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Bucher AM, Egger J, Dietz J, Strecker R, Hilbert T, Frodl E, Wenzel M, Penzkofer T, Hamm B, Chun FK, Vogl T, Kleesiek J, Beeres M. Value of MRI - T2 Mapping to Differentiate Clinically Significant Prostate Cancer. JOURNAL OF IMAGING INFORMATICS IN MEDICINE 2024:10.1007/s10278-024-01150-6. [PMID: 38926263 DOI: 10.1007/s10278-024-01150-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/16/2023] [Revised: 05/21/2024] [Accepted: 05/23/2024] [Indexed: 06/28/2024]
Abstract
Standardized reporting of multiparametric prostate MRI (mpMRI) is widespread and follows international standards (Pi-RADS). However, quantitative measurements from mpMRI are not widely comparable. Although T2 mapping sequences can provide repeatable quantitative image measurements and extract reliable imaging biomarkers from mpMRI, they are often time-consuming. We therefore investigated the value of quantitative measurements on a highly accelerated T2 mapping sequence, in order to establish a threshold to differentiate benign from malignant lesions. For this purpose, we evaluated a novel, highly accelerated T2 mapping research sequence that enables high-resolution image acquisition with short acquisition times in everyday clinical practice. In this retrospective single-center study, we included 54 patients with clinically indicated MRI of the prostate and biopsy-confirmed carcinoma (n = 37) or exclusion of carcinoma (n = 17). All patients had received a standard of care biopsy of the prostate, results of which were used to confirm or exclude presence of malignant lesions. We used the linear mixed-effects model-fit by REML to determine the difference between mean values of cancerous tissue and healthy tissue. We found good differentiation between malignant lesions and normal appearing tissue in the peripheral zone based on the mean T2 value. Specifically, the mean T2 value for tissue without malignant lesions was (151.7 ms [95% CI: 146.9-156.5 ms] compared to 80.9 ms for malignant lesions [95% CI: 67.9-79.1 ms]; p < 0.001). Based on this assessment, a limit of 109.2 ms is suggested. Aditionally, a significant correlation was observed between T2 values of the peripheral zone and PI-RADS scores (p = 0.0194). However, no correlation was found between the Gleason Score and the T2 relaxation time. Using REML, we found a difference of -82.7 ms in mean values between cancerous tissue and healthy tissue. We established a cut-off-value of 109.2 ms to accurately differentiate between malignant and non-malignant prostate regions. The addition of T2 mapping sequences to routine imaging could benefit automated lesion detection and facilitate contrast-free multiparametric MRI of the prostate.
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Affiliation(s)
- Andreas Michael Bucher
- Institute for Diagnostic and Interventional Radiology, Goethe University Frankfurt, University Hospital Frankfurt, Theodor-Stern Kai 7, 60590, Frankfurt, Germany
| | - Jan Egger
- Institute for AI in Medicine, University Hospital Essen, Girardetstraße 2, 45131, Essen, Germany.
| | - Julia Dietz
- Institute for Diagnostic and Interventional Radiology, Goethe University Frankfurt, University Hospital Frankfurt, Theodor-Stern Kai 7, 60590, Frankfurt, Germany
| | - Ralph Strecker
- Siemens Healthineers AG, (EMEA Scientific Partnerships), Henkestraße 127, 91052, Erlangen, Germany
| | - Tom Hilbert
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, EPFL, QI E, 1015, Lausanne, Lausanne, Switzerland
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Eric Frodl
- Institute for Diagnostic and Interventional Radiology, Goethe University Frankfurt, University Hospital Frankfurt, Theodor-Stern Kai 7, 60590, Frankfurt, Germany
| | - Mike Wenzel
- Department of Urology, Goethe University Hospital, Goethe University Frankfurt, Frankfurt, Germany, Theodor-Stern Kai 7, 60590, Frankfurt, Germany
| | - Tobias Penzkofer
- Department of Radiology, Charité - Universitätsmedizin Berlin, Charitéplatz 1, 10117, Berlin, Germany
- Berlin Institute of Health, Berlin, Germany
| | - Bernd Hamm
- Department of Radiology, Charité - Universitätsmedizin Berlin, Charitéplatz 1, 10117, Berlin, Germany
| | - Felix Kh Chun
- Department of Urology, Goethe University Hospital, Goethe University Frankfurt, Frankfurt, Germany, Theodor-Stern Kai 7, 60590, Frankfurt, Germany
| | - Thomas Vogl
- Institute for Diagnostic and Interventional Radiology, Goethe University Frankfurt, University Hospital Frankfurt, Theodor-Stern Kai 7, 60590, Frankfurt, Germany
| | - Jens Kleesiek
- Institute for AI in Medicine, University Hospital Essen, Girardetstraße 2, 45131, Essen, Germany
- Department of Physics, TU Dortmund University, Otto-Hahn-Straße 4, 44227, Dortmund, Germany
- Cancer Research Center Cologne Essen (CCCE), West German Cancer Center Essen (WTZ), 45122, Essen, Germany
- German Cancer Research Center (DKFZ), Partner site University Hospital Essen, German Cancer Consortium (DKTK), 45122, Essen, Germany
- Medical Faculty, University of Duisburg-Essen, 45122, Essen, Germany
| | - Martin Beeres
- Institute for Diagnostic and Interventional Radiology, Goethe University Frankfurt, University Hospital Frankfurt, Theodor-Stern Kai 7, 60590, Frankfurt, Germany
- Departement of Neuroradiology, University-Hospital of Giessen and Marburg Campus Marburg, Baldingerstraße 1, 35043, Marburg, Germany
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Coronado R, Castillo-Passi C, Besa C, Irarrazaval P. Fast and accessible T2 mapping using off-resonance corrected DESPOT2 with application to 3D prostate. Magn Reson Imaging 2024; 109:227-237. [PMID: 38508291 DOI: 10.1016/j.mri.2024.03.018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2024] [Revised: 03/12/2024] [Accepted: 03/13/2024] [Indexed: 03/22/2024]
Abstract
PURPOSE Most T1 and T2 mapping take long acquisitions or needs specialized sequences not widely accessible on clinical scanners. An available solution is DESPOT1/T2 (Driven equilibrium single pulse observation of T1/T2). DESPOT1/T2 uses Spoiled gradient-echo (SPGR) and balanced Steady-State Free Precession (bSSFP) sequences, offering an accessible and reliable way for 3D accelerated T1/T2 mapping. However, bSSFP is prone to off-resonance artifacts, limiting the application of DESPOT2 in regions with high susceptibility contrasts, like the prostate. Our proposal, DESPO+, employs the full bSSFP and SPGR models with a dictionary-based method to reconstruct 3D T1/T2 maps in the prostate region without off-resonance banding. METHODS DESPO+ modifies the bSSFP acquisition of the original variable flip angle DESPOT2. DESPO+ uses variable repetition and echo times, employing a dictionary-based method of the full bSSFP and SPGR models to reconstruct T1, T2, and Proton Density (PD) simultaneously. The proposed DESPO+ method underwent testing through simulations, T1/T2 phantoms, and on fourteen healthy subjects. RESULTS The results reveal a significant reduction in T2 map banding artifacts compared to the original DESPOT2 method. DESPO+ approach reduced T2 errors by up to seven times compared to DESPOT2 in simulations and phantom experiments. We also synthesized in-vivo T1-weighted/T2-weighted images from the acquired maps using a spin-echo model to verify the map's quality when lacking a reference. For in-vivo imaging, the synthesized images closely resemble those from the clinical MRI protocol, reducing scan time by around 50% compared to traditional spin-echo T1-weighted/T2-weighted acquisitions. CONCLUSION DESPO+ provides an off-resonance insensitive and clinically available solution, enabling high-resolution 3D T1/T2 mapping and synthesized T1-weighted/T2-weighted images for the entire prostate, all achieved within a short scan time of 3.6 min, similar to DESPOT1/T2.
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Affiliation(s)
- Ronal Coronado
- Biomedical Imaging Center, Pontificia Universidad Católica de Chile, Santiago, Chile; Department of Electrical Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile; Millennium Institute for Intelligent Healthcare Engineering, Santiago, Chile
| | - Carlos Castillo-Passi
- Millennium Institute for Intelligent Healthcare Engineering, Santiago, Chile; School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom; Institute for Biological and Medical Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Cecilia Besa
- Millennium Institute for Intelligent Healthcare Engineering, Santiago, Chile; Department of Radiology, School of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Pablo Irarrazaval
- Biomedical Imaging Center, Pontificia Universidad Católica de Chile, Santiago, Chile; Department of Electrical Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile; Millennium Institute for Intelligent Healthcare Engineering, Santiago, Chile; Institute for Biological and Medical Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile.
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Gaur S, Panda A, Fajardo JE, Hamilton J, Jiang Y, Gulani V. Magnetic Resonance Fingerprinting: A Review of Clinical Applications. Invest Radiol 2023; 58:561-577. [PMID: 37026802 PMCID: PMC10330487 DOI: 10.1097/rli.0000000000000975] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/08/2023]
Abstract
ABSTRACT Magnetic resonance fingerprinting (MRF) is an approach to quantitative magnetic resonance imaging that allows for efficient simultaneous measurements of multiple tissue properties, which are then used to create accurate and reproducible quantitative maps of these properties. As the technique has gained popularity, the extent of preclinical and clinical applications has vastly increased. The goal of this review is to provide an overview of currently investigated preclinical and clinical applications of MRF, as well as future directions. Topics covered include MRF in neuroimaging, neurovascular, prostate, liver, kidney, breast, abdominal quantitative imaging, cardiac, and musculoskeletal applications.
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Affiliation(s)
- Sonia Gaur
- Department of Radiology, Michigan Medicine, Ann Arbor, MI
| | - Ananya Panda
- All India Institute of Medical Sciences, Jodhpur, Rajasthan, India
| | | | - Jesse Hamilton
- Department of Radiology, Michigan Medicine, Ann Arbor, MI
| | - Yun Jiang
- Department of Radiology, Michigan Medicine, Ann Arbor, MI
| | - Vikas Gulani
- Department of Radiology, Michigan Medicine, Ann Arbor, MI
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Cao H, Xu W, Xu Y, Rong X, Xiao X, Feng H, Wang X, Wang L, Qi T, Zhang L. Value of synthetic MRI quantitative parameters in preprocedural evaluation for TRUS/MRI fusion-guided biopsy of the prostate. Prostate 2023. [PMID: 37157155 DOI: 10.1002/pros.24550] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/21/2022] [Revised: 03/17/2023] [Accepted: 04/24/2023] [Indexed: 05/10/2023]
Abstract
BACKGROUND Transrectal ultrasonography (TRUS)/magnetic resonance imaging (MRI) fusion-guided biopsy has a high clinical application value. However, this technique has some limitations, which limit its use in routine clinical practice. Therefore, the selection of suitable proatate lesions for this technique is worthy of our attention. Synthetic MRI (SyMRI) is capable of quantifying multiple relaxation parameters, which might have potential value in preprocedural evaluation for TRUS/MRI fusion-guided biopsy of the prostate. The aim of our study is to examine the value of SyMRI quantitative parameters in preprocedural evaluation for TRUS/MRI fusion-guided biopsy of the prostate. METHODS We prospectively selected 148 lesions in 137 patients who underwent prostate biopsy in our hospital. Next, 2-4 needles of TRUS/MRI fusion-guided biopsy combined with 10 needles of system biopsy (SB) were used as the protocol for prostate biopsy. Before biopsy, the MAGiC sequences of the MRI images of the enrolled patients underwent post-processing, and the longitudinal relaxation time (T1), transverse relaxation time (T2), and proton density (PD) were extracted. The biopsy pathology results were used as a gold standard to compare the differences in SyMRI quantitative parameters between benign and malignant prostate lesions in the peripheral and transitional zones. The receiver operating characteristic (ROC) curves were plotted to confirm the optimal SyMRI quantitative parameter for prostate lesion benignancy/malignancy performance, and the cutoff values of these parameters were used for grouping the lesions. The single-needle biopsy prostate cancer (PCa)-positivity rates (number of positive biopsy needles/total biopsy needles) and PCa overall detection rates by TRUS/MRI fusion-guided biopsy and SB were compared in different subgroups. RESULTS The T1 and T2 values can determine the benignancy/malignancy of prostate transition lesions(p < 0.01), and the T2 value has a greater diagnostic performance (p = 0.0376). The T2 value can determine the benignancy/malignancy of prostate peripheral lesions. The optimal diagnostic cutoff values for T2 were 77 and 81 ms, respectively. The single-needle PCa positivity rate of TRUS/MRI fusion-guided biopsy was higher than SB for any prostate lesions in different subgroups (p < 0.01). However, only in the subgroup of transition zone lesions with T2 ≤ 77 ms, the PCa overall detection rate of TRUS/MRI fusion-guided biopsy was significantly higher than that of SB (p = 0.031). CONCLUSION SyMRI-T2 value can provide a theoretical basis for the selection of suitable lesions for TRUS/MRI fusion-guided biopsy.
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Affiliation(s)
- Haiyan Cao
- Department of Ultrasound, Affiliated Hospital of Yangzhou University, Medical Imaging Center, Yangzhou University, Yangzhou, China
- Department of Ultrasound, Yancheng First Hospital, Affiliated Hospital of Nanjing University Medical school (The First people's Hospital of Yancheng), Yancheng, China
| | - Wenjuan Xu
- Department of Radiology, Affiliated Hospital of Yangzhou University, Medical Imaging Center, Yangzhou University, Yangzhou, China
| | - Yan Xu
- Department of Ultrasound, Affiliated Hospital of Yangzhou University, Medical Imaging Center, Yangzhou University, Yangzhou, China
| | - Xin Rong
- Department of Ultrasound, Affiliated Hospital of Yangzhou University, Medical Imaging Center, Yangzhou University, Yangzhou, China
| | - Xiao Xiao
- Department of Ultrasound, Affiliated Hospital of Yangzhou University, Medical Imaging Center, Yangzhou University, Yangzhou, China
| | - Hao Feng
- Department of Ultrasound, Affiliated Hospital of Yangzhou University, Medical Imaging Center, Yangzhou University, Yangzhou, China
| | - Xiaoxiang Wang
- Department of Urology, Affiliated Hospital of Yangzhou University, Yangzhou University, Yangzhou, China
| | - Lei Wang
- Department of Pathology, Affiliated Hospital of Yangzhou University, Yangzhou University, Yangzhou, China
| | - Tingyue Qi
- Department of Ultrasound, Affiliated Hospital of Yangzhou University, Medical Imaging Center, Yangzhou University, Yangzhou, China
| | - Li Zhang
- Department of Interventional Radiology, Affiliated Hospital of Yangzhou University, Medical Imaging Center, Yangzhou University, Yangzhou, China
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Daniel G, Meirav G, Noam O, Tamar BK, Dvir R, Ricardo O, Noam BE. Fast and accurate T 2 mapping using Bloch simulations and low-rank plus sparse matrix decomposition. Magn Reson Imaging 2023; 98:66-75. [PMID: 36649808 DOI: 10.1016/j.mri.2023.01.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2022] [Accepted: 01/08/2023] [Indexed: 01/15/2023]
Abstract
PURPOSE MRI's T2 relaxation time is one of the key contrast mechanisms for clinical diagnosis and prognosis of pathologies. Mapping this relaxation time, however, involves extensive scan times, which are needed to collect quantitative data, thereby impeding its integration into clinical routine. This study employs a low-rank plus sparse (L + S) signal decomposition approach in order to reconstruct accurate T2-maps from highly undersampled multi-echo spin-echo (MESE) MRI data. METHODS Two new algorithms are presented: the first uses standard L + S approach, where both L and S are iteratively updated. The second technique, dubbed SPArse and fixed RanK (SPARK), uses a fixed-rank L, under the assumption that most MESE information is found in the L component and that this rank can be pre-calculated. The utility of these new techniques is demonstrated on in vivo brain and calf data at x2 to x6 acceleration factors. RESULTS Accelerated T2 maps showed improved accuracy compared to fully sampled ground truth maps, when using L + S and SPARK techniques vis-à-vis standard GRAPPA acceleration. CONCLUSION SPARK provides accurate T2 maps with increased robustness to the selection of reconstruction parameters making it suitable to a wide range of applications and facilitating the use of quantitative T2 information in clinical settings.
