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Mijaljevic MB, Milosevic ZC, Lavrnic SĐ, Jokovic ZM, Ninkovic DI, Tubic RM, Jankovic RR. Assessment of chemical-shift and diffusion-weighted magnetic resonance imaging in differentiating malignant and benign vertebral lesions in oncologic patients. A single institution experience. Radiol Oncol 2024:raon-2024-0049. [PMID: 39361940 DOI: 10.2478/raon-2024-0049] [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: 04/11/2024] [Accepted: 07/25/2024] [Indexed: 10/05/2024] Open
Abstract
BACKGROUND To analyze the contribution of two non-standard magnetic resonance imaging (MRI) techniques the chemical-shift image (CSI), and diffusion-weighted imaging (DWI) in distinguishing malignant and benign vertebral bone marrow lesions (VBMLs). PATIENTS AND METHODS Conventional spine MRI protocol, followed by CSI and DWI was performed with a 1.5 T system on 102 oncologic patients between January 2020 and December 2023. From the identified 325 VBMLs, 102 representative lesions (one per patient) were selected. VBMLs were divided into malignant (n = 74) and benign (n = 28) based on histopathology, or imaging follow-up. The quantitative parameters for VBMLs assessment were signal intensity ratio (SIR) derived from CSI and apparent diffusion coefficient (ADC) derived from DWI. RESULTS The malignant VBMLs had significantly higher SIR values (p < 0.05) and lower ADC values compared to benign VBMLs (p < 0.05). The area under the curve (AUC) was 0.953 (p < 0.001) for SIR, and 0.894 for ADC (p < 0.001) (cut-off at > 0.82, and ≤ 1.57x10-3 mm2/s, respectively). The sensitivity and specificity for SIR were 93.6%, and 88.5%, while for ADC were 88.2% and 92.3% (respectively). The combined use of SIR and ADC improved the diagnostic accuracy to AUC of 0.988 (p < 0.001, cut-off at > 0.19), sensitivity, and specificity of 100.0% and 90.9% (respectively). CONCLUSIONS Quantitative parameters, SIR and ADC, derived from two non-standard MRI techniques, CSI, and DWI, showed diagnostic strength in differentiating malignant and benign VBMLs. Combining both methods can further enhance the diagnostic performance and accuracy of spine MRI in clinical practice.
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Affiliation(s)
- Marija B Mijaljevic
- Department of Radiology, Institute of Oncology and Radiology of Serbia, Belgrade, Serbia
| | | | - Slobodan Đ Lavrnic
- Department of Radiology, Institute of Oncology and Radiology of Serbia, Belgrade, Serbia
| | - Zorica M Jokovic
- Department of Radiology, University Children's Hospital, Belgrade, Serbia
| | - Danica I Ninkovic
- Department of Radiology, Institute of Oncology and Radiology of Serbia, Belgrade, Serbia
| | - Radoje M Tubic
- Department of Radiology, Institute of Oncology and Radiology of Serbia, Belgrade, Serbia
| | - Rajna R Jankovic
- Department of Radiology, Institute of Oncology and Radiology of Serbia, Belgrade, Serbia
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Erkal Tonkaz D, Ozpar R, Tonkaz M, Yazici Z. Efficacy of fat quantification methods used in MRI to distinguish between normal, benign, and malignant bone marrow pathologies in children. Acta Radiol 2024; 65:841-850. [PMID: 38659300 DOI: 10.1177/02841851241247110] [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] [Indexed: 04/26/2024]
Abstract
BACKGROUND Fat quantification methods in magnetic resonance imaging (MRI) have been studied to differentiate bone marrow pathologies in adult patients; however, scarce literature is available in pediatric patients. PURPOSE To evaluate the efficacy of the T1 signal intensity value (T1-SIV), out-of-phase/in-phase signal ratio (OP/IP SR), and fat fraction (FF) to differentiate between normal, benign, and malignant pathological processes. MATERIAL AND METHODS A total of 48 pediatric patients with lumbar and pelvic MRI were classified into three groups according to bone marrow pathology (group 1, normal; group 2, benign pathology/reconversion; group 3, malignant). The efficacy of T1-SIV, OP/IP SR, and FF values in differentiating these pathologies was evaluated using Kruskal-Wallis or analysis of variance and followed by Bonferroni or Dunn-Bonferroni tests. Cutoff values for malignant infiltration were defined using ROC analysis. RESULTS Although these values were significantly different in all three groups (P = 0.001-0.008), this difference was not sufficient to discriminate between all groups. Subgroup analyses showed significant differences in T1-SIV between groups 1-3, in OP/IP SR between groups 1-3, 2-3, and 1-2, in FF between groups 1-2 and 1-3 in various regions (P = 0.001-0.049). Cutoff values had a sensitivity and specificity of 90%-100% for OP/IP SR and FF. CONCLUSION T1-SIV, OP/IP SR, and FF may potentially distinguish normal from pathological bone marrow. OP/IP SR and FF values detected malignant infiltration with high sensitivity and specificity in this study. However, only OP/IP SR may significantly differentiate benign and malignant bone marrow pathologies which needs to be confirmed in the future study with a larger patient population.
