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Song Q, Wang C, Jiang W, Wang J, Li J, Guo H, Chen H, Han X. Pre-operative spinal cord perfusion quantified by DSC MRI as a predictor of post-operative prognosis in patients with cervical spondylotic myelopathy. EUROPEAN SPINE JOURNAL : OFFICIAL PUBLICATION OF THE EUROPEAN SPINE SOCIETY, THE EUROPEAN SPINAL DEFORMITY SOCIETY, AND THE EUROPEAN SECTION OF THE CERVICAL SPINE RESEARCH SOCIETY 2024:10.1007/s00586-024-08417-0. [PMID: 39048843 DOI: 10.1007/s00586-024-08417-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/09/2023] [Revised: 03/26/2024] [Accepted: 07/15/2024] [Indexed: 07/27/2024]
Abstract
OBJECTIVE This study aims to investigate the potential of preoperative blood supply condition measured by dynamic susceptibility contract (DSC) MRI in prediction of postoperative outcomes for patients with cervical spondylotic myelopathy (CSM). MATERIALS AND METHOD Thirty-nine patients (Age: 61 ± 7, male: 23, female: 16) with CSM who underwent laminoplasty were enrolled. All patients received DSC MRI before the operation. Five parameters include Enhance, rEnhance, full width at half maxima (FWHM), Slope1 and Slope2 in DSC MRI, were calculated at all the compressed spinal cord segments. Clinical outcomes were evaluated by modified Japanese Orthopaedic Association (mJOA) scores. Patients were divided into two groups based on mJOA recovery rate of 5 years: good recovery (> 50%) or poor recovery (≤ 50%). The difference between two groups were compared. The value of DSC MRI to CSM was evaluated by logistic and receiver operating characteristic (ROC) curve analysis. RESULTS There were 26 patients in good recovery group and 13 patients in poor recovery group. The baseline characteristics, including age, gender, preoperative mJOA score, and smoking status showed no significant difference between the two groups (all p > 0.05). The FWHM was significantly higher in the poor recovery group (9.77 ± 2.78) compared to the good recovery group (6.64 ± 1.65) (p = 0.002). Logistic regression analysis indicated that an increased FWHM was a significant risk factor for poor prognosis recovery (p = 0.013, OR = 0.392, 95%CI: 0.187-0.822). The AUC of FWHM for ROC was 0.843 (95% CI: 0.710-0.975) with a p value of 0.001. In addition, an FWHM greater than 5.87, with a sensitivity of 92.3% and specificity of 69.2%, was found to be an independent risk factor for poor postoperative recovery in patients with CSM. CONCLUSION In this study, we successfully quantified the spinal cord blood supply condition by DSC MRI technique. We found that an increase in FWHM was an independent risk factor for poor postoperative recovery in CSM patients. Specifically, patients with FWHM > 5.87 have a poor postoperative recovery.
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Affiliation(s)
- Qingpeng Song
- Department of Spine Surgery, Beijing Jishuitan Hospital, Capital Medical University, Beijing, China
| | - Chunyao Wang
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China
| | - Wen Jiang
- Department of Radiology, Beijing Jishuitan Hospital, Capital Medical University, Beijing, China
| | - Jinchao Wang
- Department of Spine Surgery, Beijing Jishuitan Hospital, Capital Medical University, Beijing, China
| | - Jiuheng Li
- Beijing Jishuitan Hospital, Capital Medical University, Beijing, China
| | - Hua Guo
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China
| | - Huijun Chen
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China.
| | - Xiao Han
- Department of Spine Surgery, Beijing Jishuitan Hospital, Capital Medical University, Beijing, China.
- Beijing Research Institute of Traumatology and Orthopaedics, Beijing, China.