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Affiliation(s)
- Grzeda Daniel
- Department of Biomedical Engineering, Tel-Aviv University, Tel Aviv, Israel
| | - Galun Meirav
- Department of Computer Science and Applied Mathematics, Weitzman Institute of Science, Rehovot, Israel
| | - Omer Noam
- Department of Biomedical Engineering, Tel-Aviv University, Tel Aviv, Israel
| | | | - Radunsky Dvir
- Department of Biomedical Engineering, Tel-Aviv University, Tel Aviv, Israel
| | - Otazo Ricardo
- Departments of Medical Physics and Radiology, Memorial Sloan Kettering Cancer Center, New York, NY 10016, USA
| | - Ben-Eliezer Noam
- Department of Biomedical Engineering, Tel-Aviv University, Tel Aviv, Israel; Sagol School of Neuroscience, Tel-Aviv University, Tel-Aviv, Israel; Center for Advanced Imaging Innovation and Research (CAI2R), New-York University Langone Medical Center, New York, NY 10016, USA.
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Magnetic Resonance Image Compilation Was Used in Conjunction with Prostate PI-RADS v2.1 Score Has Diagnostic Relevance for Benign and Malignant Prostate Lesions. COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE 2022; 2022:3613540. [PMID: 36072774 PMCID: PMC9444436 DOI: 10.1155/2022/3613540] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/25/2022] [Revised: 07/22/2022] [Accepted: 07/27/2022] [Indexed: 12/24/2022]
Abstract
Objective To assess the diagnostic usefulness of magic in conjunction with PI-RADS v2.1 for prostate cancer malignant foci. Methods A total of 202 lesions (97 transitional zone lesions and 105 peripheral zone lesions) from 198 people were investigated retrospectively using traditional MRI and magic images. Each lesion has a unique pathological consequence. Lesions T1, T2, and PD values were employed as magic observation markers. The locations of the lesions were aggregated, and the paired t-test and receiver operating characteristic curve (ROC) were employed to find the indices with statistical significance in separating benign from malignant prostatic nodules (+1 point) and (−1 point) respectively. Draw a ROC curve and compare it to the PI-RADS v2.1 score using the magic positive and negative indices as well as the PI-RADS v2.1 score. By comparing the ROC curves scored separately, the diagnostic efficiency of the two scoring approaches for benign and malignant prostate lesions was investigated. Results T2 value has the highest diagnostic efficiency among the magic observation indices. T2 value of 77 ms for transitional zone lesions and T2 value of 89 ms for peripheral zone lesions are positive indices, whereas T2 value >77 ms and T2 value >89 ms are negative indexes. PI-RADS v2.1 combines one score and magic. In the transitional zone, the sensitivity, specificity, positive predictive value, and negative predictive value of the two scoring methods were 57.52, 87.70, 76.70, and 74.6 percent and 82.50, 73.68, 95.5, and 74.7 percent, respectively, and the AUC values were 0.735 and 0.846, respectively (P = 0.004); in the peripheral zone, the AUC values were 86.15 percent, 68.42 percent, 82.4. Conclusions Magic T2 value is a favorable sign for diagnosing benign and malignant prostate cancers when used in conjunction with PI-RADS v2.1. The end product exceeds PI-RADS v2.1 on its own, which is more useful in identifying benign and malignant prostate lesions, decreasing unnecessary puncture and alleviating patient pain.
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Dwivedi DK, Jagannathan NR. Emerging MR methods for improved diagnosis of prostate cancer by multiparametric MRI. MAGMA (NEW YORK, N.Y.) 2022; 35:587-608. [PMID: 35867236 DOI: 10.1007/s10334-022-01031-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/04/2021] [Revised: 06/28/2022] [Accepted: 07/08/2022] [Indexed: 06/15/2023]
Abstract
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.
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Affiliation(s)
- Durgesh Kumar Dwivedi
- Department of Radiodiagnosis, King George Medical University, Lucknow, UP, 226 003, India.
| | - Naranamangalam R Jagannathan
- Department of Radiology, Chettinad Hospital and Research Institute, Chettinad Academy of Research and Education, Kelambakkam, TN, 603 103, India.
- Department of Radiology, Sri Ramachandra Institute of Higher Education and Research, Chennai, TN, 600 116, India.
- Department of Electrical Engineering, Indian Institute Technology Madras, Chennai, TN, 600 036, India.
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Pseudo-T2 mapping for normalization of T2-weighted prostate MRI. MAGMA (NEW YORK, N.Y.) 2022; 35:573-585. [PMID: 35150363 PMCID: PMC9363383 DOI: 10.1007/s10334-022-01003-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/24/2021] [Revised: 12/22/2021] [Accepted: 01/23/2022] [Indexed: 01/04/2023]
Abstract
Objective Signal intensity normalization is necessary to reduce heterogeneity in T2-weighted (T2W) magnetic resonance imaging (MRI) for quantitative analysis of multicenter data. AutoRef is an automated dual-reference tissue normalization method that normalizes transversal prostate T2W MRI by creating a pseudo-T2 map. The aim of this study was to evaluate the accuracy of pseudo-T2s and multicenter standardization performance for AutoRef with three pairs of reference tissues: fat/muscle (AutoRefF), femoral head/muscle (AutoRefFH) and pelvic bone/muscle (AutoRefPB). Materials and methods T2s measured by multi-echo spin echo (MESE) were compared to AutoRef pseudo-T2s in the whole prostate (WP) and zones (PZ and TZ/CZ/AFS) for seven asymptomatic volunteers with a paired Wilcoxon signed-rank test. AutoRef normalization was assessed on T2W images from a multicenter evaluation set of 1186 prostate cancer patients. Performance was measured by inter-patient histogram intersections of voxel intensities in the WP before and after normalization in a selected subset of 80 cases. Results AutoRefFH pseudo-T2s best approached MESE T2s in the volunteer study, with no significant difference shown (WP: p = 0.30, TZ/CZ/AFS: p = 0.22, PZ: p = 0.69). All three AutoRef versions increased inter-patient histogram intersections in the multicenter dataset, with median histogram intersections of 0.505 (original data), 0.738 (AutoRefFH), 0.739 (AutoRefF) and 0.726 (AutoRefPB). Discussion All AutoRef versions reduced variation in the multicenter data. AutoRefFH pseudo-T2s were closest to experimentally measured T2s. Supplementary Information The online version contains supplementary material available at 10.1007/s10334-022-01003-9.
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Lo WC, Panda A, Jiang Y, Ahad J, Gulani V, Seiberlich N. MR fingerprinting of the prostate. MAGMA (NEW YORK, N.Y.) 2022; 35:557-571. [PMID: 35419668 DOI: 10.1007/s10334-022-01012-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/16/2021] [Revised: 03/21/2022] [Accepted: 03/24/2022] [Indexed: 06/03/2023]
Abstract
Multiparametric magnetic resonance imaging (mpMRI) has been adopted as the key tool for detection, localization, characterization, and risk stratification of patients suspected to have prostate cancer. Despite advantages over systematic biopsy, the interpretation of prostate mpMRI has limitations including a steep learning curve, leading to considerable interobserver variation. There is growing interest in clinical translation of quantitative imaging techniques for more objective lesion assessment. However, traditional mapping techniques are slow, precluding their use in the clinic. Magnetic resonance fingerprinting (MRF) is an efficient approach for quantitative maps of multiple tissue properties simultaneously. The T1 and T2 values obtained with MRF have been validated with phantom studies as well as in normal volunteers and patients. Studies have shown that MRF-derived T1 and T2 along with ADC values are all significant independent predictors in the differentiation between normal prostate tissue and prostate cancer, and hold promise in differentiating low and intermediate/high-grade cancers. This review seeks to introduce the basics of the prostate MRF technique, discuss the potential applications of prostate MRF for the characterization of prostate cancer, and describes ongoing areas of research.
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Affiliation(s)
- Wei-Ching Lo
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA
- Siemens Medical Solutions USA, Boston, Massachusetts, USA
| | - Ananya Panda
- Department of Radiology, Mayo Clinic, 200 1st Street SW, Rochester, MN, 55905, USA
| | - Yun Jiang
- Department of Radiology, University of Michigan, University of Michigan Health System, 1500 E. Medical Center Drive, Ann Arbor, MI, 48109-5030, USA
| | - James Ahad
- Case Western Reserve University, Cleveland, OH, USA
| | - Vikas Gulani
- Department of Radiology, University of Michigan, University of Michigan Health System, 1500 E. Medical Center Drive, Ann Arbor, MI, 48109-5030, USA
| | - Nicole Seiberlich
- Department of Radiology, University of Michigan, University of Michigan Health System, 1500 E. Medical Center Drive, Ann Arbor, MI, 48109-5030, USA.
- Case Western Reserve University, Cleveland, OH, USA.
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Bnaiahu N, Omer N, Wilczynski E, Levy S, Blumenfeld-Katzir T, Ben-Eliezer N. Correcting for imaging gradients-related bias of T 2 relaxation times at high-resolution MRI. Magn Reson Med 2022; 88:1806-1817. [PMID: 35666831 PMCID: PMC9544944 DOI: 10.1002/mrm.29319] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2022] [Revised: 04/15/2022] [Accepted: 05/11/2022] [Indexed: 11/16/2022]
Abstract
Purpose High‐resolution animal imaging is an integral part of preclinical drug development and the investigation of diseases' pathophysiology. Quantitative mapping of T2 relaxation times (qT2) is a valuable tool for both preclinical and research applications, providing high sensitivity to subtle tissue pathologies. High‐resolution T2 mapping, however, suffers from severe underestimation of T2 values due to molecular diffusion. This affects both single‐echo and multi‐echo spin echo (SSE and MESE), on top of the well‐known contamination of MESE signals by stimulated echoes, and especially on high‐field and preclinical scanners in which high imaging gradients are used in comparison to clinical scanners. Methods Diffusion bias due to imaging gradients was analyzed by quantifying the effective b‐value for each coherence pathway in SSE and MESE protocols, and incorporating this information in a joint T2‐diffusion reconstruction algorithm. Validation was done on phantoms and in vivo mouse brain using a 9.4T and a 7T MRI scanner. Results Underestimation of T2 values due to strong imaging gradients can reach up to 70%, depending on scan parameters and on the sample's diffusion coefficient. The algorithm presented here produced T2 values that agreed with reference spectroscopic measurements, were reproducible across scan settings, and reduced the average bias of T2 values from −33.5 ± 20.5% to −0.1 ± 3.6%. Conclusions A new joint T2‐diffusion reconstruction algorithm is able to negate imaging gradient–related underestimation of T2 values, leading to reliable mapping of T2 values at high resolutions. Click here for author‐reader discussions
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Affiliation(s)
- Natalie Bnaiahu
- Department of Biomedical Engineering, Tel Aviv University, Tel Aviv, Israel
| | - Noam Omer
- Department of Biomedical Engineering, Tel Aviv University, Tel Aviv, Israel
| | - Ella Wilczynski
- Department of Biomedical Engineering, Tel Aviv University, Tel Aviv, Israel
| | - Shir Levy
- School of Chemistry, Tel Aviv University, Tel Aviv, Israel
| | | | - Noam Ben-Eliezer
- Department of Biomedical Engineering, Tel Aviv University, Tel Aviv, Israel.,Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel.,Center for Advanced Imaging Innovation and Research (CAI2R), New York University School of Medicine, New York, NY, USA
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T2 mapping for the characterization of prostate lesions. World J Urol 2022; 40:1455-1461. [PMID: 35357510 PMCID: PMC9166840 DOI: 10.1007/s00345-022-03991-8] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Accepted: 03/11/2022] [Indexed: 11/26/2022] Open
Abstract
Purpose Purpose of this study is to evaluate the diagnostic accuracy of quantitative T2/ADC values in differentiating between PCa and lesions showing non-specific inflammatory infiltrates and atrophy, features of chronic prostatitis, as the most common histologically proven differential diagnosis. Methods In this retrospective, single-center cohort study, we analyzed 55 patients suspected of PCa, who underwent mpMRI (3T) including quantitative T2 maps before robot-assisted mpMRI-TRUS fusion prostate biopsy. All prostate lesions were scored according to PI-RADS v2.1. Regions of interest (ROIs) were annotated in focal lesions and normal prostate tissue. Quantitative mpMRI values from T2 mapping and ADC were compared using two-tailed t tests. Receiver operating characteristic curves (ROCs) and cutoff were calculated to differentiate between PCa and chronic prostatitis. Results Focal lesions showed significantly lower ADC and T2 mapping values than normal prostate tissue (p < 0.001). PCa showed significantly lower ADC and T2 values than chronic prostatitis (p < 0.001). ROC analysis revealed areas under the receiver operating characteristic curves (AUCs) of 0.85 (95% CI 0.74–0.97) for quantitative ADC values and 0.84 (95% CI 0.73–0.96) for T2 mapping. A significant correlation between ADC and T2 values was observed (r = 0.70; p < 0.001). Conclusion T2 mapping showed high diagnostic accuracy for differentiating between PCa and chronic prostatitis, comparable to the performance of ADC values. Supplementary Information The online version contains supplementary material available at 10.1007/s00345-022-03991-8.
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12
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Lee YS, Choi MH, Lee YJ, Han D, Kim DH. Magnetic resonance fingerprinting in prostate cancer before and after contrast enhancement. Br J Radiol 2022; 95:20210479. [PMID: 34415785 PMCID: PMC8978224 DOI: 10.1259/bjr.20210479] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
OBJECTIVES To assess the apparent diffusion coefficient (ADC) values and the T1 and T2 values derived from nonenhanced (NE) and contrast-enhanced (CE) magnetic resonance fingerprinting (MRF) in the prostate gland and to evaluate differences in values among prostate cancer, the normal peripheral zone (PZ) and the normal transition zone (TZ). METHODS Fifty-seven patients (median age, 73 years; range, 48-86) with prostate cancer who underwent multiparametric MRI including NE and CE MRF were included in this study. T1 and T2 values were extracted from NE and CE MRF, respectively. Five quantitative values (the ADC, NE T1, NE T2, CE T1 and CE T2 values) were measured in three areas: prostate cancer, PZ and TZ. We compared the values among the three areas and evaluated the differences between NE MRF and CE MRF values. RESULTS ADC values and MRF-derived values were significantly higher in PZ than prostate cancer or TZ (p < 0.001). TZ had a significantly lower CE T1 but significantly higher values of the other variables than prostate cancer (p < 0.001). The T1 values in all three areas and the T2 values in prostate cancer and TZ were significantly lower on CE MRF than on NE MRF (p < 0.001). CONCLUSIONS Quantitative analysis of NE and CE MRI can be conducted by using the MRF technique. The ADC value and the T1 and T2 values from CE MRF and NE MRF were found to be significantly different between prostate cancer and normal prostate tissue. ADVANCES IN KNOWLEDGE The T1 and T2 values from contrast-enhanced MR fingerprinting are significantly different between prostate cancer and normal prostate tissue.