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Affiliation(s)
| | - Rifat Ozpar
- Department of Radiology, Bursa Uludag University Faculty of Medicine, Bursa, Turkey
| | - Mehmet Tonkaz
- Department of Radiology, Gumushane State Hospital, Gumushane, Turkey
| | - Zeynep Yazici
- Department of Radiology, Bursa Uludag University Faculty of Medicine, Bursa, Turkey
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3
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Qin C, Goldberg O, Kakar G, Wan S, Haroon A, Azam A, Adeleke S. MRI fat fraction imaging of nodal and bone metastases in prostate cancer. Eur Radiol 2023; 33:5851-5855. [PMID: 36928564 DOI: 10.1007/s00330-023-09527-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Revised: 12/14/2022] [Accepted: 02/05/2023] [Indexed: 03/18/2023]
Abstract
KEY POINTS • Characterisation and quantification of tissue fat on MRI can be used to provide information on disease processes. • Fat in bone and lymph nodes up until recently have not been exploited for diagnostic purposes or response monitoring in prostate cancer. • Fat imaging on MRI using Dixon/PDFF sequences has the potential to add clinical value in the future but prospective data is needed.
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Affiliation(s)
- Cathy Qin
- Department of Radiology, Imperial College Healthcare NHS Trust, London, UK.
| | - Olivia Goldberg
- Department of Radiology, Imperial College Healthcare NHS Trust, London, UK
| | - Geetanjali Kakar
- Department of Radiology, Imperial College Healthcare NHS Trust, London, UK
| | - Simon Wan
- Institute of Nuclear Medicine, University College London, London, UK
| | - Athar Haroon
- Department of Nuclear Medicine, Bart's Health NHS Trust, London, UK
| | - Aishah Azam
- Department of Radiology, Guy's and St Thomas' NHS Trust, London, UK
| | - Sola Adeleke
- Department of Oncology, Guy's and St Thomas' NHS Trust, London, UK
- School of Cancer and Pharmaceutical Sciences, Kings College London, London, UK
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4
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Yan SY, Yang YW, Jiang XY, Hu S, Su YY, Yao H, Hu CH. Fat quantification: Imaging methods and clinical applications in cancer. Eur J Radiol 2023; 164:110851. [PMID: 37148843 DOI: 10.1016/j.ejrad.2023.110851] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2023] [Revised: 04/19/2023] [Accepted: 04/24/2023] [Indexed: 05/08/2023]
Abstract
Recently, the study of the relationship between lipid metabolism and cancer has evolved. The characteristics of intratumoral and peritumoral fat are distinct and changeable during cancer development. Subcutaneous and visceral adipose tissue are also associated with cancer prognosis. In non-invasive imaging, fat quantification parameters such as controlled attenuation parameter, fat volume fraction, and proton density fat fraction from different imaging methods complement conventional images by providing concrete fat information. Therefore, measuring the changes of fat content for further understanding of cancer characteristics has been applied in both research and clinical settings. In this review, the authors summarize imaging advances in fat quantification and highlight their clinical applications in cancer precaution, auxiliary diagnosis and classification, therapy response monitoring, and prognosis.