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Surendra KL, Patwari S, Agrawal S, Chadaga H, Nagadi A. Percentage signal intensity recovery: A step ahead of rCBV in DSC MR perfusion imaging for the differentiation of common neoplasms of brain. Indian J Cancer 2020; 57:36-43. [PMID: 31898591 DOI: 10.4103/ijc.ijc_421_18] [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: 11/04/2022]
Abstract
Context Relative cerebral blood volume (rCBV) and percentage signal recovery (PSR) obtained from T2* dynamic susceptibility contrast magnetic resonance imaging are important parameters for brain tumor assessment. Aim To study the accuracy of PSR in the differentiation of low-grade glioma, high-grade glioma, lymphoma, and metastases particularly in comparison to rCBV. Settings and Design Retrospective observational study. Subjects and Methods Study included pathologically confirmed cases of 10 low-grade glioma, 22 high-grade glioma, 6 lymphoma, and 12 metastases (Total 50). PSR, relative PSR (rPSR), and rCBV were calculated. Statistical Analysis Used Accuracy of these parameters studied statistically using analysis of variance and ROC (Receiver operating characteristic) curves. Results rCBV was higher in metastases (3.45 ± 2.82) and high-grade glioma (3.47 ± 1.62), whereas was low in lymphoma (1.03 ± 0.74) and low-grade glioma (1.43 ± 0.47) with P value of 0.030. PSR was low in metastases (48 ± 16.18), intermediate in glioma (73.24 ± 6.39 and 88.26 ± 6.05, high and low grade), and high in lymphoma (112.16 ± 10.57) with P value < 0.000. rPSR was higher for lymphoma (1.73 ± 0.57) than high-grade glioma (0.85 ± 0.11) and metastasis (0.69 ± 0.19) with P value <.000. Area under ROC for PSR was greater than rCBV in differentiating metastases from lymphoma (1.00 vs 0.13), high-grade glioma from lymphoma (1.00 vs 0.38), high-grade glioma from metastases (0.89 vs 0.58), and high-grade glioma from low-grade glioma (0.96 vs 0.03) with excellent curve characteristics. F values for PSR and rPSR from ANOVA analysis were 71.47 and 36.77, was better than rCBV (3.84) in differentiating these groups. Conclusions Percentage of signal recovery shows low recovery values in metastases, intermediate recovery values in glioma, and overshoot in lymphoma. PSR values show lower overlap than rCBV between lymphoma and metastases; and between high grade glioma and metastases. PSR difference is also higher than rCBV between low- and high-grade gliomas. Hence, PSR can potentially help as an additional perfusion parameter in the preoperative differentiation of these tumors.
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Affiliation(s)
- K L Surendra
- Department of Radiology, Columbia Asia Referral Hospital, Bangalore, Karnataka, India
| | - Sriram Patwari
- Department of Radiology, Columbia Asia Referral Hospital, Bangalore, Karnataka, India
| | - Shishir Agrawal
- Department of Radiology, Columbia Asia Referral Hospital, Bangalore, Karnataka, India
| | - Harsha Chadaga
- Department of Radiology, Columbia Asia Referral Hospital, Bangalore, Karnataka, India
| | - Anita Nagadi
- Department of Radiology, Columbia Asia Referral Hospital, Bangalore, Karnataka, India
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Pons-Escoda A, Garcia-Ruiz A, Naval-Baudin P, Cos M, Vidal N, Plans G, Bruna J, Perez-Lopez R, Majos C. Presurgical Identification of Primary Central Nervous System Lymphoma with Normalized Time-Intensity Curve: A Pilot Study of a New Method to Analyze DSC-PWI. AJNR Am J Neuroradiol 2020; 41:1816-1824. [PMID: 32943424 DOI: 10.3174/ajnr.a6761] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2020] [Accepted: 07/03/2020] [Indexed: 11/07/2022]
Abstract
BACKGROUND AND PURPOSE DSC-PWI has demonstrated promising results in the presurgical diagnosis of brain tumors. While most studies analyze specific parameters derived from time-intensity curves, very few have directly analyzed the whole curves. The aims of this study were the following: 1) to design a new method of postprocessing time-intensity curves, which renders normalized curves, and 2) to test its feasibility and performance on the diagnosis of primary central nervous system lymphoma. MATERIALS AND METHODS Diagnostic MR imaging of patients with histologically confirmed primary central nervous system lymphoma were retrospectively reviewed. Correlative cases of glioblastoma, anaplastic astrocytoma, metastasis, and meningioma, matched by date and number, were retrieved for comparison. Time-intensity curves of enhancing tumor and normal-appearing white matter were obtained for each case. Enhancing tumor curves were normalized relative to normal-appearing white matter. We performed pair-wise comparisons for primary central nervous system lymphoma against the other tumor type. The best discriminatory time points of the curves were obtained through a stepwise selection. Logistic binary regression was applied to obtain prediction models. The generated algorithms were applied in a test subset. RESULTS A total of 233 patients were included in the study: 47 primary central nervous system lymphomas, 48 glioblastomas, 39 anaplastic astrocytomas, 49 metastases, and 50 meningiomas. The classifiers satisfactorily performed all bilateral comparisons in the test subset (primary central nervous system lymphoma versus glioblastoma, area under the curve = 0.96 and accuracy = 93%; versus anaplastic astrocytoma, 0.83 and 71%; versus metastases, 0.95 and 93%; versus meningioma, 0.93 and 96%). CONCLUSIONS The proposed method for DSC-PWI time-intensity curve normalization renders comparable curves beyond technical and patient variability. Normalized time-intensity curves performed satisfactorily for the presurgical identification of primary central nervous system lymphoma.