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Affiliation(s)
- Young Sub Lee
- Department of Hospital Pathology, Eunpyeong St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Moon Hyung Choi
- Department of Radiology, Eunpyeong St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Young Joon Lee
- Department of Radiology, Eunpyeong St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Dongyeob Han
- Siemens Healthineers Ltd., Seoul, Republic of Korea
| | - Dong-Hyun Kim
- School of Electrical and Electronic Engineering, Yonsei University, Seoul, Korea
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13
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MR Imaging in Real Time Guiding of Therapies in Prostate Cancer. Life (Basel) 2022; 12:life12020302. [PMID: 35207589 PMCID: PMC8878909 DOI: 10.3390/life12020302] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2022] [Revised: 01/31/2022] [Accepted: 02/11/2022] [Indexed: 11/22/2022] Open
Abstract
Magnetic resonance imaging (MRI)-guided therapy for prostate cancer (PCa) aims to reduce the treatment-associated comorbidity of existing radical treatment, including radical prostatectomy and radiotherapy. Although active surveillance has been used as a conservative method to reduce overtreatment, there is a growing demand for less morbidity and personalized (focal) treatment. The development of multiparametric MRI was of real importance in improving the detection, localization and staging of PCa. Moreover, MRI has been useful for lesion targeting within the prostate, as it is used in the guidance of prostate biopsies, by means of cognitive registration, MRI-ultrasound fusion guidance or direct in-bore MRI-guidance. With regard to PCa therapies, MRI is used for precise probe placement into the lesion and to accurately monitor the treatment in real-time. Moreover, advances in MR-compatible thermal ablation allow for noninvasive real-time temperature mapping during treatment. In this review, we present an overview of the current status of MRI-guided therapies in PCa, focusing on cryoablation, focal laser ablation, high intensity focused ultrasound and transurethral ultrasound ablation. We explain the important role of MRI in the evaluation of the completeness of the ablation and during follow-up. Finally, we will discuss the challenges and future development inherent to these new technologies.
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14
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Choi IY, Yeom SK. Editorial for "Value of T2 Mapping MRI for Prostate Cancer Detection and Classification". J Magn Reson Imaging 2022; 56:423-424. [PMID: 35014109 DOI: 10.1002/jmri.28058] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2021] [Accepted: 12/09/2021] [Indexed: 11/07/2022] Open
Affiliation(s)
- In Young Choi
- Department of Radiology, Korea University Ansan Hospital, Korea University College of Medicine, Danwon-gu, Ansan, Republic of Korea
| | - Suk Keu Yeom
- Department of Radiology, Korea University Ansan Hospital, Korea University College of Medicine, Danwon-gu, Ansan, Republic of Korea
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15
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Arita Y, Akita H, Fujiwara H, Hashimoto M, Shigeta K, Kwee TC, Yoshida S, Kosaka T, Okuda S, Oya M, Jinzaki M. Synthetic magnetic resonance imaging for primary prostate cancer evaluation: Diagnostic potential of a non-contrast-enhanced bi-parametric approach enhanced with relaxometry measurements. Eur J Radiol Open 2022; 9:100403. [PMID: 35242886 PMCID: PMC8857584 DOI: 10.1016/j.ejro.2022.100403] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2022] [Accepted: 02/09/2022] [Indexed: 12/28/2022] Open
Abstract
Purpose Bi-parametric magnetic resonance imaging (bpMRI) with diffusion-weighted images has wide utility in diagnosing clinically significant prostate cancer (csPCa). However, bpMRI yields more false-negatives for PI-RADS category 3 lesions than multiparametric (mp)MRI with dynamic-contrast-enhanced (DCE)-MRI. We investigated the utility of synthetic MRI with relaxometry maps for bpMRI-based diagnosis of csPCa. Methods One hundred and five treatment-naïve patients who underwent mpMRI and synthetic MRI before prostate biopsy for suspected PCa between August 2019 and December 2020 were prospectively included. Three experts and three basic prostate radiologists evaluated the diagnostic performance of conventional bpMRI and synthetic bpMRI for csPCa. PI-RADS version 2.1 category 3 lesions were identified by consensus, and relaxometry measurements (T1-value, T2-value, and proton density [PD]) were performed. The diagnostic performance of relaxometry measurements for PI-RADS category 3 lesions in peripheral zone was compared with that of DCE-MRI. Histopathological evaluation results were used as the reference standard. Statistical analysis was performed using the areas under the receiver operating characteristic curve (AUC) and McNemar test. Results In 102 patients without significant MRI artefacts, the diagnostic performance of conventional bpMRI was not significantly different from that of synthetic bpMRI for all readers (p = 0.11–0.79). The AUCs of the combination of T1-value, T2-value, and PD (T1 + T2 + PD) for csPCa in peripheral zone for PI-RADS category 3 lesions were 0.85 for expert and 0.86 for basic radiologists, with no significant difference between T1 + T2 + PD and DCE-MRI for both expert and basic radiologists (p = 0.29–0.45). Conclusion Synthetic MRI with relaxometry maps shows promise for contrast media-free evaluation of csPCa. Diagnostic performances of synthetic bpMRI and conventional bpMRI are comparable for primary PCa Diagnostic performance of synthetic MRI variables are similar to that of DCE-MRI for csPCa in PZ Synthetic bpMRI shows potential as a contrast agent-free method for primary PCa
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16
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Shpringer G, Bendahan D, Ben-Eliezer N. Accelerated reconstruction of dictionary-based T 2 relaxation maps based on dictionary compression and gradient descent search algorithms. Magn Reson Imaging 2021; 87:56-66. [PMID: 34973389 DOI: 10.1016/j.mri.2021.12.006] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2021] [Revised: 11/19/2021] [Accepted: 12/22/2021] [Indexed: 11/18/2022]
Abstract
Background Quantitative T2-relaxation-based contrast maps have shown to be highly beneficial for clinical diagnosis and follow-up. The generation of quantitative maps, however, is impaired by long acquisition times, and time-consuming post-processing schemes. The EMC platform is a dictionary-based technique, which involves simulating theoretical signal curves for different physical and experimental values, followed by matching the experimentally acquired signals to the set simulated ones. Purpose Although the EMC technique has shown to produce accurate T2 maps, it involves computationally intensive post-processing procedures. In this work we present an approach for accelerating the reconstruction of T2 relaxation maps. Methods This work presents two alternative post-processing approaches for accelerating the reconstruction of EMC-based T2 relaxation maps. These are (a) Dictionary compression using principal component analysis (PCA) and (b) gradient-descent search algorithm. Additional acceleration was achieved by finding the optimal MATLAB C++ compiler. The utility of the two suggested approaches was examined by calculating the relative error, produced by each technique. Results Gradient descent method was in perfect agreement with the ground truth exhaustive search matching process. PCA based acceleration produced root mean square error (RMSE) of up to 4% compared to exhaustive matching process. Overall acceleration of x16 was achieved using gradient descent in addition to x7 acceleration by choosing the optimal MATLAB C++ compiler. Conclusions Postprocessing of EMC-based T2 relaxation maps can be accelerated without impairing the accuracy of the ensuing T2 values.
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Affiliation(s)
- Guy Shpringer
- Department of Biomedical Engineering, Tel Aviv University, Tel Aviv, Israel
| | - David Bendahan
- Aix Marseille University, CNRS UMR 7339, CRMBM, Marseille, France
| | - Noam Ben-Eliezer
- Department of Biomedical Engineering, Tel Aviv University, Tel Aviv, Israel; Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel; Center for Advanced Imaging Innovation and Research (CAI2R), New York University Langone Medical Center, New York, NY, USA.
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17
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Freitas AC, Gaspar AS, Sousa I, Teixeira RPAG, Hajnal JV, Nunes RG. Improving B 1 + parametric estimation in the brain from multispin-echo sequences using a fusion bootstrap moves solver. Magn Reson Med 2021; 86:2426-2440. [PMID: 34231250 DOI: 10.1002/mrm.28878] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2020] [Revised: 05/08/2021] [Accepted: 05/11/2021] [Indexed: 11/10/2022]
Abstract
PURPOSE To simultaneously estimate the B 1 + field (along with the T2 ) in the brain with multispin-echo (MSE) sequences and dictionary matching. METHODS T2 mapping provides clinically relevant information such as in the assessment of brain degenerative diseases. It is commonly obtained with MSE sequences, and accuracy can be further improved by matching the MSE signal to a precomputed dictionary of echo-modulation curves. For additional T1 quantification, transmit B 1 + field knowledge is also required. Preliminary work has shown that although simultaneous brain B 1 + estimation along with T2 is possible, it presents a bimodal distribution with the main peak coinciding with the true value. By taking advantage of this, the B 1 + maps are expected to be spatially smooth by applying an iterative method that takes into account each pixel neighborhood known as the fusion bootstrap moves solver (FBMS). The effect of the FBMS on B 1 + accuracy and piecewise smoothness is investigated and different spatial regularization levels are compared. Total variation regularization was used for both B 1 + and T2 simultaneous estimation because of its simplicity as an initial proof-of-concept; future work could explore non edge-preserving regularization independently for B 1 + . RESULTS Improvements in B 1 + accuracy (up to 45.37% and 16.81% B 1 + error decrease) and recovery of spatially homogeneous maps are shown in simulations and in vivo 3.0T brain data, respectively. CONCLUSION Accurate B 1 + estimated values can be obtained from widely available MSE sequences while jointly estimating T2 maps with the use of echo-modulation curve matching and FBMS at no further cost.
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Affiliation(s)
- Andreia C Freitas
- Institute for Systems and Robotics (ISR-Lisboa)/LaRSyS and Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
| | - Andreia S Gaspar
- Institute for Systems and Robotics (ISR-Lisboa)/LaRSyS and Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
| | - Inês Sousa
- Institute for Systems and Robotics (ISR-Lisboa)/LaRSyS and Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
| | - Rui P A G Teixeira
- Centre for the Developing Brain, School of Imaging Sciences and Biomedical Engineering, King's College London, London, United Kingdom
| | - Joseph V Hajnal
- Centre for the Developing Brain, School of Imaging Sciences and Biomedical Engineering, King's College London, London, United Kingdom
| | - Rita G Nunes
- Institute for Systems and Robotics (ISR-Lisboa)/LaRSyS and Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal.,Centre for the Developing Brain, School of Imaging Sciences and Biomedical Engineering, King's College London, London, United Kingdom
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18
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Sathiadoss P, Schieda N, Haroon M, Osman H, Alrasheed S, Flood TA, Melkus G. Utility of Quantitative T2-Mapping Compared to Conventional and Advanced Diffusion Weighted Imaging Techniques for Multiparametric Prostate MRI in Men with Hip Prosthesis. J Magn Reson Imaging 2021; 55:265-274. [PMID: 34223675 DOI: 10.1002/jmri.27803] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2021] [Revised: 06/11/2021] [Accepted: 06/11/2021] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND Diffusion weighted imaging (DWI) is fundamental for prostate cancer (PCa) detection with MRI; however, limited by susceptibility artifact from hip prosthesis. PURPOSE To evaluate image quality and ability to detect PCa with quantitative T2-mapping and DWI in men with hip prosthesis undergoing prostate MRI. STUDY TYPE Prospective, cross-sectional study. POPULATION Thirty consecutive men with hip replacement (18 unilateral, 12 bilateral) undergoing prostate MRI from 2019 to 2021. FIELD STRENGTH/SEQUENCE 3-T; multiparametric MRI (T2W, DCE-MRI, echo-planar [EPI]-DWI), T2-mapping (Carr-Purcell-Meiboom-Gill), FOCUS-EPI-DWI, PROPELLER-DWI. ASSESSMENT Five blinded radiologists independently evaluated MRI image quality using a 5-point Likert scale. PI-RADS v2.1 scores were applied in four interpretation strategies: 1) T2W-FSE+DCE-MRI+EPI-DWI, 2) T2W-FSE+DCE-MRI+EPI-DWI+FOCUS-EPI-DWI, 3) T2W-FSE+DCE-MRI+EPI-DWI+PROPELLER-DWI, 4) T2W-FSE+DCE-MRI+EPI-DWI+T2-maps. Five-point confidence scores were recorded. STATISTICAL ANALYSIS ANOVA, Kruskal-Wallis with pair-wise comparisons by Wilcoxon sign-rank, and paired t-tests, P < 0.05 was considered significant. Cohen's Kappa (k) for PI-RADSv2.1 scoring and proportion of correctly classified lesions tabulated for pathology-confirmed cases with 95% confidence intervals (CIs). RESULTS For all radiologists, T2-map image quality was significantly higher than EPI-DWI, FOCUS-EPI-DWI, and PROPELLER-DWI and similar (P = 0.146-0.706) or significantly better (for two readers) than T2W-FSE and DCE-MRI. PI-RADS v2.1 agreement improved comparing strategy A (k = 0.46) to strategy B (k = 0.58) to strategy C (k = 0.58) and was highest with strategy D which included T2-maps (k = 1.00). Radiologists' confidence was significantly highest with strategy D. Strategies B and C had similar confidence (P = 0.051-0.063) both significantly outperforming strategy A. Twelve men with 17 lesions had pathology confirmed diagnoses (13 PCa, 4 benign). Strategy D had the highest proportion of correctly classified lesions (76.5-82.4%) with overlapping 95% confidence intervals. DATA CONCLUSION T2-mapping may be a valuable adjunct to prostate MRI in men with hip replacement resulting in improved image quality, higher reader confidence, interobserver agreement, and accuracy in PI-RADS scoring. LEVEL OF EVIDENCE 1 TECHNICAL EFFICACY STAGE: 2.
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Affiliation(s)
- Paul Sathiadoss
- Department of Medical Imaging, The Ottawa Hospital, University of Ottawa, Ottawa, Ontario, Canada
| | - Nicola Schieda
- Department of Medical Imaging, The Ottawa Hospital, University of Ottawa, Ottawa, Ontario, Canada
| | - Mohammad Haroon
- Department of Medical Imaging, The Ottawa Hospital, University of Ottawa, Ottawa, Ontario, Canada
| | - Heba Osman
- Department of Medical Imaging, The Ottawa Hospital, University of Ottawa, Ottawa, Ontario, Canada
| | - Sumaya Alrasheed
- Department of Medical Imaging, The Ottawa Hospital, University of Ottawa, Ottawa, Ontario, Canada
| | - Trevor A Flood
- Department of Anatomical Pathology, The Ottawa Hospital, University of Ottawa, Ottawa, Ontario, Canada
| | - Gerd Melkus
- Department of Medical Imaging, The Ottawa Hospital, University of Ottawa, Ottawa, Ontario, Canada
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Wang YF, Tadimalla S, Hayden AJ, Holloway L, Haworth A. Artificial intelligence and imaging biomarkers for prostate radiation therapy during and after treatment. J Med Imaging Radiat Oncol 2021; 65:612-626. [PMID: 34060219 DOI: 10.1111/1754-9485.13242] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2021] [Revised: 04/18/2021] [Accepted: 05/02/2021] [Indexed: 12/15/2022]
Abstract
Magnetic resonance imaging (MRI) is increasingly used in the management of prostate cancer (PCa). Quantitative MRI (qMRI) parameters, derived from multi-parametric MRI, provide indirect measures of tumour characteristics such as cellularity, angiogenesis and hypoxia. Using Artificial Intelligence (AI), relevant information and patterns can be efficiently identified in these complex data to develop quantitative imaging biomarkers (QIBs) of tumour function and biology. Such QIBs have already demonstrated potential in the diagnosis and staging of PCa. In this review, we explore the role of these QIBs in monitoring treatment response during and after PCa radiotherapy (RT). Recurrence of PCa after RT is not uncommon, and early detection prior to development of metastases provides an opportunity for salvage treatments with curative intent. However, the current method of monitoring treatment response using prostate-specific antigen levels lacks specificity. QIBs, derived from qMRI and developed using AI techniques, can be used to monitor biological changes post-RT providing the potential for accurate and early diagnosis of recurrent disease.
