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Cui Y, Wang X, Wang Y, Meng N, Wu Y, Shen Y, Roberts N, Bai Y, Song X, Shen G, Guo Y, Guo J, Wang M. Restriction Spectrum Imaging and Diffusion Kurtosis Imaging for Assessing Proliferation Status in Rectal Carcinoma. Acad Radiol 2024:S1076-6332(24)00584-1. [PMID: 39191564 DOI: 10.1016/j.acra.2024.08.021] [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: 06/26/2024] [Revised: 08/04/2024] [Accepted: 08/12/2024] [Indexed: 08/29/2024]
Abstract
OBJECTIVES To investigate the application of the three-compartment restriction spectrum imaging (RSI) model, diffusion kurtosis imaging (DKI), and diffusion-weighted imaging (DWI) in predicting Ki-67 status in rectal carcinoma. METHODS A total of 80 rectal carcinoma patients, including 47 high-proliferation (Ki-67 > 50%) cases and 33 low-proliferation (Ki-67 ≤ 50%) cases, underwent pelvic MRI were enrolled. Parameters derived from RSI (f1, f2, and f3), DKI (MD and MK), and DWI (ADC) were calculated and compared between the two groups. Logistic regression (LR) analysis was conducted to identify independent predictors and assess combined diagnosis. Area under the receiver operating characteristic curve (AUC), DeLong analysis, and calibration curve analyses were performed to evaluate diagnostic performance. RESULTS The patients with high-proliferation rectal carcinoma exhibited significantly higher f1 and MK values and significantly lower ADC, MD, f2, and f3 values than those with low-proliferation rectal carcinoma (P < 0.05). LR analysis showed that MD, MK, and f2 were independent predictors for Ki-67 status in rectal carcinoma. Moreover, the combination of these three parameters achieved an optimal diagnostic efficacy (AUC = 0.877, sensitivity = 80.85%, specificity = 84.85%) that was significantly better than that obtained using ADC (AUC = 0.783, Z = 2.347, P = 0.019), f2 (AUC = 0.732, Z = 2.762, P = 0.006), and f3 (AUC = 0.700, Z = 3.071, P = 0.002). The combined diagnosis also showed good performance (AUC = 0.859) in the internal validation analysis based on 1000 bootstrap samples, while the calibration curve demonstrated that the combined diagnosis provided good stability. CONCLUSION RSI, DKI, and DWI can effectively differentiate between patients with high- and low-proliferation rectal carcinoma. Furthermore, the MD, MK, and f2 imaging parameters may be a novel and promising combination biomarker for examining Ki-67 status in rectal carcinoma.
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Affiliation(s)
- Yingying Cui
- Department of Radiology, Henan Provincial People's Hospital & Zhengzhou University People's Hospital, Zhengzhou, China (Y.C., X.W., Y.W., N.M., Y.W., Y.S., Y.B., M.W.)
| | - Xinhui Wang
- Department of Radiology, Henan Provincial People's Hospital & Zhengzhou University People's Hospital, Zhengzhou, China (Y.C., X.W., Y.W., N.M., Y.W., Y.S., Y.B., M.W.)
| | - Ying Wang
- Department of Radiology, Henan Provincial People's Hospital & Zhengzhou University People's Hospital, Zhengzhou, China (Y.C., X.W., Y.W., N.M., Y.W., Y.S., Y.B., M.W.)
| | - Nan Meng
- Department of Radiology, Henan Provincial People's Hospital & Zhengzhou University People's Hospital, Zhengzhou, China (Y.C., X.W., Y.W., N.M., Y.W., Y.S., Y.B., M.W.)
| | - Yaping Wu
- Department of Radiology, Henan Provincial People's Hospital & Zhengzhou University People's Hospital, Zhengzhou, China (Y.C., X.W., Y.W., N.M., Y.W., Y.S., Y.B., M.W.)
| | - Yu Shen
- Department of Radiology, Henan Provincial People's Hospital & Zhengzhou University People's Hospital, Zhengzhou, China (Y.C., X.W., Y.W., N.M., Y.W., Y.S., Y.B., M.W.)
| | - Neil Roberts
- Queen's Medical Research Institute, University of Edinburgh, Edinburgh, UK (N.R.); Biomedical Research Institute, Henan Academy of Sciences, Zhengzhou, China (N.R., X.S., M.W.)
| | - Yan Bai
- Department of Radiology, Henan Provincial People's Hospital & Zhengzhou University People's Hospital, Zhengzhou, China (Y.C., X.W., Y.W., N.M., Y.W., Y.S., Y.B., M.W.)
| | - Xiaosheng Song
- Biomedical Research Institute, Henan Academy of Sciences, Zhengzhou, China (N.R., X.S., M.W.)
| | - Guofeng Shen
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China (G.S.); Shanghai Shende Green Medical Era Healthcare Technology Co., Ltd., Shanghai, China (G.S.)
| | - Yongjun Guo
- Henan Academy of Innovations in Medical Science, Zhengzhou, China (Y.G.)
| | - Jinxia Guo
- MR Research China, GE Healthcare, Beijing, China (J.G.)
| | - Meiyun Wang
- Department of Radiology, Henan Provincial People's Hospital & Zhengzhou University People's Hospital, Zhengzhou, China (Y.C., X.W., Y.W., N.M., Y.W., Y.S., Y.B., M.W.); Biomedical Research Institute, Henan Academy of Sciences, Zhengzhou, China (N.R., X.S., M.W.).