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Affiliation(s)
- Suo Yu Yan
- Department of Radiology, The First Affiliated Hospital to Soochow University, Suzhou 215006, PR China
| | - Yi Wen Yang
- Department of Radiology, The First Affiliated Hospital to Soochow University, Suzhou 215006, PR China
| | - Xin Yu Jiang
- Department of Radiology, The First Affiliated Hospital to Soochow University, Suzhou 215006, PR China
| | - Su Hu
- Department of Radiology, The First Affiliated Hospital to Soochow University, Suzhou 215006, PR China
| | - Yun Yan Su
- Department of Radiology, The First Affiliated Hospital to Soochow University, Suzhou 215006, PR China.
| | - Hui Yao
- Department of Radiology, The First Affiliated Hospital to Soochow University, Suzhou 215006, PR China; Department of General Surgery, The First Affiliated Hospital to Soochow University, Suzhou 215006, PR China.
| | - Chun Hong Hu
- Department of Radiology, The First Affiliated Hospital to Soochow University, Suzhou 215006, PR China.
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Saifuddin A, Tyler P, Rajakulasingam R. Imaging of bone marrow pitfalls with emphasis on MRI. Br J Radiol 2023; 96:20220063. [PMID: 35522786 PMCID: PMC9975530 DOI: 10.1259/bjr.20220063] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2022] [Revised: 04/17/2022] [Accepted: 04/19/2022] [Indexed: 01/27/2023] Open
Abstract
Normal marrow contains both hematopoietic/red and fatty/yellow marrow with a predictable pattern of conversion and skeletal distribution on MRI. Many variations in normal bone marrow signal and appearances are apparent and the reporting radiologist must differentiate these from other non-neoplastic, benign or neoplastic processes. The advent of chemical shift imaging has helped in characterising and differentiating more focal heterogeneous areas of red marrow from marrow infiltration. This review aims to cover the MRI appearances of normal marrow, its evolution with age, marrow reconversion, variations of normal marrow signal, causes of oedema-like marrow signal, and some common non-neoplastic entities, which may mimic marrow neoplasms.
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Affiliation(s)
- Asif Saifuddin
- Department of Radiology, Royal National Orthopaedic Hospital, Stanmore, United Kingdom
| | - Philippa Tyler
- Department of Radiology, Royal National Orthopaedic Hospital, Stanmore, United Kingdom
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Mourad C, Cosentino A, Nicod Lalonde M, Omoumi P. Advances in Bone Marrow Imaging: Strengths and Limitations from a Clinical Perspective. Semin Musculoskelet Radiol 2023; 27:3-21. [PMID: 36868241 PMCID: PMC9984270 DOI: 10.1055/s-0043-1761612] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/05/2023]
Abstract
Conventional magnetic resonance imaging (MRI) remains the modality of choice to image bone marrow. However, the last few decades have witnessed the emergence and development of novel MRI techniques, such as chemical shift imaging, diffusion-weighted imaging, dynamic contrast-enhanced MRI, and whole-body MRI, as well as spectral computed tomography and nuclear medicine techniques. We summarize the technical bases behind these methods, in relation to the common physiologic and pathologic processes involving the bone marrow. We present the strengths and limitations of these imaging methods and consider their added value compared with conventional imaging in assessing non-neoplastic disorders like septic, rheumatologic, traumatic, and metabolic conditions. The potential usefulness of these methods to differentiate between benign and malignant bone marrow lesions is discussed. Finally, we consider the limitations hampering a more widespread use of these techniques in clinical practice.