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Affiliation(s)
- Yu-Feng Wang
- Institute of Medical Physics, School of Physics, Faculty of Science, The University of Sydney, Sydney, New South Wales, Australia
- Ingham Institute for Applied Medical Research, Liverpool, New South Wales, Australia
| | - Sirisha Tadimalla
- Institute of Medical Physics, School of Physics, Faculty of Science, The University of Sydney, Sydney, New South Wales, Australia
| | - Amy J Hayden
- Sydney West Radiation Oncology, Westmead Hospital, Wentworthville, New South Wales, Australia
- Faculty of Medicine, Western Sydney University, Sydney, New South Wales, Australia
- Faculty of Medicine, Health & Human Sciences, Macquarie University, Sydney, New South Wales, Australia
| | - Lois Holloway
- Institute of Medical Physics, School of Physics, Faculty of Science, The University of Sydney, Sydney, New South Wales, Australia
- Ingham Institute for Applied Medical Research, Liverpool, New South Wales, Australia
- Liverpool and Macarthur Cancer Therapy Centre, Liverpool Hospital, Liverpool, New South Wales, Australia
| | - Annette Haworth
- Institute of Medical Physics, School of Physics, Faculty of Science, The University of Sydney, Sydney, New South Wales, Australia
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20
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Han D, Choi MH, Lee YJ, Kim DH. Feasibility of Novel Three-Dimensional Magnetic Resonance Fingerprinting of the Prostate Gland: Phantom and Clinical Studies. Korean J Radiol 2021; 22:1332-1340. [PMID: 34047506 PMCID: PMC8316768 DOI: 10.3348/kjr.2020.1362] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2020] [Revised: 02/08/2021] [Accepted: 03/17/2021] [Indexed: 01/24/2023] Open
Abstract
Objective To evaluate the feasibility of a new three-dimensional (3D) MR fingerprinting (MRF) technique for the prostate gland by conducting phantom and clinical studies. Materials and Methods The new 3D MRF technique used in this study enables quick data acquisition and has a high resolution. For the phantom study, the MRF T1 and T2 values in an in-house phantom were compared with those of gold-standard mapping methods using linear regression analysis. For the clinical study, we evaluated 90 patients who underwent prostate imaging with MRF for suspected prostate cancer between September 2019 and February 2020. The mean T1 and T2 values were compared in the peripheral zone, transition zone, and focal lesions using paired t tests. The differences in the T1 and T2 values according to cancer aggressiveness were evaluated using one-way analysis of variance. Results In the phantom study, the MRF T1 and T2 values showed a perfect correlation with the gold-standard T1 and T2 values (R > 0.99). In the clinical study, the T1 and T2 values in the peripheral zone were significantly higher than those in the transitional zone (p < 0.001, both). The T1 and T2 values in prostate cancer were significantly lower than those in the peripheral and transitional zones. The higher the grade of cancer, the lower the T2 values. Conclusion The T1 and T2 values obtained from the 3D MRF showed a perfect correlation with the gold standard values in the phantom study. Differences in the T1 and T2 values among the different zones of the prostate gland were identified using 3D MRF in patients.
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Affiliation(s)
| | - Moon Hyung Choi
- Department of Radiology, Eunpyeong St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea.
| | - Young Joon Lee
- Department of Radiology, Eunpyeong St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - Dong Hyun Kim
- School of Electrical and Electronic Engineering, Yonsei University, Seoul, Korea
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21
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Tomaszewski MR, Dominguez-Viqueira W, Ortiz A, Shi Y, Costello JR, Enderling H, Rosenberg SA, Gillies RJ. Heterogeneity analysis of MRI T2 maps for measurement of early tumor response to radiotherapy. NMR IN BIOMEDICINE 2021; 34:e4454. [PMID: 33325086 DOI: 10.1002/nbm.4454] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/24/2020] [Accepted: 11/09/2020] [Indexed: 06/12/2023]
Abstract
External beam radiotherapy (XRT) is a widely used cancer treatment, yet responses vary dramatically among patients. These differences are not accounted for in clinical practice, partly due to a lack of sensitive early response biomarkers. We hypothesize that quantitative magnetic resonance imaging (MRI) measures reflecting tumor heterogeneity can provide a sensitive and robust biomarker of early XRT response. MRI T2 mapping was performed every 72 hours following 10 Gy dose XRT in two models of pancreatic cancer propagated in the hind limb of mice. Interquartile range (IQR) of tumor T2 was presented as a potential biomarker of radiotherapy response compared with tumor growth kinetics, and biological validation was performed through quantitative histology analysis. Quantification of tumor T2 IQR showed sensitivity for detection of XRT-induced tumor changes 72 hours after treatment, outperforming T2-weighted and diffusion-weighted MRI, with very good robustness. Histological comparison revealed that T2 IQR provides a measure of spatial heterogeneity in tumor cell density, related to radiation-induced necrosis. Early IQR changes were found to correlate to subsequent tumor volume changes, indicating promise for treatment response prediction. Our preclinical findings indicate that spatial heterogeneity analysis of T2 MRI can provide a translatable method for early radiotherapy response assessment. We propose that the method may in future be applied for personalization of radiotherapy through adaptive treatment paradigms.
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Affiliation(s)
- Michal R Tomaszewski
- Department of Cancer Physiology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida, USA
| | - William Dominguez-Viqueira
- Small Imaging Laboratory Core Facility, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida, USA
| | - Antonio Ortiz
- Analytical Microscopy Core Facility, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida, USA
| | - Yu Shi
- Department of Radiology, ShengJing Hospital of China Medical University, Shenyang, China
| | - James R Costello
- Department of Radiology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida, USA
| | - Heiko Enderling
- Department of Integrated Mathematical Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida, USA
- Department of Radiation Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida, USA
| | - Stephen A Rosenberg
- Department of Radiation Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida, USA
| | - Robert J Gillies
- Department of Cancer Physiology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida, USA
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22
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Abstract
Prostate MRI has seen increasing interest in recent years and has led to the development of new MRI techniques and sequences to improve prostate cancer (PCa) diagnosis which are reviewed in this article. Numerous studies have focused on improving image quality (segmented DWI) and faster acquisition (compressed sensing, k-t-SENSE, PROPELLER). An increasing number of studies have developed new quantitative and computer-aided diagnosis methods including artificial intelligence (PROSTATEx challenge) that mitigate the subjective nature of mpMRI interpretation. MR fingerprinting allows rapid, simultaneous generation of quantitative maps of multiple physical properties (T1, T2), where PCa are characterized by lower T1 and T2 values. New techniques like luminal water imaging (LWI), restriction spectrum imaging (RSI), VERDICT and hybrid multi-dimensional MRI (HM-MRI) have been developed for microstructure imaging, which provide information similar to histology. The distinct MR properties of tissue components and their change with the presence of cancer is used to diagnose prostate cancer. LWI is a T2-based imaging technique where long T2-component corresponding to luminal water is reduced in PCa. RSI and VERDICT are diffusion-based techniques where PCa is characterized by increased signal from intra-cellular restricted water and increased intracellular volume fraction, respectively, due to increased cellularity. VERDICT also reveal loss of extracellular-extravascular space in PCa due to loss of glandular structure. HM-MRI measures volumes of prostate tissue components, where PCa has reduced lumen and stromal and increased epithelium volume similar to results shown in histology. Similarly, molecular imaging using hyperpolarized 13C imaging has been utilized.
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23
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Roccia E, Neji R, Benkert T, Kiefer B, Goh V, Dregely I. Distortion-free 3D diffusion imaging of the prostate using a multishot diffusion-prepared phase-cycled acquisition and dictionary matching. Magn Reson Med 2020; 85:1441-1454. [PMID: 32989765 DOI: 10.1002/mrm.28527] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2020] [Revised: 07/27/2020] [Accepted: 08/31/2020] [Indexed: 11/06/2022]
Abstract
PURPOSE To achieve three-dimensional (3D) distortion-free apparent diffusion coefficient (ADC) maps for prostate imaging using a multishot diffusion prepared-gradient echo (msDP-GRE) sequence and ADC dictionary matching. METHODS The msDP-GRE sequence is combined with a 3D Cartesian, centric k-space trajectory with center oversampling. Oversampled k-space center averaging and phase cycling are used to address motion- and eddy current-induced magnitude corruption. Extended-phase-graph (EPG) simulations and ADC dictionary matching are used to compensate for T1 effects. To shorten the acquisition time, each volume is undersampled by a factor of two and reconstructed using iterative sensitivity encoding. The proposed approach is characterized using simulations and validated in a kiwifruit phantom, comparing the msDP-GRE ADC maps obtained using both standard monoexponential fitting and dictionary matching with the clinical standard single-shot diffusion weighted-echo planar imaging (ssDW-EPI) ADC. Initial in vivo feasibility is tested in three healthy subjects, and geometric distortion is compared with anatomical T2 -weighted-turbo spin echo. RESULTS In the kiwifruit phantom experiment, the signal magnitude could be recovered using k-space center averaging and phase cycling. No statistically significant difference was observed in the ADC values estimated using msDP-GRE with dictionary matching and clinical standard DW-EPI (P < .05). The in vivo prostate msDP-GRE scans were free of geometric distortion caused by off-resonance susceptibility, and the ADC values in the prostate were in agreement with values found in the published literature. CONCLUSION Nondistorted 3D ADC maps of the prostate can be achieved using a msDP sequence and dictionary matching.
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Affiliation(s)
- Elisa Roccia
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Radhouene Neji
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom.,MR Research Collaboration, Siemens Healthcare Limited, Frimley, United Kingdom
| | - Thomas Benkert
- Oncology Application Predevelopment, Siemens Healthcare GmbH, Erlangen, Germany
| | - Berthold Kiefer
- Oncology Application Predevelopment, Siemens Healthcare GmbH, Erlangen, Germany
| | - Vicky Goh
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom.,Department of Radiology, Guy's & St Thomas' NHS Foundation Trust, London, United Kingdom
| | - Isabel Dregely
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
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Lee CH, Taupitz M, Asbach P, Lenk J, Haas M. Clinical utility of combined T2-weighted imaging and T2-mapping in the detection of prostate cancer: a multi-observer study. Quant Imaging Med Surg 2020; 10:1811-1822. [PMID: 32879859 DOI: 10.21037/qims-20-222] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
Background To evaluate the clinical utility of combined T2-weighted imaging and T2-mapping for the detection of prostate cancer. Methods Forty patients underwent multiparametric magnetic resonance imaging (mpMRI) and T2-mapping of the prostate. Three readers each reviewed two sets of images: T2-weighted fast spin-echo (FSE) sequence (standard T2), and standard T2 in combination with T2-mapping. Each reader assigned probability scores for malignancy to each zone [peripheral zone (PZ) or transition zone (TZ)]. Inter-observer variability for standard T2 and combined standard T2 with T2-mapping were assessed. Diagnostic accuracy was compared between standard T2 and combined standard T2 with T2-mapping. Results There was fair agreement between all three readers for standard T2 [intraclass correlation coefficient (ICC) =0.56] and combined standard T2 with T2-mapping (ICC =0.58). There was no significant difference in the area under the receiver operator characteristics curve for standard T2 compared to combined standard T2 with T2-mapping (0.89 vs. 0.82, P=0.31). Sensitivity (Sn) for combined standard T2 with T2-mapping was significantly higher compared to standard T2 alone (73.0% vs. 49.2%, P=0.006). Specificity (Sp) for combined standard T2 with T2-mapping was borderline significantly lower compared to standard T2 alone (89.3% vs. 94.9%, P=0.05). There was no significant differences between the negative predictive values (NPVs) and positive predictive values (PPVs) (P=0.07, P=0.45). Conclusions Combination of T2-weighted imaging and T2-mapping could potentially increase Sn for prostate malignancy compared to T2-weighted imaging alone.
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Affiliation(s)
- Chau Hung Lee
- Department of Radiology, Charite-Universitätsmedizin Berlin, Campus Benjamin Franklin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany.,Department of Radiology, Tan Tock Seng Hospital, Singapore, Singapore
| | - Matthias Taupitz
- Department of Radiology, Charite-Universitätsmedizin Berlin, Campus Benjamin Franklin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Patrick Asbach
- Department of Radiology, Charite-Universitätsmedizin Berlin, Campus Benjamin Franklin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Julian Lenk
- Department of Radiology, Charite-Universitätsmedizin Berlin, Campus Benjamin Franklin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Matthias Haas
- Department of Radiology, Charite-Universitätsmedizin Berlin, Campus Benjamin Franklin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
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25
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Walker SM, Fernandez M, Turkbey B. Advances in Prostate Magnetic Resonance Imaging. Magn Reson Imaging Clin N Am 2020; 28:407-414. [PMID: 32624158 DOI: 10.1016/j.mric.2020.03.006] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Prostate magnetic resonance (MR) imaging is a widely used imaging technique to detect intraprostatic lesions and guide prostate biopsies, with continuous technical advances for better accuracy in prostate cancer diagnosis. Current evaluation of prostate multiparametric MR imaging mainly depends on qualitative evaluation, which is prone to inter-reader variation. Recent advances in prostate MR imaging, such as quantitative T2 mapping and abbreviated MR imaging protocols (eg, biparametric MR imaging), are designed to simplify prostate MR imaging acquisition and interpretation.
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Affiliation(s)
- Stephanie M Walker
- Molecular Imaging Program, NCI, NIH, 10 Center Drive, Building 10, Room B3B85, Bethesda, MD 20814, USA
| | - Martina Fernandez
- Molecular Imaging Program, NCI, NIH, 10 Center Drive, Building 10, Room B3B85, Bethesda, MD 20814, USA; Department of Radiology, Hospital Alemán, Buenos Aires, Argentina
| | - Baris Turkbey
- Molecular Imaging Program, NCI, NIH, 10 Center Drive, Building 10, Room B3B85, Bethesda, MD 20814, USA.
