: We demonstrated that the simultaneous acquisition of ¹⁸F-fluciclovine PET and MRSI with an integrated PET/MRI system is feasible and a combination of these imaging modalities has potential to improve the diagnostic sensitivity and specificity of prostate cancer lesions.

High-Quality 3-Dimensional 1H Magnetic Resonance Spectroscopic Imaging of the Prostate Without Endorectal Receive Coil Using A Semi-LASER Sequence

OBJECTIVES

Inclusion of 3-dimensional H magnetic resonance spectroscopic imaging (3D-H-MRSI) in routine multiparametric MRI of the prostate requires good quality spectra and easy interpretable metabolite maps of the whole organ obtained without endorectal coil in clinically feasible acquisition times. We evaluated if a semi-LASER pulse sequence with gradient offset independent adiabaticity refocusing pulses (GOIA-sLASER) for volume selection can meet these requirements.

MATERIALS AND METHODS

Thirteen patients with suspicion of prostate cancer and 1 patient known to have prostate cancer were examined at 3 T with a multichannel body-receive coil. A 3D-H-MRSI sequence with GOIA-sLASER volume selection (echo time, 88 milliseconds) was added to a routine clinical multiparametric MRI examination of these patients. Repetition times from 630 to 1000 milliseconds and effective voxel sizes of approximately 0.9 and 0.6 cm were tested. Spectral components were quantified by LCModel software for quality assessment and to construct choline and citrate maps.

RESULTS

Three-dimensional MRSI of the prostate was successfully performed in all patients in measurement times of 5 to 10 minutes. Analysis of the multiparametric MRI examination or of biopsies did not reveal malignant tissue in the prostate of the 13 patients. In 1404 evaluated voxels acquired from 13 patients, the citrate resonance could be fitted with a high reliability (Cramér-Rao lower bound <30%), 100% for 7 × 7 × 7-mm voxels and 96 ± 7 in 6 × 6 × 6-mm voxels. The percentage of 7 × 7 × 7-mm voxels in which the choline signal was fitted with Cramér-Rao lower bound of less than 30% was approximately 50% at a TR of 630 milliseconds and increased to more than 80% for TRs of 800 milliseconds and above. In the patient with prostate cancer, choline was detectable throughout the prostate in spectra recorded at a TR of 700 milliseconds. The homogeneous B1 field over the prostate of the receive coil enabled the generation of whole organ metabolite maps, revealing choline and citrate variations between areas with normal prostate tissue, seminal vesicles, proliferative benign prostatic hyperplasia, and tumor.

CONCLUSIONS

The good signal-to-noise ratio and low chemical shift artifacts of GOIA-sLASER at an echo time of 88 milliseconds enable acquisition of high-quality 3D-H-MRSI of the prostate without endorectal coil in less than 10 minutes. This facilitates reconstruction of easy interpretable, quantitative metabolite maps for routine clinical applications of prostate MRSI.

Ex vivo metabolic fingerprinting identifies biomarkers predictive of prostate cancer recurrence following radical prostatectomy

Background:

Robust biomarkers that identify prostate cancer patients with high risk of recurrence will improve personalised cancer care. In this study, we investigated whether tissue metabolites detectable by high-resolution magic angle spinning magnetic resonance spectroscopy (HR-MAS MRS) were associated with recurrence following radical prostatectomy.

Methods:

We performed a retrospective ex vivo study using HR-MAS MRS on tissue samples from 110 radical prostatectomy specimens obtained from three different Norwegian cohorts collected between 2002 and 2010. At the time of analysis, 50 patients had experienced prostate cancer recurrence. Associations between metabolites, clinicopathological variables, and recurrence-free survival were evaluated using Cox proportional hazards regression modelling, Kaplan–Meier survival analyses and concordance index (C-index).

Results:

High intratumoural spermine and citrate concentrations were associated with longer recurrence-free survival, whereas high (total-choline+creatine)/spermine (tChoCre/Spm) and higher (total-choline+creatine)/citrate (tChoCre/Cit) ratios were associated with shorter time to recurrence. Spermine concentration and tChoCre/Spm were independently associated with recurrence in multivariate Cox proportional hazards modelling after adjusting for clinically relevant risk factors (C-index: 0.769; HR: 0.72; P=0.016 and C-index: 0.765; HR: 1.43; P=0.014, respectively).

Conclusions:

Spermine concentration and tChoCre/Spm ratio in prostatectomy specimens were independent prognostic markers of recurrence. These metabolites can be noninvasively measured in vivo and may thus offer predictive value to establish preoperative risk assessment nomograms.

Metabolic Imaging in Prostate Cancer: Where We Are

In recent years, the development of diagnostic methods based on metabolic imaging has been aimed at improving diagnosis of prostate cancer (PCa) and perhaps at improving therapy. Molecular imaging methods can detect specific biological processes that are different when detected within cancer cells relative to those taking place in surrounding normal tissues. Many methods are sensitive to tissue metabolism; among them, positron emission tomography (PET) and magnetic resonance spectroscopic imaging (MRSI) are widely used in clinical practice and clinical research. There is a rich literature that establishes the role of these metabolic imaging techniques as valid tools for the diagnosis, staging, and monitoring of PCa. Until recently, European guidelines for PCa detection still considered both MRSI/MRI and PET/CT to be under evaluation, even though they had demonstrated their value in the staging of high risk PCa, and in the restaging of patients presenting elevated prostatic-specific antigen levels following radical treatment of PCa, respectively. Very recently, advanced methods for metabolic imaging have been proposed in the literature: multiparametric MRI (mpMRI), hyperpolarized MRSI, PET/CT with the use of new tracers and finally PET/MRI. Their detection capabilities are currently under evaluation, as is the feasibility of using such techniques in clinical studies.

Flexible proton 3D MR spectroscopic imaging of the prostate with low-power adiabatic pulses for volume selection and spiral readout

PURPOSE

Cartesian k-space sampling in three-dimensional magnetic resonance spectroscopic imaging (MRSI) of the prostate limits the selection of voxel size and acquisition time. Therefore, large prostates are often scanned at reduced spatial resolutions to stay within clinically acceptable measurement times. Here we present a semilocalized adiabatic selective refocusing (sLASER) sequence with gradient-modulated offset-independent adiabatic (GOIA) refocusing pulses and spiral k-space acquisition (GOIA-sLASER-Spiral) for fast prostate MRSI with enhanced resolution and extended matrix sizes.

METHODS

MR was performed at 3 tesla with an endorectal receive coil. GOIA-sLASER-Spiral at an echo time (TE) of 90 ms was compared to a point-resolved spectroscopy sequence (PRESS) with weighted, elliptical phase encoding at an TE of 145 ms using simulations and measurements of phantoms and patients (n = 9).

RESULTS

GOIA-sLASER-Spiral acquisition allows prostate MR spectra to be obtained in ∼5 min with a quality comparable to those acquired with a common Cartesian PRESS protocol in ∼9 min, or at an enhanced spatial resolution showing more precise tissue allocation of metabolites. Extended field of views (FOVs) and matrix sizes for large prostates are possible without compromising spatial resolution or measurement time.

CONCLUSION

The flexibility of spiral sampling enables prostate MRSI with a wide range of resolutions and FOVs without undesirable increases in acquisition times, as in Cartesian encoding. This approach is suitable for routine clinical exams of prostate metabolites. Magn Reson Med 77:928-935, 2017. © 2016 International Society for Magnetic Resonance in Medicine.