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Affiliation(s)
- Charbel Mourad
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.,Department of Diagnostic and Interventional Radiology, Hôpital Libanais Geitaoui- CHU, Beyrouth, Lebanon
| | - Aurelio Cosentino
- Department of Radiology, Hôpital Riviera-Chablais, Vaud-Valais, Rennaz, Switzerland
| | - Marie Nicod Lalonde
- Department of Nuclear Medicine and Molecular Imaging, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Patrick Omoumi
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
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Wang Y, Galante JR, Haroon A, Wan S, Afaq A, Payne H, Bomanji J, Adeleke S, Kasivisvanathan V. The future of PSMA PET and WB MRI as next-generation imaging tools in prostate cancer. Nat Rev Urol 2022; 19:475-493. [PMID: 35789204 DOI: 10.1038/s41585-022-00618-w] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/01/2022] [Indexed: 11/09/2022]
Abstract
Radiolabelled prostate-specific membrane antigen (PSMA)-based PET-CT has been shown in numerous studies to be superior to conventional imaging in the detection of nodal or distant metastatic lesions. 68Ga-PSMA PET-CT is now recommended by many guidelines for the detection of biochemically relapsed disease after radical local therapy. PSMA radioligands can also function as radiotheranostics, and Lu-PSMA has been shown to be a potential new line of treatment for metastatic castration-resistant prostate cancer. Whole-body (WB) MRI has been shown to have a high diagnostic performance in the detection and monitoring of metastatic bone disease. Prospective, randomized, multicentre studies comparing 68Ga-PSMA PET-CT and WB MRI for pelvic nodal and metastatic disease detection are yet to be performed. Challenges for interpretation of PSMA include tracer trapping in non-target tissues and also urinary excretion of tracers, which confounds image interpretation at the vesicoureteral junction. Additionally, studies have shown how long-term androgen deprivation therapy (ADT) affects PSMA expression and could, therefore, reduce tracer uptake and visibility of PSMA+ lesions. Furthermore, ADT of short duration might increase PSMA expression, leading to the PSMA flare phenomenon, which makes the accurate monitoring of treatment response to ADT with PSMA PET challenging. Scan duration, detection of incidentalomas and presence of metallic implants are some of the major challenges with WB MRI. Emerging data support the wider adoption of PSMA PET and WB MRI for diagnosis, staging, disease burden evaluation and response monitoring, although their relative roles in the standard-of-care management of patients are yet to be fully defined.
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Affiliation(s)
- Yishen Wang
- School of Clinical Medicine, University of Cambridge, Cambridge, UK. .,Barking, Havering and Redbridge University Hospitals NHS Trust, Romford, UK.
| | - Joao R Galante
- Department of Oncology, Guy's and St Thomas' NHS Foundation Trust, London, UK
| | - Athar Haroon
- Department of Nuclear Medicine, Barts Health NHS Trust, London, UK
| | - Simon Wan
- Institute of Nuclear Medicine, University College London, London, UK
| | - Asim Afaq
- Institute of Nuclear Medicine, University College London, London, UK.,Department of Radiology, University of Iowa Carver College of Medicine, Iowa City, IA, USA
| | - Heather Payne
- Department of Oncology, University College London Hospitals, London, UK
| | - Jamshed Bomanji
- Institute of Nuclear Medicine, University College London, London, UK
| | - Sola Adeleke
- Department of Oncology, Guy's and St Thomas' NHS Foundation Trust, London, UK.,School of Cancer & Pharmaceutical Sciences, King's College London, London, UK
| | - Veeru Kasivisvanathan
- Division of Surgery & Interventional Science, University College London, London, UK.,Department of Urology, University College London Hospitals NHS Foundation Trust, London, UK
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8
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Greve T, Rayudu NM, Dieckmeyer M, Boehm C, Ruschke S, Burian E, Kloth C, Kirschke JS, Karampinos DC, Baum T, Subburaj K, Sollmann N. Finite Element Analysis of Osteoporotic and Osteoblastic Vertebrae and Its Association With the Proton Density Fat Fraction From Chemical Shift Encoding-Based Water-Fat MRI - A Preliminary Study. Front Endocrinol (Lausanne) 2022; 13:900356. [PMID: 35898459 PMCID: PMC9313539 DOI: 10.3389/fendo.2022.900356] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/20/2022] [Accepted: 05/11/2022] [Indexed: 11/16/2022] Open