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26
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Schieda N, Lim CS, Zabihollahy F, Abreu-Gomez J, Krishna S, Woo S, Melkus G, Ukwatta E, Turkbey B. Quantitative Prostate MRI. J Magn Reson Imaging 2020; 53:1632-1645. [PMID: 32410356 DOI: 10.1002/jmri.27191] [Citation(s) in RCA: 35] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2020] [Revised: 04/24/2020] [Accepted: 04/24/2020] [Indexed: 12/17/2022] Open
Abstract
Prostate MRI is reported in clinical practice using the Prostate Imaging and Data Reporting System (PI-RADS). PI-RADS aims to standardize, as much as possible, the acquisition, interpretation, reporting, and ultimately the performance of prostate MRI. PI-RADS relies upon mainly subjective analysis of MR imaging findings, with very few incorporated quantitative features. The shortcomings of PI-RADS are mainly: low-to-moderate interobserver agreement and modest accuracy for detection of clinically significant tumors in the transition zone. The use of a more quantitative analysis of prostate MR imaging findings is therefore of interest. Quantitative MR imaging features including: tumor size and volume, tumor length of capsular contact, tumor apparent diffusion coefficient (ADC) metrics, tumor T1 and T2 relaxation times, tumor shape, and texture analyses have all shown value for improving characterization of observations detected on prostate MRI and for differentiating between tumors by their pathological grade and stage. Quantitative analysis may therefore improve diagnostic accuracy for detection of cancer and could be a noninvasive means to predict patient prognosis and guide management. Since quantitative analysis of prostate MRI is less dependent on an individual users' assessment, it could also improve interobserver agreement. Semi- and fully automated analysis of quantitative (radiomic) MRI features using artificial neural networks represent the next step in quantitative prostate MRI and are now being actively studied. Validation, through high-quality multicenter studies assessing diagnostic accuracy for clinically significant prostate cancer detection, in the domain of quantitative prostate MRI is needed. This article reviews advances in quantitative prostate MRI, highlighting the strengths and limitations of existing and emerging techniques, as well as discussing opportunities and challenges for evaluation of prostate MRI in clinical practice when using quantitative assessment. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Nicola Schieda
- Department of Medical Imaging, The Ottawa Hospital, Ottawa, Ontario, Canada
| | - Christopher S Lim
- Department of Medical Imaging, Sunnybrook Health Sciences, Toronto, Ontario, Canada
| | | | - Jorge Abreu-Gomez
- Department of Medical Imaging, Sunnybrook Health Sciences, Toronto, Ontario, Canada
| | - Satheesh Krishna
- Joint Department of Medical Imaging, University Health Network, Toronto, Ontario, Canada
| | - Sungmin Woo
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Gerd Melkus
- Department of Medical Imaging, The Ottawa Hospital, Ottawa, Ontario, Canada
| | - Eran Ukwatta
- Faculty of Engineering, Guelph University, Guelph, Ontario, Canada
| | - Baris Turkbey
- Molecular Imaging Program, National Cancer Institute NIH, Bethesda, Maryland, USA
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Cui Y, Han S, Liu M, Wu PY, Zhang W, Zhang J, Li C, Chen M. Diagnosis and Grading of Prostate Cancer by Relaxation Maps From Synthetic MRI. J Magn Reson Imaging 2020; 52:552-564. [PMID: 32027071 DOI: 10.1002/jmri.27075] [Citation(s) in RCA: 42] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2019] [Revised: 01/12/2020] [Accepted: 01/13/2020] [Indexed: 12/18/2022] Open
Abstract
BACKGROUND The interpretation system for prostate MRI is largely based on qualitative image contrast of different tissue types. Therefore, a fast, standardized, and robust quantitative technique is necessary. Synthetic MRI is capable of quantifying multiple relaxation parameters, which might have potential applications in prostate cancer (PCa). PURPOSE To investigate the use of quantitative relaxation maps derived from synthetic MRI for the diagnosis and grading of PCa. STUDY TYPE Prospective. SUBJECTS In all, 94 men with pathologically confirmed PCa or benign pathological changes. FIELD STRENGTH/SEQUENCE T1 -weighted imaging, T2 -weighted imaging, diffusion-weighted imaging, and synthetic MRI at 3.0T. ASSESSMENT Four kinds of tissue types were identified on pathology, including PCa, stromal hyperplasia (SH), glandular hyperplasia (GH), and noncancerous peripheral zone (PZ). PCa foci were grouped as low-grade (LG, Gleason score ≤6) and intermediate/high-grade (HG, Gleason score ≥7). Regions of interest were manually drawn by two radiologists in consensus on parametric maps according to the pathological results. STATISTICAL TESTS Independent sample t-test, Mann-Whitney U-test, and receiver operating characteristic curve analysis. RESULTS T1 and T2 values of PCa were significantly lower than SH (P = 0.015 and 0.002). The differences of T1 and T2 values between PCa and noncancerous PZ were also significant (P ≤ 0.006). The area under the curve (AUC) of the apparent diffusion coefficient (ADC) value was significantly higher than T1 , T2 , and proton density (PD) values in discriminating PCa from SH and noncancerous PZ (P ≤ 0.025). T2 , PD, and ADC values demonstrated similar diagnostic performance in discriminating LG from HG PCa (AUC = 0.806 [0.640-0.918], 0.717 [0.542-0.854], and 0.817 [0.652-0.925], respectively; P ≥ 0.535). DATA CONCLUSION Relaxation maps derived from synthetic MRI were helpful for discriminating PCa from other benign pathologies. But the overall diagnostic performance was inferior to the ADC values. T2 , PD, and ADC values performed similarly in discriminating LG from HG PCa lesions. LEVEL OF EVIDENCE 2 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2020;52:552-564.
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Affiliation(s)
- Yadong Cui
- Department of Radiology, Beijing Hospital, National Center of Gerontology; Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing P. R., China.,Graduate School of Peking Union Medical College, Beijing P. R., China
| | - Siyuan Han
- Department of Radiology, Beijing Hospital, National Center of Gerontology; Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing P. R., China.,Graduate School of Peking Union Medical College, Beijing P. R., China
| | - Ming Liu
- Department of Urology, Beijing Hospital, National Center of Gerontology; Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing P. R., China
| | - Pu-Yeh Wu
- GE Healthcare, MR Research, Beijing P. R., China
| | - Wei Zhang
- Department of Pathology, Beijing Hospital, National Center of Gerontology; Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing P. R., China
| | - Jintao Zhang
- Department of Radiology, Beijing Hospital, National Center of Gerontology; Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing P. R., China
| | - Chunmei Li
- Department of Radiology, Beijing Hospital, National Center of Gerontology; Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing P. R., China
| | - Min Chen
- Department of Radiology, Beijing Hospital, National Center of Gerontology; Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing P. R., China.,Graduate School of Peking Union Medical College, Beijing P. R., China
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Lee CH. Quantitative T2-mapping using MRI for detection of prostate malignancy: a systematic review of the literature. Acta Radiol 2019; 60:1181-1189. [PMID: 30621443 DOI: 10.1177/0284185118820058] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Affiliation(s)
- Chau Hung Lee
- 1 Department of Radiology, Charite - Universitätzsmedizin Berlin, Berlin, Germany
- 2 Department of Radiology, Tan Tock Seng Hospital, Singapore
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Vidya Shankar R, Roccia E, Cruz G, Neji R, Botnar R, Prezzi D, Goh V, Prieto C, Dregely I. Accelerated 3D T 2 w-imaging of the prostate with 1-millimeter isotropic resolution in less than 3 minutes. Magn Reson Med 2019; 82:721-731. [PMID: 31006906 PMCID: PMC6563534 DOI: 10.1002/mrm.27764] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2018] [Revised: 03/15/2019] [Accepted: 03/16/2019] [Indexed: 12/29/2022]
Abstract
PURPOSE To achieve 3D T2 w imaging of the prostate with 1-mm isotropic resolution in less than 3 min. METHODS We devised and implemented a 3D T2 -prepared multishot balanced steady state free precession (T2 prep-bSSFP) acquisition sequence with a variable density undersampled trajectory combined with a total variation regularized iterative SENSE (TV-SENSE) reconstruction. Prospectively undersampled images of the prostate (acceleration factor R = 3) were acquired in 11 healthy subjects in an institutional review board-approved study. Image quality metrics (subjective signal-to-noise ratio, contrast, sharpness, and overall prostate image quality) were evaluated by 2 radiologists. Scores of the proposed accelerated sequence were compared using the Wilcoxon signed-rank and Kruskal-Wallis non-parametric tests to prostate images acquired using a fully sampled 3D T2 prep-bSSFP acquisition, and with clinical standard 2D and 3D turbo spin echo (TSE) T2 w acquisitions. A P-value < 0.05 was considered significant. RESULTS The 3× accelerated 3D T2 prep-bSSFP images required a scan time (min:s) of 2:45, while the fully sampled 3D T2 prep-bSSFP and clinical standard 3D TSE images were acquired in 8:23 and 7:29, respectively. Image quality scores (contrast, sharpness, and overall prostate image quality) of the accelerated 3D T2 prep-bSSFP, fully sampled T2 prep-bSSFP, and clinical standard 3D TSE acquisitions along all 3 spatial dimensions were not significantly different (P > 0.05). CONCLUSION 3D T2 w images of the prostate with 1-mm isotropic resolution can be acquired in less than 3 min, with image quality that is comparable to a clinical standard 3D TSE sequence but only takes a third of the acquisition time.
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Affiliation(s)
- Rohini Vidya Shankar
- School of Biomedical Engineering and Imaging SciencesKing's College LondonLondonUnited Kingdom
| | - Elisa Roccia
- School of Biomedical Engineering and Imaging SciencesKing's College LondonLondonUnited Kingdom
| | - Gastao Cruz
- School of Biomedical Engineering and Imaging SciencesKing's College LondonLondonUnited Kingdom
| | - Radhouene Neji
- School of Biomedical Engineering and Imaging SciencesKing's College LondonLondonUnited Kingdom
- MR Research Collaborations, Siemens Healthcare LimitedFrimleyUnited Kingdom
| | - René Botnar
- School of Biomedical Engineering and Imaging SciencesKing's College LondonLondonUnited Kingdom
| | - Davide Prezzi
- Department of RadiologyGuy's and St Thomas' Hospitals NHS Foundation TrustLondonUnited Kingdom
| | - Vicky Goh
- School of Biomedical Engineering and Imaging SciencesKing's College LondonLondonUnited Kingdom
- Department of RadiologyGuy's and St Thomas' Hospitals NHS Foundation TrustLondonUnited Kingdom
| | - Claudia Prieto
- School of Biomedical Engineering and Imaging SciencesKing's College LondonLondonUnited Kingdom
| | - Isabel Dregely
- School of Biomedical Engineering and Imaging SciencesKing's College LondonLondonUnited Kingdom
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Radunsky D, Blumenfeld-Katzir T, Volovyk O, Tal A, Barazany D, Tsarfaty G, Ben-Eliezer N. Analysis of magnetization transfer (MT) influence on quantitative mapping of T 2 relaxation time. Magn Reson Med 2019; 82:145-158. [PMID: 30860287 DOI: 10.1002/mrm.27704] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2018] [Revised: 01/28/2019] [Accepted: 01/30/2019] [Indexed: 12/22/2022]
Abstract
PURPOSE Multi-echo spin-echo (MESE) protocol is the most effective tool for mapping T2 relaxation in vivo. Still, MESE extensive use of radiofrequency pulses causes magnetization transfer (MT)-related bias of the water signal, instigated by the presence of macromolecules (MMP). Here, we analyze the effects of MT on MESE signal, alongside their impact on quantitative T2 measurements. METHODS Study used 3 models: in vitro urea phantom, ex vivo horse brain, and in vivo human brain. MT ratio (MTR) was measured between single-SE and MESE protocols under different scan settings including varying echo train lengths, number of slices, and inter-slice gap. MTR and T2 values were extracted for each model and protocol. RESULTS MT interactions biased MESE signals, and in certain settings, the corresponding T2 values. T2 underestimation of up to 4.3% was found versus single-SE values in vitro and up to 13.8% ex vivo, correlating with the MMP content. T2 bias originated from intra-slice saturation of the MMP, rather than from indirect saturation in multi-slice acquisitions. MT-related signal attenuation was caused by slice crosstalk and/or partial T1 recovery, whereas smaller contribution was caused by MMP interactions. Inter-slice gap had a similar effect on in vivo MTR (21.2%), in comparison to increasing the number of slices (18.9%). CONCLUSIONS MT influences MESE protocols either by uniformly attenuating the entire echo train or by cumulatively attenuating the signal along the train. Although both processes depend on scan settings and MMP content, only the latter will cause underestimation of T2 .
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Affiliation(s)
- Dvir Radunsky
- Department of Biomedical Engineering, Tel Aviv University, Tel Aviv, Israel
| | | | - Osnat Volovyk
- Department of Chemical Physics, The Weizmann Institute, Rehovot, Israel
| | - Assaf Tal
- Department of Chemical Physics, The Weizmann Institute, Rehovot, Israel
| | - Daniel Barazany
- Strauss computational neuroimaging center, Tel Aviv University, Tel Aviv, Israel
| | - Galia Tsarfaty
- Department of Diagnostic Imaging, Sheba Medical Center, Ramat Gan, Israel
| | - Noam Ben-Eliezer
- Department of Biomedical Engineering, Tel Aviv University, Tel Aviv, Israel.,Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel.,Center for Advanced Imaging Innovation and Research (CAI2R), NewYork University Langone Medical Center, New York, New York
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32
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Roccia E, Vidya Shankar R, Neji R, Cruz G, Munoz C, Botnar R, Goh V, Prieto C, Dregely I. Accelerated 3D T 2 mapping with dictionary-based matching for prostate imaging. Magn Reson Med 2019; 81:1795-1805. [PMID: 30368900 DOI: 10.1002/mrm.27540] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2018] [Revised: 08/28/2018] [Accepted: 08/28/2018] [Indexed: 01/17/2023]
Abstract
PURPOSE To develop a fast and accurate method for 3D T2 mapping of prostate cancer using undersampled acquisition and dictionary-based fitting. METHODS 3D high-resolution T2 -weighted images (0.9 × 0.9 × 3 mm3 ) were obtained with a multishot T2 -prepared balanced steady-state free precession (T2 -prep-bSSFP) acquisition sequence using a 3D variable density undersampled Cartesian trajectory. Each T2 -weighted image was reconstructed using total variation regularized sensitivity encoding. A flexible simulation framework based on extended phase graphs generated a dictionary of magnetization signals, which was customized to the proposed sequence. The dictionary was matched to the acquired T2 -weighted images to retrieve quantitative T2 values, which were then compared to gold-standard spin echo acquisition values using monoexponential fitting. The proposed approach was validated in simulations and a T1 /T2 phantom, and feasibility was tested in 8 healthy subjects. RESULTS The simulation analysis showed that the proposed T2 mapping approach is robust to noise and typically observed T1 variations. T2 values obtained in the phantom with T2 prep-bSSFP and the acquisition-specific, dictionary-based matching were highly correlated with the gold-standard spin echo method (r = 0.99). Furthermore, no differences were observed with the accelerated acquisition compared to the fully sampled acquisition (r = 0.99). T2 values obtained in prostate peripheral zone, central gland, and muscle in healthy subjects (age, 26 ± 6 years) were 97 ± 14, 76 ± 7, and 36 ± 3 ms, respectively. CONCLUSION 3D quantitative T2 mapping of the whole prostate can be achieved in 3 minutes.
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Affiliation(s)
- Elisa Roccia
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Rohini Vidya Shankar
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Radhouene Neji
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
- Siemens Healthcare Limited, Frimley, United Kingdom
| | - Gastão Cruz
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Camila Munoz
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - René Botnar
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Vicky Goh
- Cancer Imaging, King's College London, London, United Kingdom
| | - Claudia Prieto
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Isabel Dregely
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
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Sun Y, Reynolds HM, Parameswaran B, Wraith D, Finnegan ME, Williams S, Haworth A. Multiparametric MRI and radiomics in prostate cancer: a review. AUSTRALASIAN PHYSICAL & ENGINEERING SCIENCES IN MEDICINE 2019; 42:3-25. [PMID: 30762223 DOI: 10.1007/s13246-019-00730-z] [Citation(s) in RCA: 65] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/19/2018] [Accepted: 01/22/2019] [Indexed: 12/30/2022]
Abstract
Multiparametric MRI (mpMRI) is an imaging modality that combines anatomical MR imaging with one or more functional MRI sequences. It has become a versatile tool for detecting and characterising prostate cancer (PCa). The traditional role of mpMRI was confined to PCa staging, but due to the advanced imaging techniques, its role has expanded to various stages in clinical practises including tumour detection, disease monitor during active surveillance and sequential imaging for patient follow-up. Meanwhile, with the growing speed of data generation and the increasing volume of imaging data, it is highly demanded to apply computerised methods to process mpMRI data and extract useful information. Hence quantitative analysis for imaging data using radiomics has become an emerging paradigm. The application of radiomics approaches in prostate cancer has not only enabled automatic localisation of the disease but also provided a non-invasive solution to assess tumour biology (e.g. aggressiveness and the presence of hypoxia). This article reviews mpMRI and its expanding role in PCa detection, staging and patient management. Following that, an overview of prostate radiomics will be provided, with a special focus on its current applications as well as its future directions.