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Affiliation(s)
- A Pons-Escoda
- Radiology Department (A.P.-E., P.N.-B., M.C., C.M.), Institut de Diagnòstic per la Imatge, Hospital Universitari de Bellvitge. L'Hospitalet de Llobregat, Barcelona, Spain .,Neurooncology Unit (A.P.-E., N.V., G.P., J.B., C.M.), Insitut Català d'Oncologia, Institut d'Investigació Biomèdica de Bellvitge, Hospital Universitari de Bellvitge, L'Hospitalet de Llobregat, Barcelona, Spain
| | - A Garcia-Ruiz
- Radiomics Group (A.G.-R., R.P.-L.), Vall d'Hebron Institut d'Oncologia, Barcelona, Spain
| | - P Naval-Baudin
- Radiology Department (A.P.-E., P.N.-B., M.C., C.M.), Institut de Diagnòstic per la Imatge, Hospital Universitari de Bellvitge. L'Hospitalet de Llobregat, Barcelona, Spain
| | - M Cos
- Radiology Department (A.P.-E., P.N.-B., M.C., C.M.), Institut de Diagnòstic per la Imatge, Hospital Universitari de Bellvitge. L'Hospitalet de Llobregat, Barcelona, Spain
| | - N Vidal
- Pathology Department (N.V.), Hospital Universitari de Bellvitge, L'Hospitalet de Llobregat, Barcelona, Spain.,Neurooncology Unit (A.P.-E., N.V., G.P., J.B., C.M.), Insitut Català d'Oncologia, Institut d'Investigació Biomèdica de Bellvitge, Hospital Universitari de Bellvitge, L'Hospitalet de Llobregat, Barcelona, Spain
| | - G Plans
- Neurosurgery Department (G.P.), Hospital Universitari de Bellvitge, L'Hospitalet de Llobregat, Barcelona, Spain.,Neurooncology Unit (A.P.-E., N.V., G.P., J.B., C.M.), Insitut Català d'Oncologia, Institut d'Investigació Biomèdica de Bellvitge, Hospital Universitari de Bellvitge, L'Hospitalet de Llobregat, Barcelona, Spain
| | - J Bruna
- Neurology Department (J.B.), Hospital Universitari de Bellvitge, L'Hospitalet de Llobregat, Barcelona, Spain.,Neurooncology Unit (A.P.-E., N.V., G.P., J.B., C.M.), Insitut Català d'Oncologia, Institut d'Investigació Biomèdica de Bellvitge, Hospital Universitari de Bellvitge, L'Hospitalet de Llobregat, Barcelona, Spain
| | - R Perez-Lopez
- Radiomics Group (A.G.-R., R.P.-L.), Vall d'Hebron Institut d'Oncologia, Barcelona, Spain
| | - C Majos
- Radiology Department (A.P.-E., P.N.-B., M.C., C.M.), Institut de Diagnòstic per la Imatge, Hospital Universitari de Bellvitge. L'Hospitalet de Llobregat, Barcelona, Spain.,Neurooncology Unit (A.P.-E., N.V., G.P., J.B., C.M.), Insitut Català d'Oncologia, Institut d'Investigació Biomèdica de Bellvitge, Hospital Universitari de Bellvitge, L'Hospitalet de Llobregat, Barcelona, Spain
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Smitha KA, Gupta AK, Jayasree RS. Relative percentage signal intensity recovery of perfusion metrics—an efficient tool for differentiating grades of glioma. Br J Radiol 2015; 88:20140784. [PMID: 26110202 DOI: 10.1259/bjr.20140784] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022] Open
Abstract
OBJECTIVE Glioma classification and characterization may be facilitated by a multiparametric approach of perfusion metrics, which could not be achieved by conventional MRI alone. Our aim is to explore the potential of relative percentage signal intensity recovery (rPSR) values, in addition to relative cerebral blood volume (rCBV) and relative cerebral blood flow (rCBF) of first-pass T2* dynamic susceptibility contrast (DSC) perfusion MRI, in differentiating high- and low-grade glioma. METHODS This prospective study included 39 patients with low-grade and 25 patients with high-grade glioma. rPSR, rCBV and rCBF were calculated from the first-pass T2* DSC perfusion MRI. rPSR was calculated using standard software and validated with dedicated perfusion metrics analysis software. The statistical analysis was performed using analysis of variance and receiver operating characteristic (ROC) curves. RESULTS Variation in rPSR, rCBV and rCBF values between low- and high-grade gliomas were statistically significant (p < 0.005). The ROC curve analysis for each of them yielded 96% sensitivity and 71.8% specificity; 88% sensitivity and 69.2% specificity; and 72% sensitivity and 66.7% specificity. The area under the curve (AUC) from the ROC curve analysis yielded 0.893, 0.852 and 0.702 for rPSR, rCBV and rCBF, respectively. The rPSR calculation with the validation software yielded 92.3% sensitivity and 72% specificity with an AUC of 0.864. CONCLUSION rPSR inversely correlates while rCBV and rCBF values directly correlate with the tumour grade. Furthermore, the overall diagnostic performance of rPSR is better than rCBV and rCBF values. ADVANCES IN KNOWLEDGE rPSR of T2* DSC perfusion is an indicator of blood-brain barrier status and lesion leakiness, which has not been explored yet compared with the usual haemodynamic parameters, rCBV and rCBF.