Abstract
PURPOSE Osteoporosis is prevalent and entails alterations of vertebral bone and marrow. Yet, the spine is also a common site of metastatic spread. Parameters that can be non-invasively measured and could capture these alterations are the volumetric bone mineral density (vBMD), proton density fat fraction (PDFF) as an estimate of relative fat content, and failure displacement and load from finite element analysis (FEA) for assessment of bone strength. This study's purpose was to investigate if osteoporotic and osteoblastic metastatic changes in lumbar vertebrae can be differentiated based on the abovementioned parameters (vBMD, PDFF, and measures from FEA), and how these parameters correlate with each other. MATERIALS AND METHODS Seven patients (3 females, median age: 77.5 years) who received 3-Tesla magnetic resonance imaging (MRI) and multi-detector computed tomography (CT) of the lumbar spine and were diagnosed with either osteoporosis (4 patients) or diffuse osteoblastic metastases (3 patients) were included. Chemical shift encoding-based water-fat MRI (CSE-MRI) was used to extract the PDFF, while vBMD was extracted after automated vertebral body segmentation using CT. Segmentation masks were used for FEA-based failure displacement and failure load calculations. Failure displacement, failure load, and PDFF were compared between patients with osteoporotic vertebrae versus patients with osteoblastic metastases, considering non-fractured vertebrae (L1-L4). Associations between those parameters were assessed using Spearman correlation. RESULTS Median vBMD was 59.3 mg/cm3 in osteoporotic patients. Median PDFF was lower in the metastatic compared to the osteoporotic patients (11.9% vs. 43.8%, p=0.032). Median failure displacement and failure load were significantly higher in metastatic compared to osteoporotic patients (0.874 mm vs. 0.348 mm, 29,589 N vs. 3,095 N, p=0.034 each). A strong correlation was noted between PDFF and failure displacement (rho -0.679, p=0.094). A very strong correlation was noted between PDFF and failure load (rho -0.893, p=0.007). CONCLUSION PDFF as well as failure displacement and load allowed to distinguish osteoporotic from diffuse osteoblastic vertebrae. Our findings further show strong associations between PDFF and failure displacement and load, thus may indicate complimentary pathophysiological associations derived from two non-invasive techniques (CSE-MRI and CT) that inherently measure different properties of vertebral bone and marrow.
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Affiliation(s)
- Tobias Greve
- Department of Neurosurgery, University Hospital, Ludwig-Maximilians-University (LMU) Munich, Munich, Germany
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- *Correspondence: Tobias Greve,
| | - Nithin Manohar Rayudu
- Engineering Product Development (EPD) Pillar, Singapore University of Technology and Design (SUTD), Singapore, Singapore
| | - Michael Dieckmeyer
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Christof Boehm
- Department of Diagnostic and Interventional Radiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Stefan Ruschke
- Department of Diagnostic and Interventional Radiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Egon Burian
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- Department of Diagnostic and Interventional Radiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Christopher Kloth
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany
| | - Jan S. Kirschke
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Dimitrios C. Karampinos
- Department of Diagnostic and Interventional Radiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Thomas Baum
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Karupppasamy Subburaj
- Engineering Product Development (EPD) Pillar, Singapore University of Technology and Design (SUTD), Singapore, Singapore
- Sobey School of Business, Saint Mary’s University, Halifax, NS, Canada
| | - Nico Sollmann
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany
- TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