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Affiliation(s)
- Yu Sun
- University of Sydney, Sydney, Australia. .,Peter MacCallum Cancer Centre, Melbourne, Australia.
| | | | | | - Darren Wraith
- Queensland University of Technology, Brisbane, Australia
| | - Mary E Finnegan
- Imperial College Healthcare NHS Trust, London, UK.,Imperial College London, London, UK
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Chatterjee A, Oto A. Future Perspectives in Multiparametric Prostate MR Imaging. Magn Reson Imaging Clin N Am 2019; 27:117-130. [DOI: 10.1016/j.mric.2018.08.003] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
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Performance of T2 Maps in the Detection of Prostate Cancer. Acad Radiol 2019; 26:15-21. [PMID: 29731420 DOI: 10.1016/j.acra.2018.04.005] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2017] [Revised: 02/15/2018] [Accepted: 04/02/2018] [Indexed: 11/20/2022]
Abstract
RATIONALE AND OBJECTIVES This study compares the performance of T2 maps in the detection of prostate cancer (PCa) in comparison to T2-weighted (T2W) magnetic resonance images. MATERIALS AND METHODS The prospective study was institutional review board approved. Consenting patients (n = 45) with histologic confirmed PCa underwent preoperative 3-T magnetic resonance imaging with or without endorectal coil. Two radiologists, working independently, marked regions of interests (ROIs) on PCa lesions separately on T2W images and T2 maps. Each ROI was assigned a score of 1-5 based on the confidence in accurately detecting cancer, with 5 being the highest confidence. Subsequently, the histologically confirmed PCa lesions (n = 112) on whole-mount sections were matched with ROIs to calculate sensitivity, positive predictive value (PPV), and radiologist confidence score. Quantitative T2 values of PCa and benign tissue ROIs were measured. RESULTS Sensitivity and confidence score for PCa detection were similar for T2W images (51%, 4.5 ± 0.8) and T2 maps (52%, 4.5 ± 0.6). However, PPV was significantly higher (P = .001) for T2 maps (88%) compared to T2W (72%) images. The use of endorectal coils nominally improved sensitivity (T2W: 55 vs 47%, T2 map: 54% vs 48%) compared to the use of no endorectal coils, but not the PPV and the confidence score. Quantitative T2 values for PCa (105 ± 28 milliseconds) were significantly (P = 9.3 × 10-14) lower than benign peripheral zone tissue (211 ± 71 milliseconds), with moderate significant correlation with Gleason score (ρ = -0.284). CONCLUSIONS Our study shows that review of T2 maps by radiologists has similar sensitivity but higher PPV compared to T2W images. Additional quantitative information obtained from T2 maps is helpful in differentiating cancer from normal prostate tissue and determining its aggressiveness.
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Dregely I, Prezzi D, Kelly‐Morland C, Roccia E, Neji R, Goh V. Imaging biomarkers in oncology: Basics and application to MRI. J Magn Reson Imaging 2018; 48:13-26. [PMID: 29969192 PMCID: PMC6587121 DOI: 10.1002/jmri.26058] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2018] [Accepted: 03/26/2018] [Indexed: 12/12/2022] Open
Abstract
Cancer remains a global killer alongside cardiovascular disease. A better understanding of cancer biology has transformed its management with an increasing emphasis on a personalized approach, so-called "precision cancer medicine." Imaging has a key role to play in the management of cancer patients. Imaging biomarkers that objectively inform on tumor biology, the tumor environment, and tumor changes in response to an intervention complement genomic and molecular diagnostics. In this review we describe the key principles for imaging biomarker development and discuss the current status with respect to magnetic resonance imaging (MRI). LEVEL OF EVIDENCE 5 TECHNICAL EFFICACY: Stage 5 J. Magn. Reson. Imaging 2018;48:13-26.
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Affiliation(s)
- Isabel Dregely
- Biomedical Engineering, School of Biomedical Engineering & Imaging SciencesKing's Health Partners, St Thomas' HospitalLondon, UK
| | - Davide Prezzi
- Cancer Imaging, School of Biomedical Engineering & Imaging Sciences King's College London, King's Health Partners, St Thomas' Hospital, LondonUK
- RadiologyGuy's & St Thomas' NHS Foundation TrustLondonUK
| | - Christian Kelly‐Morland
- Cancer Imaging, School of Biomedical Engineering & Imaging Sciences King's College London, King's Health Partners, St Thomas' Hospital, LondonUK
- RadiologyGuy's & St Thomas' NHS Foundation TrustLondonUK
| | - Elisa Roccia
- Biomedical Engineering, School of Biomedical Engineering & Imaging SciencesKing's Health Partners, St Thomas' HospitalLondon, UK
| | - Radhouene Neji
- Biomedical Engineering, School of Biomedical Engineering & Imaging SciencesKing's Health Partners, St Thomas' HospitalLondon, UK
- MR Research CollaborationsSiemens HealthcareFrimleyUK
| | - Vicky Goh
- Cancer Imaging, School of Biomedical Engineering & Imaging Sciences King's College London, King's Health Partners, St Thomas' Hospital, LondonUK
- RadiologyGuy's & St Thomas' NHS Foundation TrustLondonUK
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Towards intrinsic R2* imaging in the prostate at 3 and 7 tesla. Magn Reson Imaging 2017; 42:16-21. [DOI: 10.1016/j.mri.2017.04.014] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2016] [Revised: 03/26/2017] [Accepted: 04/30/2017] [Indexed: 12/17/2022]
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van Houdt PJ, Agarwal HK, van Buuren LD, Heijmink SWTPJ, Haack S, van der Poel HG, Ghobadi G, Pos FJ, Peeters JM, Choyke PL, van der Heide UA. Performance of a fast and high-resolution multi-echo spin-echo sequence for prostate T 2 mapping across multiple systems. Magn Reson Med 2017; 79:1586-1594. [PMID: 28671331 DOI: 10.1002/mrm.26816] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2017] [Revised: 05/18/2017] [Accepted: 06/09/2017] [Indexed: 12/27/2022]
Abstract
PURPOSE To evaluate the performance of a multi-echo spin-echo sequence with k-t undersampling scheme (k-t T2 ) in prostate cancer. METHODS Phantom experiments were performed at five systems to estimate the bias, short-term repeatability, and reproducibility across all systems expressed with the within-subject coefficient of variation (wCV). Monthly measurements were performed on two systems for long-term repeatability estimation. To evaluate clinical repeatability, two T2 maps (voxel size 0.8 × 0.8 × 3 mm3 ; 5 min) were acquired at separate visits on one system for 13 prostate cancer patients. Repeatability was assessed per patient in relation to spatial resolution. T2 values were compared for tumor, peripheral zone, and transition zone. RESULTS Phantom measurements showed a small bias (median = -0.9 ms) and good short-term repeatability (median wCV = 0.5%). Long-term repeatability was 0.9 and 1.1% and reproducibility between systems was 1.7%. The median bias observed in patients was -1.1 ms. At voxel level, the median wCV was 15%, dropping to 4% for structures of 0.5 cm3 . The median tumor T2 values (79 ms) were significantly lower (P < 0.001) than in the peripheral zone (149 ms), but overlapped with the transition zone (91 ms). CONCLUSIONS Reproducible T2 mapping of the prostate is feasible with good spatial resolution in a clinically reasonable scan time, allowing reliable measurement of T2 in structures as small as 0.5 cm3 . Magn Reson Med 79:1586-1594, 2018. © 2017 International Society for Magnetic Resonance in Medicine.
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Affiliation(s)
- Petra J van Houdt
- Department of Radiation Oncology, the Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - Harsh K Agarwal
- Philips Research NA, Cambridge, Massachusetts, USA.,National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Laurens D van Buuren
- Department of Radiation Oncology, the Netherlands Cancer Institute, Amsterdam, the Netherlands
| | | | - Søren Haack
- Department of Clinical Engineering, Aarhus University Hospital, Aarhus, Denmark
| | - Henk G van der Poel
- Department of Urology, the Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - Ghazaleh Ghobadi
- Department of Radiation Oncology, the Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - Floris J Pos
- Department of Radiation Oncology, the Netherlands Cancer Institute, Amsterdam, the Netherlands
| | | | - Peter L Choyke
- National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Uulke A van der Heide
- Department of Radiation Oncology, the Netherlands Cancer Institute, Amsterdam, the Netherlands
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Siracusano G, La Corte A, Milazzo C, Anastasi GP, Finocchio G, Gaeta M. On the R 2⁎ relaxometry in complex multi-peak multi-Echo chemical shift-based water-fat quantification: Applications to the neuromuscular diseases. Magn Reson Imaging 2016; 35:4-14. [PMID: 27569370 DOI: 10.1016/j.mri.2016.08.006] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2016] [Revised: 08/03/2016] [Accepted: 08/20/2016] [Indexed: 12/31/2022]
Abstract
PURPOSE Investigation of the feasibility of the R2⁎ mapping techniques by using latest theoretical models corrected for confounding factors and optimized for signal to noise ratio. THEORY AND METHODS The improvement of the performance of state of the art magnetic resonance imaging (MRI) relaxometry algorithms is challenging because of a non-negligible bias and still unresolved numerical instabilities. Here, R2⁎ mapping reconstructions, including complex fitting with multi-spectral fat-correction by using single-decay and double-decay formulation, are deeply studied in order to investigate and identify optimal configuration parameters and minimize the occurrence of numerical artifacts. The effects of echo number, echo spacing, and fat/water relaxation model type are evaluated through both simulated and in-vivo data. We also explore the stability and feasibility of the fat/water relaxation model by analyzing the impact of high percentage of fat infiltrations and local transverse relaxation differences among biological species. RESULTS The main limits of the MRI relaxometry are the presence of bias and the occurrence of artifacts, which significantly affect its accuracy. Chemical-shift complex R2⁎-correct single-decay reconstructions exhibit a large bias in presence of a significant difference in the relaxation rates of fat and water and with fat concentration larger than 30%. We find that for fat-dominated tissues or in patients affected by extensive iron deposition, MRI reconstructions accounting for multi-exponential relaxation time provide accurate R2⁎ measurements and are less prone to numerical artifacts. CONCLUSIONS Complex fitting and fat-correction with multi-exponential decay formulation outperforms the conventional single-decay approximation in various diagnostic scenarios. Although it still lacks of numerical stability, which requires model enhancement and support from spectroscopy, it offers promising perspectives for the development of relaxometry as a reliable tool to improve tissue characterization and monitoring of neuromuscular disorders.
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Affiliation(s)
- Giulio Siracusano
- Department of Mathematical and Computer Sciences, Physical Sciences and Earth Sciences, University of Messina, V.le F. D'alcontres, 31, 98166, Messina, Italy; Department of Computer Engineering and Telecommunications, University of Catania, Viale Andrea Doria 6, 95125, Catania, Italy.
| | - Aurelio La Corte
- Department of Computer Engineering and Telecommunications, University of Catania, Viale Andrea Doria 6, 95125, Catania, Italy
| | - Carmelo Milazzo
- Department of Biomedical sciences, Dental and of Morphological and Functional images, University of Messina, Via Consolare Valeria 1, 98125, Messina, Italy
| | - Giuseppe Pio Anastasi
- Department of Biomedical sciences, Dental and of Morphological and Functional images, University of Messina, Via Consolare Valeria 1, 98125, Messina, Italy
| | - Giovanni Finocchio
- Department of Mathematical and Computer Sciences, Physical Sciences and Earth Sciences, University of Messina, V.le F. D'alcontres, 31, 98166, Messina, Italy; Istituto Nazionale di Geofisica e Vulcanologia (INGV), Via Vigna Murata 605, 00143, Roma, Italy
| | - Michele Gaeta
- Department of Biomedical sciences, Dental and of Morphological and Functional images, University of Messina, Via Consolare Valeria 1, 98125, Messina, Italy
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Liu L, Tian Z, Zhang Z, Fei B. Computer-aided Detection of Prostate Cancer with MRI: Technology and Applications. Acad Radiol 2016; 23:1024-46. [PMID: 27133005 PMCID: PMC5355004 DOI: 10.1016/j.acra.2016.03.010] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2015] [Revised: 03/18/2016] [Accepted: 03/21/2016] [Indexed: 01/10/2023]
Abstract
One in six men will develop prostate cancer in his lifetime. Early detection and accurate diagnosis of the disease can improve cancer survival and reduce treatment costs. Recently, imaging of prostate cancer has greatly advanced since the introduction of multiparametric magnetic resonance imaging (mp-MRI). Mp-MRI consists of T2-weighted sequences combined with functional sequences including dynamic contrast-enhanced MRI, diffusion-weighted MRI, and magnetic resonance spectroscopy imaging. Because of the big data and variations in imaging sequences, detection can be affected by multiple factors such as observer variability and visibility and complexity of the lesions. To improve quantitative assessment of the disease, various computer-aided detection systems have been designed to help radiologists in their clinical practice. This review paper presents an overview of literatures on computer-aided detection of prostate cancer with mp-MRI, which include the technology and its applications. The aim of the survey is threefold: an introduction for those new to the field, an overview for those working in the field, and a reference for those searching for literature on a specific application.
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Affiliation(s)
- Lizhi Liu
- Department of Radiology and Imaging Sciences, Emory University School of Medicine, 1841 Clifton Road NE, Atlanta, GA 30329; Center of Medical Imaging and Image-guided Therapy, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology Collaborative Innovation Center for Cancer Medicine, 651 Dongfeng Road East, Guangzhou, 510060, China
| | - Zhiqiang Tian
- Department of Radiology and Imaging Sciences, Emory University School of Medicine, 1841 Clifton Road NE, Atlanta, GA 30329
| | - Zhenfeng Zhang
- Center of Medical Imaging and Image-guided Therapy, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology Collaborative Innovation Center for Cancer Medicine, 651 Dongfeng Road East, Guangzhou, 510060, China
| | - Baowei Fei
- Department of Radiology and Imaging Sciences, Emory University School of Medicine, 1841 Clifton Road NE, Atlanta, GA 30329; Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, 1841 Clifton Road NE, Atlanta, Georgia 30329; Winship Cancer Institute of Emory University, 1841 Clifton Road NE, Atlanta, Georgia 30329.
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Ciris PA, Balasubramanian M, Seethamraju RT, Tokuda J, Scalera J, Penzkofer T, Fennessy FM, Tempany-Afdhal CM, Tuncali K, Mulkern RV. Characterization of gradient echo signal decays in healthy and cancerous prostate at 3T improves with a Gaussian augmentation of the mono-exponential (GAME) model. NMR IN BIOMEDICINE 2016; 29:999-1009. [PMID: 27241215 PMCID: PMC4957529 DOI: 10.1002/nbm.3556] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/20/2015] [Revised: 04/11/2016] [Accepted: 04/12/2016] [Indexed: 05/06/2023]
Abstract
A biomarker of cancer aggressiveness, such as hypoxia, could substantially impact treatment decisions in the prostate, especially radiation therapy, by balancing treatment morbidity (urinary incontinence, erectile dysfunction, etc.) against mortality. R2 (*) mapping with Mono-Exponential (ME) decay modeling has shown potential for identifying areas of prostate cancer hypoxia at 1.5T. However, Gaussian deviations from ME decay have been observed in other tissues at 3T. The purpose of this study is to assess whether gradient-echo signal decays are better characterized by a standard ME decay model, or a Gaussian Augmentation of the Mono-Exponential (GAME) decay model, in the prostate at 3T. Multi-gradient-echo signals were acquired on 20 consecutive patients with a clinical suspicion of prostate cancer undergoing MR-guided prostate biopsies. Data were fitted with both ME and GAME models. The information contents of these models were compared using Akaike's information criterion (second order, AICC ), in skeletal muscle, the prostate central gland (CG), and peripheral zone (PZ) regions of interest (ROIs). The GAME model had higher information content in 30% of the prostate on average (across all patients and ROIs), covering up to 67% of cancerous PZ ROIs, and up to 100% of cancerous CG ROIs (in individual patients). The higher information content of GAME became more prominent in regions that would be assumed hypoxic using ME alone, reaching 50% of the PZ and 70% of the CG as ME R2 (*) approached 40 s(-1) . R2 (*) mapping may have important applications in MRI; however, information lost due to modeling could mask differences in parameters due to underlying tissue anatomy or physiology. The GAME model improves characterization of signal behavior in the prostate at 3T, and may increase the potential for determining correlates of fit parameters with biomarkers, for example of oxygenation status.