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Affiliation(s)
- K A Smitha
- 1 Department of Imaging Sciences and Interventional Radiology, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Trivandrum, Kerala, India
| | - A K Gupta
- 2 Department of Neuroimaging and Interventional Radiology, National Institute of Mental Health and Neurosciences, Bangalore, Karnataka, India
| | - R S Jayasree
- 3 Biophotonics and Imaging Laboratory, BMT Wing, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Trivandrum, Kerala, India
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Xia XB, Tan CL. A quantitative study of magnetic susceptibility-weighted imaging of deep cerebral veins. J Neuroradiol 2013; 40:355-9. [PMID: 23669499 DOI: 10.1016/j.neurad.2013.03.005] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2012] [Revised: 07/16/2012] [Accepted: 03/26/2013] [Indexed: 10/26/2022]
Abstract
OBJECTIVE To evaluate the value of magnetic susceptibility-weighted imaging (SWI) for measuring deep cerebral venous diameter. METHODS The diameters of 150 deep cerebral veins were measured by SWI and digital subtraction angiography (DSA) in 50 patients. RESULTS SWI showed whole cerebral veins as clear soft vessels, but with a crooked hypointense linear structure along the sulcus. Venous vessel diameter as measured by SWI was greater than that by DSA, but values from the two different techniques showed significant linear correlation (r=0.905). CONCLUSION SWI is reliable and suitable for quantitative measurements of deep cerebral veins, and more sensitive for measuring smaller vessels deep within the brain.
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Affiliation(s)
- Xi-bin Xia
- Department of Radiology, Second Xiangya Hospital, Central South University, 139, Renmin Road, 410011 Changsha, PR China; Department of Radiology, the Tumor Hospital of Hunan Province, 410013 Changsha, PR China
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Eisenbrey JR, Sridharan A, Machado P, Zhao H, Halldorsdottir VG, Dave JK, Liu JB, Park S, Dianis S, Wallace K, Thomenius KE, Forsberg F. Three-dimensional subharmonic ultrasound imaging in vitro and in vivo. Acad Radiol 2012; 19:732-9. [PMID: 22464198 DOI: 10.1016/j.acra.2012.02.015] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2012] [Revised: 02/08/2012] [Accepted: 02/09/2012] [Indexed: 12/27/2022]
Abstract
RATIONALE AND OBJECTIVES Although contrast-enhanced ultrasound imaging techniques such as harmonic imaging (HI) have evolved to reduce tissue signals using the nonlinear properties of the contrast agent, levels of background suppression have been mixed. Subharmonic imaging (SHI) offers near complete tissue suppression by centering the receive bandwidth at half the transmitting frequency. The aims of this study were to demonstrate the feasibility of three-dimensional (3D) SHI and to compare it to 3D HI. MATERIALS AND METHODS Three-dimensional HI and SHI were implemented on a Logiq 9 ultrasound scanner with a 4D10L probe. Four-cycle SHI was implemented to transmit at 5.8 MHz and receive at 2.9 MHz, while two-cycle HI was implemented to transmit at 5 MHz and receive at 10 MHz. The ultrasound contrast agent Definity was imaged within a flow phantom and the lower pole of two canine kidneys in both HI and SHI modes. Contrast-to-tissue ratios and rendered images were compared offline. RESULTS SHI resulted in significant improvement in contrast-to-tissue ratios relative to HI both in vitro (12.11 ± 0.52 vs 2.67 ± 0.77, P< .001) and in vivo (5.74 ± 1.92 vs 2.40 ± 0.48, P = .04). Rendered 3D subharmonic images provided better tissue suppression and a greater overall view of vessels in a flow phantom and canine renal vasculature. CONCLUSIONS The successful implementation of SHI in 3D allows imaging of vascular networks over a heterogeneous sample volume and should improve future diagnostic accuracy. Additionally, 3D SHI provides improved contrast-to-tissue ratios relative to 3D HI.
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