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Schmeel FC, Enkirch SJ, Luetkens JA, Faron A, Lehnen N, Sprinkart AM, Schmeel LC, Radbruch A, Attenberger U, Kukuk GM, Mürtz P. Diagnostic Accuracy of Quantitative Imaging Biomarkers in the Differentiation of Benign and Malignant Vertebral Lesions : Combination of Diffusion-Weighted and Proton Density Fat Fraction Spine MRI. Clin Neuroradiol 2021; 31:1059-1070. [PMID: 33787957 PMCID: PMC8648653 DOI: 10.1007/s00062-021-01009-1] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2020] [Accepted: 02/26/2021] [Indexed: 11/30/2022]
Abstract
Purpose To compare and combine the diagnostic performance of the apparent diffusion coefficient (ADC) derived from diffusion-weighted imaging (DWI) and proton density fat fraction (PDFF) derived from chemical-shift encoding (CSE)-based water-fat magnetic resonance imaging (MRI) for distinguishing benign and malignant vertebral bone marrow lesions (VBML). Methods A total of 55 consecutive patients with 53 benign (traumatic, inflammatory and primary) and 36 malignant (metastatic and hematologic) previously untreated VBMLs were prospectively enrolled in this IRB-approved study and underwent sagittal DWI (single-shot spin-echo echo-planar with multi-slice short TI inversion recovery fat suppression) and CSE-based MRI (gradient-echo 6‑point modified Dixon) in addition to routine clinical spine MRI at 1.5 T or 3.0 T. Diagnostic reference standard was established according to histopathology or imaging follow-up. The ADC = ADC (0, 800) and PDFF = fat / (water + fat) were calculated voxel-wise and examined for differences between benign and malignant lesions. Results The ADC and PDFF values of malignant lesions were significantly lower compared to benign lesions (mean ADC 861 × 10−6 mm2/s vs. 1323 × 10−6 mm2/s, p < 0.001; mean PDFF 3.1% vs. 28.2%, p < 0.001). The areas under the curve (AUC) and diagnostic accuracies were 0.847 (p < 0.001) and 85.4% (cut-off at 1084.4 × 10−6 mm2/s) for ADC and 0.940 (p < 0.001) and 89.9% for PDFF (cut-off at 7.8%), respectively. The combined use of ADC and PDFF improved the diagnostic accuracy to 96.6% (malignancy if ADC ≤ 1118.2 × 10−6 mm2/s and PDFF ≤ 20.0%, otherwise benign). Conclusion Quantitative evaluation of both ADC and PDFF was useful in differentiating benign VBMLs from malignancy. The combination of ADC and PDFF improved the diagnostic performance and yielded high diagnostic accuracy for the differentiation of benign and malignant VBMLs.
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Affiliation(s)
- Frederic Carsten Schmeel
- Department of Neuroradiology, University Hospital Bonn, Rheinische-Friedrich-Wilhelms-Universität Bonn, Venusberg-Campus 1, 53127, Bonn, Germany. .,Research Group Clinical Neuroimaging, German Centre for Neurodegenerative Diseases (DZNE), Bonn, Germany.
| | - Simon Jonas Enkirch
- Department of Neuroradiology, University Hospital Bonn, Rheinische-Friedrich-Wilhelms-Universität Bonn, Venusberg-Campus 1, 53127, Bonn, Germany
| | - Julian Alexander Luetkens
- Department of Radiology, University Hospital Bonn, Rheinische-Friedrich-Wilhelms-Universität Bonn, Bonn, Germany
| | - Anton Faron
- Department of Radiology, University Hospital Bonn, Rheinische-Friedrich-Wilhelms-Universität Bonn, Bonn, Germany
| | - Nils Lehnen
- Department of Neuroradiology, University Hospital Bonn, Rheinische-Friedrich-Wilhelms-Universität Bonn, Venusberg-Campus 1, 53127, Bonn, Germany.,Research Group Clinical Neuroimaging, German Centre for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Alois Martin Sprinkart
- Department of Radiology, University Hospital Bonn, Rheinische-Friedrich-Wilhelms-Universität Bonn, Bonn, Germany
| | - Leonard Christopher Schmeel
- Department of Radiotherapy and Radiation Oncology, University Hospital Bonn, Rheinische-Friedrich-Wilhelms-Universität Bonn, Bonn, Germany
| | - Alexander Radbruch
- Department of Neuroradiology, University Hospital Bonn, Rheinische-Friedrich-Wilhelms-Universität Bonn, Venusberg-Campus 1, 53127, Bonn, Germany.,Research Group Clinical Neuroimaging, German Centre for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Ulrike Attenberger
- Department of Radiology, University Hospital Bonn, Rheinische-Friedrich-Wilhelms-Universität Bonn, Bonn, Germany
| | - Guido Matthias Kukuk
- Department of Radiology, University Hospital Bonn, Rheinische-Friedrich-Wilhelms-Universität Bonn, Bonn, Germany.,Department of Radiology, Cantonal Hospital Graubuenden, Chur, Switzerland
| | - Petra Mürtz
- Department of Radiology, University Hospital Bonn, Rheinische-Friedrich-Wilhelms-Universität Bonn, Bonn, Germany
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