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Affiliation(s)
- Pelin Aksit Ciris
- Department of Biomedical Engineering, Akdeniz University, Antalya, Turkey
- Harvard Medical School, Boston, MA, USA
- Brigham and Women's Hospital, Boston, MA, USA
| | | | | | - Junichi Tokuda
- Harvard Medical School, Boston, MA, USA
- Brigham and Women's Hospital, Boston, MA, USA
| | - Jonathan Scalera
- Harvard Medical School, Boston, MA, USA
- Brigham and Women's Hospital, Boston, MA, USA
| | - Tobias Penzkofer
- Harvard Medical School, Boston, MA, USA
- Brigham and Women's Hospital, Boston, MA, USA
- Charité Universitätsmedizin Berlin, Berlin, Germany
| | - Fiona M Fennessy
- Harvard Medical School, Boston, MA, USA
- Brigham and Women's Hospital, Boston, MA, USA
- Dana-Farber Cancer Institute, MA, USA
| | | | - Kemal Tuncali
- Harvard Medical School, Boston, MA, USA
- Brigham and Women's Hospital, Boston, MA, USA
| | - Robert V Mulkern
- Harvard Medical School, Boston, MA, USA
- Boston Children's Hospital, Boston, MA, USA
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Bojorquez JZ, Bricq S, Brunotte F, Walker PM, Lalande A. A novel alternative to classify tissues from T 1 and T 2 relaxation times for prostate MRI. MAGNETIC RESONANCE MATERIALS IN PHYSICS BIOLOGY AND MEDICINE 2016; 29:777-88. [PMID: 27160300 DOI: 10.1007/s10334-016-0562-3] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/01/2016] [Revised: 04/12/2016] [Accepted: 04/22/2016] [Indexed: 11/24/2022]
Abstract
OBJECTIVE To segment and classify the different attenuation regions from MRI at the pelvis level using the T 1 and T 2 relaxation times and anatomical knowledge as a first step towards the creation of PET/MR attenuation maps. MATERIALS AND METHODS Relaxation times were calculated by fitting the pixel-wise intensities of acquired T 1- and T 2-weighted images from eight men with inversion-recovery and multi-echo multi-slice spin-echo sequences. A decision binary tree based on relaxation times was implemented to segment and classify fat, muscle, prostate, and air (within the body). Connected component analysis and an anatomical knowledge-based procedure were implemented to localize the background and bone. RESULTS Relaxation times at 3 T are reported for fat (T 1 = 385 ms, T 2 = 121 ms), muscle (T 1 = 1295 ms, T 2 = 40 ms), and prostate (T 1 = 1700 ms, T 2 = 80 ms). The relaxation times allowed the segmentation-classification of fat, prostate, muscle, and air, and combined with anatomical knowledge, they allowed classification of bone. The good segmentation-classification of prostate [mean Dice similarity score (mDSC) = 0.70] suggests a viable implementation in oncology and that of fat (mDSC = 0.99), muscle (mDSC = 0.99), and bone (mDSCs = 0.78) advocates for its implementation in PET/MR attenuation correction. CONCLUSION Our method allows the segmentation and classification of the attenuation-relevant structures required for the generation of the attenuation map of PET/MR systems in prostate imaging: air, background, bone, fat, muscle, and prostate.
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Affiliation(s)
- Jorge Zavala Bojorquez
- LE2I, UMR 6306, CNRS, Arts et Métiers, Université Bourgogne Franche-Comté, 21000, Dijon, France.
| | - Stéphanie Bricq
- LE2I, UMR 6306, CNRS, Arts et Métiers, Université Bourgogne Franche-Comté, 21000, Dijon, France
| | - François Brunotte
- LE2I, UMR 6306, CNRS, Arts et Métiers, Université Bourgogne Franche-Comté, 21000, Dijon, France
| | - Paul M Walker
- LE2I, UMR 6306, CNRS, Arts et Métiers, Université Bourgogne Franche-Comté, 21000, Dijon, France
| | - Alain Lalande
- LE2I, UMR 6306, CNRS, Arts et Métiers, Université Bourgogne Franche-Comté, 21000, Dijon, France
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Gupta RT, Spilseth B, Patel N, Brown AF, Yu J. Multiparametric prostate MRI: focus on T2-weighted imaging and role in staging of prostate cancer. Abdom Radiol (NY) 2016; 41:831-43. [PMID: 27193786 DOI: 10.1007/s00261-015-0579-5] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
Multiparametric MRI (mpMRI) represents a growing modality for the non-invasive evaluation of prostate cancer (PCa) and is increasingly being used for patients with persistently elevated PSA and prior negative biopsies, for monitoring patients in active surveillance protocols, for preoperative characterization of cancer for surgical planning, and in planning for MRI-targeted biopsy. The focus of this work is twofold. First, we review the key role of T2-weighted imaging (T2WI) in mpMRI, specifically outlining how it is used for anatomic evaluation of the prostate, detection of clinically significant PCa, assessment of extraprostatic extension (EPE), and mimics of PCa on this sequence. We will also discuss optimal technical acquisition parameters for this sequence and recent technical advancements in T2WI. Second, we will delineate the role that mpMRI plays in the staging of PCa and describe the implications of the information that mpMRI can provide in determining the most appropriate management plan for the patient with PCa.
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Hoang Dinh A, Melodelima C, Souchon R, Lehaire J, Bratan F, Mège-Lechevallier F, Ruffion A, Crouzet S, Colombel M, Rouvière O. Quantitative Analysis of Prostate Multiparametric MR Images for Detection of Aggressive Prostate Cancer in the Peripheral Zone: A Multiple Imager Study. Radiology 2016; 280:117-27. [PMID: 26859255 DOI: 10.1148/radiol.2016151406] [Citation(s) in RCA: 54] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/29/2023]
Abstract
Purpose To assess the intermanufacturer variability of quantitative models in discriminating cancers with a Gleason score of at least 7 among peripheral zone (PZ) lesions seen at 3-T multiparametric magnetic resonance (MR) imaging. Materials and Methods An institutional review board-approved prospective database of 257 patients who gave written consent and underwent T2-weighted, diffusion-weighted, and dynamic contrast material-enhanced imaging before prostatectomy was retrospectively reviewed. It contained outlined lesions found to be suspicious for malignancy by two independent radiologists and classified as malignant or benign after correlation with prostatectomy whole-mount specimens. One hundred six patients who underwent imaging with 3-T MR systems from two manufacturers were selected (data set A, n = 72; data set B, n = 34). Eleven parameters were calculated in PZ lesions: normalized T2-weighted signal intensity, skewness and kurtosis of T2-weighted signal intensity, T2 value, wash-in rate, washout rate, time to peak (TTP), mean apparent diffusion coefficient (ADC), 10th percentile of the ADC, and skewness and kurtosis of the histogram of the ADC values. Parameters were selected on the basis of their specificity for a sensitivity of 0.95 in diagnosing cancers with a Gleason score of at least 7, and the area under the receiver operating characteristic curve (AUC) for the models was calculated. Results The model of the 10th percentile of the ADC with TTP yielded the highest AUC in both data sets. In data set A, the AUC was 0.90 (95% confidence interval [CI]: 0.85, 0.95) or 0.89 (95% CI: 0.82, 0.94) when it was trained in data set A or B, respectively. In data set B, the AUC was 0.84 (95% CI: 0.74, 0.94) or 0.86 (95% CI: 0.76, 0.95) when it was trained in data set A or B, respectively. No third variable added significantly independent information in any data set. Conclusion The model of the 10th percentile of the ADC with TTP yielded accurate results in discriminating cancers with a Gleason score of at least 7 among PZ lesions at 3 T in data from two manufacturers. (©) RSNA, 2016 Online supplemental material is available for this article.
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Affiliation(s)
- Au Hoang Dinh
- From INSERM, U1032, LabTau, Lyon, France (A.H.D., R.S., J.L., F.B., S.C., O.R.); CNRS, UMR 5553, BP 53, Grenoble, France (C.M.); Laboratoire d'Ecologie Alpine, Université Joseph Fourier, Grenoble, France (C.M.); Department of Urinary and Vascular Imaging (F.B., O.R.), Department of Pathology (F.M.L.), and Department of Urology (S.C., M.C.), Hospices Civils de Lyon, Hôpital Edouard Herriot, Pavillon P Radio, 5 place d'Arsonval, Lyon 69003, France; Université Lyon 1, Faculté de Médecine Lyon Est, Lyon, France (F.B., S.C., M.C., O.R.); and Department of Urology, Hospices Civils de Lyon, Centre Hospitalier Lyon Sud, Pierre Bénite, France (A.R.)
| | - Christelle Melodelima
- From INSERM, U1032, LabTau, Lyon, France (A.H.D., R.S., J.L., F.B., S.C., O.R.); CNRS, UMR 5553, BP 53, Grenoble, France (C.M.); Laboratoire d'Ecologie Alpine, Université Joseph Fourier, Grenoble, France (C.M.); Department of Urinary and Vascular Imaging (F.B., O.R.), Department of Pathology (F.M.L.), and Department of Urology (S.C., M.C.), Hospices Civils de Lyon, Hôpital Edouard Herriot, Pavillon P Radio, 5 place d'Arsonval, Lyon 69003, France; Université Lyon 1, Faculté de Médecine Lyon Est, Lyon, France (F.B., S.C., M.C., O.R.); and Department of Urology, Hospices Civils de Lyon, Centre Hospitalier Lyon Sud, Pierre Bénite, France (A.R.)
| | - Rémi Souchon
- From INSERM, U1032, LabTau, Lyon, France (A.H.D., R.S., J.L., F.B., S.C., O.R.); CNRS, UMR 5553, BP 53, Grenoble, France (C.M.); Laboratoire d'Ecologie Alpine, Université Joseph Fourier, Grenoble, France (C.M.); Department of Urinary and Vascular Imaging (F.B., O.R.), Department of Pathology (F.M.L.), and Department of Urology (S.C., M.C.), Hospices Civils de Lyon, Hôpital Edouard Herriot, Pavillon P Radio, 5 place d'Arsonval, Lyon 69003, France; Université Lyon 1, Faculté de Médecine Lyon Est, Lyon, France (F.B., S.C., M.C., O.R.); and Department of Urology, Hospices Civils de Lyon, Centre Hospitalier Lyon Sud, Pierre Bénite, France (A.R.)
| | - Jérôme Lehaire
- From INSERM, U1032, LabTau, Lyon, France (A.H.D., R.S., J.L., F.B., S.C., O.R.); CNRS, UMR 5553, BP 53, Grenoble, France (C.M.); Laboratoire d'Ecologie Alpine, Université Joseph Fourier, Grenoble, France (C.M.); Department of Urinary and Vascular Imaging (F.B., O.R.), Department of Pathology (F.M.L.), and Department of Urology (S.C., M.C.), Hospices Civils de Lyon, Hôpital Edouard Herriot, Pavillon P Radio, 5 place d'Arsonval, Lyon 69003, France; Université Lyon 1, Faculté de Médecine Lyon Est, Lyon, France (F.B., S.C., M.C., O.R.); and Department of Urology, Hospices Civils de Lyon, Centre Hospitalier Lyon Sud, Pierre Bénite, France (A.R.)
| | - Flavie Bratan
- From INSERM, U1032, LabTau, Lyon, France (A.H.D., R.S., J.L., F.B., S.C., O.R.); CNRS, UMR 5553, BP 53, Grenoble, France (C.M.); Laboratoire d'Ecologie Alpine, Université Joseph Fourier, Grenoble, France (C.M.); Department of Urinary and Vascular Imaging (F.B., O.R.), Department of Pathology (F.M.L.), and Department of Urology (S.C., M.C.), Hospices Civils de Lyon, Hôpital Edouard Herriot, Pavillon P Radio, 5 place d'Arsonval, Lyon 69003, France; Université Lyon 1, Faculté de Médecine Lyon Est, Lyon, France (F.B., S.C., M.C., O.R.); and Department of Urology, Hospices Civils de Lyon, Centre Hospitalier Lyon Sud, Pierre Bénite, France (A.R.)
| | - Florence Mège-Lechevallier
- From INSERM, U1032, LabTau, Lyon, France (A.H.D., R.S., J.L., F.B., S.C., O.R.); CNRS, UMR 5553, BP 53, Grenoble, France (C.M.); Laboratoire d'Ecologie Alpine, Université Joseph Fourier, Grenoble, France (C.M.); Department of Urinary and Vascular Imaging (F.B., O.R.), Department of Pathology (F.M.L.), and Department of Urology (S.C., M.C.), Hospices Civils de Lyon, Hôpital Edouard Herriot, Pavillon P Radio, 5 place d'Arsonval, Lyon 69003, France; Université Lyon 1, Faculté de Médecine Lyon Est, Lyon, France (F.B., S.C., M.C., O.R.); and Department of Urology, Hospices Civils de Lyon, Centre Hospitalier Lyon Sud, Pierre Bénite, France (A.R.)
| | - Alain Ruffion
- From INSERM, U1032, LabTau, Lyon, France (A.H.D., R.S., J.L., F.B., S.C., O.R.); CNRS, UMR 5553, BP 53, Grenoble, France (C.M.); Laboratoire d'Ecologie Alpine, Université Joseph Fourier, Grenoble, France (C.M.); Department of Urinary and Vascular Imaging (F.B., O.R.), Department of Pathology (F.M.L.), and Department of Urology (S.C., M.C.), Hospices Civils de Lyon, Hôpital Edouard Herriot, Pavillon P Radio, 5 place d'Arsonval, Lyon 69003, France; Université Lyon 1, Faculté de Médecine Lyon Est, Lyon, France (F.B., S.C., M.C., O.R.); and Department of Urology, Hospices Civils de Lyon, Centre Hospitalier Lyon Sud, Pierre Bénite, France (A.R.)
| | - Sébastien Crouzet
- From INSERM, U1032, LabTau, Lyon, France (A.H.D., R.S., J.L., F.B., S.C., O.R.); CNRS, UMR 5553, BP 53, Grenoble, France (C.M.); Laboratoire d'Ecologie Alpine, Université Joseph Fourier, Grenoble, France (C.M.); Department of Urinary and Vascular Imaging (F.B., O.R.), Department of Pathology (F.M.L.), and Department of Urology (S.C., M.C.), Hospices Civils de Lyon, Hôpital Edouard Herriot, Pavillon P Radio, 5 place d'Arsonval, Lyon 69003, France; Université Lyon 1, Faculté de Médecine Lyon Est, Lyon, France (F.B., S.C., M.C., O.R.); and Department of Urology, Hospices Civils de Lyon, Centre Hospitalier Lyon Sud, Pierre Bénite, France (A.R.)
| | - Marc Colombel
- From INSERM, U1032, LabTau, Lyon, France (A.H.D., R.S., J.L., F.B., S.C., O.R.); CNRS, UMR 5553, BP 53, Grenoble, France (C.M.); Laboratoire d'Ecologie Alpine, Université Joseph Fourier, Grenoble, France (C.M.); Department of Urinary and Vascular Imaging (F.B., O.R.), Department of Pathology (F.M.L.), and Department of Urology (S.C., M.C.), Hospices Civils de Lyon, Hôpital Edouard Herriot, Pavillon P Radio, 5 place d'Arsonval, Lyon 69003, France; Université Lyon 1, Faculté de Médecine Lyon Est, Lyon, France (F.B., S.C., M.C., O.R.); and Department of Urology, Hospices Civils de Lyon, Centre Hospitalier Lyon Sud, Pierre Bénite, France (A.R.)
| | - Olivier Rouvière
- From INSERM, U1032, LabTau, Lyon, France (A.H.D., R.S., J.L., F.B., S.C., O.R.); CNRS, UMR 5553, BP 53, Grenoble, France (C.M.); Laboratoire d'Ecologie Alpine, Université Joseph Fourier, Grenoble, France (C.M.); Department of Urinary and Vascular Imaging (F.B., O.R.), Department of Pathology (F.M.L.), and Department of Urology (S.C., M.C.), Hospices Civils de Lyon, Hôpital Edouard Herriot, Pavillon P Radio, 5 place d'Arsonval, Lyon 69003, France; Université Lyon 1, Faculté de Médecine Lyon Est, Lyon, France (F.B., S.C., M.C., O.R.); and Department of Urology, Hospices Civils de Lyon, Centre Hospitalier Lyon Sud, Pierre Bénite, France (A.R.)