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Watanabe M, Shrivastava RK, Balchandani P. Advanced neuroimaging of the trigeminal nerve and the whole brain in trigeminal neuralgia: a systematic review. Pain 2024:00006396-990000000-00680. [PMID: 39132931 DOI: 10.1097/j.pain.0000000000003365] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2024] [Accepted: 06/26/2024] [Indexed: 08/13/2024]
Abstract
ABSTRACT For trigeminal neuralgia (TN), a major role of imaging is to identify the causes, but recent studies demonstrated structural and microstructural changes in the affected nerve. Moreover, an increasing number of studies have reported central nervous system involvement in TN. In this systematic review, recent quantitative magnetic resonance imaging (MRI) studies of the trigeminal nerve and the brain in patients with TN were compiled, organized, and discussed, particularly emphasizing the possible background mechanisms and the interpretation of the results. A systematic search of quantitative MRI studies of the trigeminal nerve and the brain in patients with TN was conducted using PubMed. We included the studies of the primary TN published during 2013 to 2023, conducted for the assessment of the structural and microstructural analysis of the trigeminal nerve, and the structural, diffusion, and functional MRI analysis of the brain. Quantitative MRI studies of the affected trigeminal nerves and the trigeminal pathway demonstrated structural/microstructural alterations and treatment-related changes, which differentiated responders from nonresponders. Quantitative analysis of the brain revealed changes in the brain areas associated with pain processing/modulation and emotional networks. Studies of the affected nerve demonstrated evidence of demyelination and axonal damage, compatible with pathological findings, and have shown its potential value as a tool to assess treatment outcomes. Quantitative MRI has also revealed the possibility of dynamic microstructural, structural, and functional neuronal plasticity of the brain. Further studies are needed to understand these complex mechanisms of neuronal plasticity and to achieve a consensus on the clinical use of quantitative MRI in TN.
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Affiliation(s)
- Memi Watanabe
- Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Raj K Shrivastava
- Department of Neurosurgery, Mount Sinai Medical Center, New York, NY, United States
| | - Priti Balchandani
- Icahn School of Medicine at Mount Sinai, New York, NY, United States
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Filimonova E, Pashkov A, Moysak G, Martirosyan A, Zaitsev B, Rzaev J. Diffusion tensor imaging reveals distributed white matter abnormalities in primary trigeminal neuralgia: Tract-based spatial statistics study. Clin Neurol Neurosurg 2024; 236:108080. [PMID: 38113657 DOI: 10.1016/j.clineuro.2023.108080] [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: 11/12/2023] [Revised: 11/30/2023] [Accepted: 12/06/2023] [Indexed: 12/21/2023]
Abstract
BACKGROUND Primary trigeminal neuralgia (PTN) is a prevalent chronic pain disorder whose pathogenesis is not limited to the trigeminal system. Despite the significant advances in uncovering underlying mechanisms, there is a paucity of comprehensive and consistent data regarding the role of white matter throughout the entire brain in PTN. METHODS We performed a prospective case-control study. Sixty patients with PTN and 28 age- and sex-matched healthy controls were evaluated using diffusion tensor imaging (DTI). A tract-based spatial statistical approach was performed to investigate white matter impairment in patients with PTN with several metrics, including fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD) and axial diffusivity (AD). Additionally, ROI-based analysis was performed for each white matter tract to compare FA values between groups with correction for patient age and sex. Correlations between DTI data and nerve root compression severity, as well as pain severity, were also evaluated in patients with PTN. RESULTS Our analysis demonstrated a widespread and symmetrical reduction in FA values among TN patients when compared to the control group (p < 0.05). Specifically, this FA decrease was predominantly observed in regions such as the corona radiata, internal capsule, optic radiation, and thalami, as well as structures within the posterior fossa, notably the cerebellar peduncles. No statistically significant differences were found between patients and the control group during the MD, AD and RD map analyses. ROI-based analysis did not reveal statistically significant changes in FA values in white matter tracts (p > 0.05 in all comparisons, FDR-corrected); however, there were trends towards FA value decreases in the internal capsule (p = 0.08, FDR-corrected) and inferior fronto-occipital fasciculus (p = 0.09, FDR-corrected). CONCLUSIONS Our findings indicate the presence of microstructural abnormalities in white matter among individuals with primary trigeminal neuralgia, which may potentially play a role in the development and progression of the condition.
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Affiliation(s)
- Elena Filimonova
- FSBI "Federal Center of Neurosurgery", Novosibirsk, Russia; Department of Neurosurgery, Novosibirsk State Medical University, Novosibirsk, Russia.
| | - Anton Pashkov
- FSBI "Federal Center of Neurosurgery", Novosibirsk, Russia; Department of Neurosurgery, Novosibirsk State Medical University, Novosibirsk, Russia; Department of Data Collection and Processing Systems, Novosibirsk State Technical University, Novosibirsk, Russia
| | - Galina Moysak
- FSBI "Federal Center of Neurosurgery", Novosibirsk, Russia; Department of Neurosurgery, Novosibirsk State Medical University, Novosibirsk, Russia; Department of Neuroscience, Institute of Medicine and Psychology, Novosibirsk State University, Novosibirsk, Russia
| | | | - Boris Zaitsev
- FSBI "Federal Center of Neurosurgery", Novosibirsk, Russia
| | - Jamil Rzaev
- FSBI "Federal Center of Neurosurgery", Novosibirsk, Russia; Department of Neurosurgery, Novosibirsk State Medical University, Novosibirsk, Russia; Department of Neuroscience, Institute of Medicine and Psychology, Novosibirsk State University, Novosibirsk, Russia
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