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Dregely I, Margolis DAJ, Sung K, Zhou Z, Rangwala N, Raman SS, Wu HH. Rapid quantitative T2mapping of the prostate using three-dimensional dual echo steady state MRI at 3T. Magn Reson Med 2016; 76:1720-1729. [DOI: 10.1002/mrm.26053] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2015] [Revised: 10/22/2015] [Accepted: 10/23/2015] [Indexed: 11/10/2022]
Affiliation(s)
- Isabel Dregely
- Department of Radiological Sciences; University of California; Los Angeles California USA
| | - Daniel A. J. Margolis
- Department of Radiological Sciences; University of California; Los Angeles California USA
| | - Kyunghyun Sung
- Department of Radiological Sciences; University of California; Los Angeles California USA
| | - Ziwu Zhou
- Department of Radiological Sciences; University of California; Los Angeles California USA
| | - Novena Rangwala
- Department of Radiological Sciences; University of California; Los Angeles California USA
| | - Steven S. Raman
- Department of Radiological Sciences; University of California; Los Angeles California USA
| | - Holden H. Wu
- Department of Radiological Sciences; University of California; Los Angeles California USA
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Lee D, Jin KH, Kim EY, Park SH, Ye JC. Acceleration of MR parameter mapping using annihilating filter-based low rank hankel matrix (ALOHA). Magn Reson Med 2016; 76:1848-1864. [PMID: 26728777 DOI: 10.1002/mrm.26081] [Citation(s) in RCA: 67] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2015] [Revised: 10/20/2015] [Accepted: 11/19/2015] [Indexed: 01/04/2023]
Abstract
PURPOSE MR parameter mapping is one of clinically valuable MR imaging techniques. However, increased scan time makes it difficult for routine clinical use. This article aims at developing an accelerated MR parameter mapping technique using annihilating filter based low-rank Hankel matrix approach (ALOHA). THEORY When a dynamic sequence can be sparsified using spatial wavelet and temporal Fourier transform, this results in a rank-deficient Hankel structured matrix that is constructed using weighted k-t measurements. ALOHA then utilizes the low rank matrix completion algorithm combined with a multiscale pyramidal decomposition to estimate the missing k-space data. METHODS Spin-echo inversion recovery and multiecho spin echo pulse sequences for T1 and T2 mapping, respectively, were redesigned to perform undersampling along the phase encoding direction according to Gaussian distribution. The missing k-space is reconstructed using ALOHA. Then, the parameter maps were constructed using nonlinear regression. RESULTS Experimental results confirmed that ALOHA outperformed the existing compressed sensing algorithms. Compared with the existing methods, the reconstruction errors appeared scattered throughout the entire images rather than exhibiting systematic distortion along edges and the parameter maps. CONCLUSION Given that many diagnostic errors are caused by the systematic distortion of images, ALOHA may have a great potential for clinical applications. Magn Reson Med 76:1848-1864, 2016. © 2016 International Society for Magnetic Resonance in Medicine.
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Affiliation(s)
- Dongwook Lee
- Department of Bio and Brain Engineering, Korea Advanced Institute of Science & Technology (KAIST), 373-1 Guseong-dong Yuseong-gu, Daejon, 305-701, Republic of Korea
| | - Kyong Hwan Jin
- Department of Bio and Brain Engineering, Korea Advanced Institute of Science & Technology (KAIST), 373-1 Guseong-dong Yuseong-gu, Daejon, 305-701, Republic of Korea
| | - Eung Yeop Kim
- Department of Radiology, Gachon University Gil Medical Center, 21 Namdong-daero 774beon-gil, Namdong-gu, Incheon 21565, Republic of Korea
| | - Sung-Hong Park
- Department of Bio and Brain Engineering, Korea Advanced Institute of Science & Technology (KAIST), 373-1 Guseong-dong Yuseong-gu, Daejon, 305-701, Republic of Korea
| | - Jong Chul Ye
- Department of Bio and Brain Engineering, Korea Advanced Institute of Science & Technology (KAIST), 373-1 Guseong-dong Yuseong-gu, Daejon, 305-701, Republic of Korea
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Ben-Eliezer N, Sodickson DK, Shepherd T, Wiggins GC, Block KT. Accelerated and motion-robust in vivo T2 mapping from radially undersampled data using bloch-simulation-based iterative reconstruction. Magn Reson Med 2015; 75:1346-54. [PMID: 25891292 DOI: 10.1002/mrm.25558] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2014] [Revised: 11/04/2014] [Accepted: 11/11/2014] [Indexed: 11/09/2022]
Abstract
PURPOSE Development of a quantitative transverse relaxation time (T2)-mapping platform that operates at clinically feasible timescales by employing advanced image reconstruction of radially undersampled multi spin-echo (MSE) datasets. METHODS Data was acquired on phantom and in vivo at 3 Tesla using MSE protocols employing radial k-space sampling trajectories. In order to overcome the nontrivial spin evolution associated with MSE protocols, a numerical signal model was precalculated based on Bloch simulations of the actual pulse-sequence scheme used in the acquisition process. This signal model was subsequently incorporated into an iterative model-based image reconstruction process, producing T2 and proton-density maps. RESULTS T2 maps of phantom and in vivo brain were successfully constructed, closely matching values produced by a single spin-echo reference scan. High-resolution mapping was also performed for the spinal cord in vivo, differentiating the underlying gray/white matter morphology. CONCLUSION The presented MSE data-processing framework offers reliable mapping of T2 relaxation values in a ∼ 5-minute timescale, free of user- and scanner-dependent variations. The use of radial k-space sampling provides further advantages in the form of high immunity to irregular physiological motion, as well as enhanced spatial resolutions, owing to its inherent ability to perform alias-free limited field-of-view imaging.
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Affiliation(s)
- Noam Ben-Eliezer
- The Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, New York, USA
| | - Daniel K Sodickson
- The Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, New York, USA
| | - Timothy Shepherd
- The Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, New York, USA
| | - Graham C Wiggins
- The Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, New York, USA
| | - Kai Tobias Block
- The Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, New York, USA
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Jambor I, Pesola M, Taimen P, Merisaari H, Boström PJ, Minn H, Liimatainen T, Aronen HJ. Rotating frame relaxation imaging of prostate cancer: Repeatability, cancer detection, and Gleason score prediction. Magn Reson Med 2015; 75:337-44. [PMID: 25733132 DOI: 10.1002/mrm.25647] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2014] [Revised: 12/08/2014] [Accepted: 01/12/2015] [Indexed: 12/31/2022]
Abstract
PURPOSE To investigate relaxation along a fictitious field (RAFF) and continuous wave (cw) T1ρ imaging of prostate cancer (PCa) in the terms of repeatability, PCa detection, and characterization. METHODS Thirty-six patients (PSA 11.6 ± 7.6 ng/mL, mean ± standard deviation) with histologically confirmed PCa underwent two repeated 3T MR examinations using surface array coils before prostatectomy. Relaxation along fictitious field, cw T1ρ, and T2 relaxation times (TRAFF, T1ρcw, T2) were measured and averaged over regions of interest placed in PCa, normal peripheral zone (PZ), and normal central gland (CG) positioned using whole-mount prostatectomy sections and anatomical T2-weighted images. Receiver operating characteristic curve analysis with area under the curve (AUC) was calculated to distinguish PCa from PZ/CG and PCa with Gleason score (GS) of 3+3 from GS of 3+4/≥ 3+4. RESULTS TRAFF and T1ρcw relaxation times were repeatable with coefficients of repeatability as a percentage of median value in the range of 7.8-23.2%. AUC (mean, 95% confidence interval) in the differentiation of PCa with GS of 3+3 from PCa with CS of ≥ 3+4 were 0.88 (0.72-0.99), 0.69 (0.46-0.90), and 0.68 (0.45-0.88), for TRAFF, T1ρcw, and T2, respectively. CONCLUSION In quantitative region of interest based analysis, TRAFF outperformed T1ρcw and T2 in PCa detection and characterization.
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Affiliation(s)
- Ivan Jambor
- Department of Diagnostic Radiology, University of Turku, Turku, Finland
| | - Marko Pesola
- Department of Diagnostic Radiology, University of Turku, Turku, Finland
| | - Pekka Taimen
- Department of Pathology, University of Turku and Turku University Hospital, Turku, Finland
| | - Harri Merisaari
- Department of Information Technology, University of Turku, Turku, Finland.,Turku PET Centre, University of Turku, Turku, Finland
| | - Peter J Boström
- Department of Surgery, Division of Urology, Turku University Hospital, Turku, Finland
| | - Heikki Minn
- Department of Oncology and Radiotherapy, Turku University Hospital, Turku, Finland
| | - Timo Liimatainen
- Department of Biotechnology and Molecular Medicine, A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Hannu J Aronen
- Department of Diagnostic Radiology, University of Turku, Turku, Finland.,Medical Imaging Centre of Southwest Finland, Turku University Hospital, Turku, Finland
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Lemaître G, Martí R, Freixenet J, Vilanova JC, Walker PM, Meriaudeau F. Computer-Aided Detection and diagnosis for prostate cancer based on mono and multi-parametric MRI: a review. Comput Biol Med 2015; 60:8-31. [PMID: 25747341 DOI: 10.1016/j.compbiomed.2015.02.009] [Citation(s) in RCA: 121] [Impact Index Per Article: 13.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2014] [Revised: 02/11/2015] [Accepted: 02/12/2015] [Indexed: 12/30/2022]
Abstract
Prostate cancer is the second most diagnosed cancer of men all over the world. In the last few decades, new imaging techniques based on Magnetic Resonance Imaging (MRI) have been developed to improve diagnosis. In practise, diagnosis can be affected by multiple factors such as observer variability and visibility and complexity of the lesions. In this regard, computer-aided detection and computer-aided diagnosis systems have been designed to help radiologists in their clinical practice. Research on computer-aided systems specifically focused for prostate cancer is a young technology and has been part of a dynamic field of research for the last 10 years. This survey aims to provide a comprehensive review of the state-of-the-art in this lapse of time, focusing on the different stages composing the work-flow of a computer-aided system. We also provide a comparison between studies and a discussion about the potential avenues for future research. In addition, this paper presents a new public online dataset which is made available to the research community with the aim of providing a common evaluation framework to overcome some of the current limitations identified in this survey.
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Affiliation(s)
- Guillaume Lemaître
- LE2I-UMR CNRS 6306, Université de Bourgogne, 12 rue de la Fonderie, 71200 Le Creusot, France; ViCOROB, Universitat de Girona, Campus Montilivi, Edifici P4, 17071 Girona, Spain.
| | - Robert Martí
- ViCOROB, Universitat de Girona, Campus Montilivi, Edifici P4, 17071 Girona, Spain.
| | - Jordi Freixenet
- ViCOROB, Universitat de Girona, Campus Montilivi, Edifici P4, 17071 Girona, Spain.
| | - Joan C Vilanova
- Department of Magnetic Resonance, Clínica Girona, Lorenzana 36, 17002 Girona, Spain
| | - Paul M Walker
- LE2I-UMR CNRS 6306, Université de Bourgogne, Avenue Alain Savary, 21000 Dijon, France.
| | - Fabrice Meriaudeau
- LE2I-UMR CNRS 6306, Université de Bourgogne, 12 rue de la Fonderie, 71200 Le Creusot, France.
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50
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Yamauchi FI, Penzkofer T, Fedorov A, Fennessy FM, Chu R, Maier SE, Tempany CMC, Mulkern RV, Panych LP. Prostate cancer discrimination in the peripheral zone with a reduced field-of-view T(2)-mapping MRI sequence. Magn Reson Imaging 2015; 33:525-30. [PMID: 25687187 DOI: 10.1016/j.mri.2015.02.006] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2014] [Revised: 01/15/2015] [Accepted: 02/08/2015] [Indexed: 10/24/2022]
Abstract
OBJECTIVES To evaluate the performance of T2 mapping in discriminating prostate cancer from normal prostate tissue in the peripheral zone using a practical reduced field-of-view MRI sequence requiring less than 3 minutes of scan time. MATERIALS AND METHODS Thirty-six patients with biopsy-proven peripheral zone prostate cancer without prior treatment underwent routine multiparametric MRI at 3.0T with an endorectal coil. An Inner-Volume Carr-Purcell-Meiboom-Gill imaging sequence that required 2.8 minutes to obtain data for quantitative T2 mapping covering the entire prostate gland was added to the routine multiparametric protocol. Suspected cancer (SC) and suspected healthy (SH) tissue in the peripheral zone were identified in consensus by three radiologists and were correlated with available biopsy results. Differences in mean T2 values in SC and SH regions-of-interest (ROIs) were tested for significance using unpaired Student's two-tailed t-test. The area under the receiver operating characteristic curve was used to assess the optimal threshold T2 value for cancer discrimination. RESULTS ROI analyses revealed significantly (p<0.0001) shorter T2 values in SC (85.4±12.3ms) compared to SH (169.6±38.7ms). An estimated T2 threshold of 99ms yielded a sensitivity of 92% and a specificity of 97% for prostate cancer discrimination. CONCLUSIONS Quantitative values derived from this clinically practical T2-mapping sequence allow high precision discrimination between healthy and cancerous peripheral zone in the prostate.
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Affiliation(s)
- Fernando I Yamauchi
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA; Instituto de Radiologia do Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo, São Paulo, SP, Brazil
| | - Tobias Penzkofer
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA; Department of Radiology, Charité Universitätsmedizin Berlin, Berlin, Germany
| | - Andriy Fedorov
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Fiona M Fennessy
- Department of Imaging, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA
| | - Renxin Chu
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Stephan E Maier
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA; Department of Radiology, Sahlgrenska University Hospital, Gothenburg University, Gothenburg, Sweden
| | - Clare M C Tempany
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Robert V Mulkern
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA; Department of Radiology, Children's Hospital Boston, Harvard Medical School, Boston, MA
| | - Lawrence P Panych
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA.
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