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Zhan T, Yi C, Lang Y. Predicting efficacy of neoadjuvant chemotherapy in breast cancer patients with synthetic magnetic resonance imaging method MAGiC: An observational cohort study. Eur J Radiol 2024; 179:111666. [PMID: 39128250 DOI: 10.1016/j.ejrad.2024.111666] [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: 03/19/2024] [Revised: 07/29/2024] [Accepted: 08/02/2024] [Indexed: 08/13/2024]
Abstract
OBJECTIVE MAGnetic resonance Imaging Compilation (MAGiC) is typical method of synthetic magnetic resonance imaging (MRI). The present aimed to investigate the role of MAGiC parameters of relaxation time (T1), transverse relaxation time (T2) and proton density (PD) to predict the treatment efficacy of breast cancer patients after neoadjuvant chemotherapy (NAC). METHODS The present prospective cohort study enrolled 120 breast cancer patients who received NAC during 2021-2023. Demographic data and clinical characteristics including tumor node metastasis (TNM) stage, pathological type, molecular classification and lymph node metastasis were collected. The levels of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER-2) were measured. Patients were divided by treatment efficacy using the Miller-Payne grading as partial pathological response (pPR) group and pathological complete response (pCR). The values of MAGiC parameters of longitudinal T1, T2, and PD values were recorded. RESULTS In all 120 patients, 73 (60.83%) cases were with pPR and 47 (39.17%) cases were with pCR after treatment. T2 values were markedly lower in pPR patients compared with pCR patients. However, no significant difference was found for T1 and PD values. No significant correlation was observed between any of MAGiC parameters and HER-2, ER or PR. ROC curve showed T2 could be used for prediction of pPR with AUC 0.780. Lymph node metastasis and low levels of T2 were found as independent risk factors for pPR after treatment. CONCLUSION The T2 value parameter from MAGiC is an independent risk factor for pPR following NAC in breast cancer patients, suggesting its potential as a biomarker for predicting treatment efficacy.
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Affiliation(s)
- Ting Zhan
- Department of Radiology, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang 330006, Jiangxi Province, PR China
| | - Chenghao Yi
- Department of Breast Surgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang 330006, Jiangxi Province, PR China
| | - Yuanyuan Lang
- Department of Radiology, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang 330006, Jiangxi Province, PR China.
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Lian C, Zhuang L, Wang Z, Liang J, Wu Y, Huang Y, Dai Y, Huang R. The diagnostic performance of T1 mapping in the assessment of breast lesions: A preliminary study. Eur J Radiol 2024; 177:111589. [PMID: 38941821 DOI: 10.1016/j.ejrad.2024.111589] [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: 01/28/2024] [Revised: 06/12/2024] [Accepted: 06/24/2024] [Indexed: 06/30/2024]
Abstract
PURPOSE To assess T1 mapping performance in distinguishing between benign and malignant breast lesions and to explore its correlation with histopathologic features in breast cancer. METHODS This study prospectively enrolled 103 participants with a total of 108 lesions, including 25 benign and 83 malignant lesions. T1 mapping, diffusion-weighted imaging (DWI), and dynamic contrast-enhanced (DCE) were performed. Two radiologists independently outlined the ROIs and analyzed T1 and apparent diffusion coefficient (ADC) values for each lesion, assessing interobserver reliability with the intraclass correlation coefficient (ICC). T1 and ADC values were compared between benign and malignant lesions, across different histopathological characteristics (histological grades, estrogen, progesterone and HER2 receptors expression, Ki67, N status). Receiver operating characteristic (ROC) analysis and Pearson correlation coefficient (ρ) were performed. RESULTS T1 values showed statistically significant differences between benign and malignant groups (P < 0.001), with higher values in the malignant (1817.08 ms ± 126.64) compared to the benign group (1429.31 ms ± 167.66). In addition, T1 values significantly increased in the ER (-) group (P = 0.001). No significant differences were found in T1 values among HER2, Ki67, N status, and histological grades groups. Furthermore, T1 values exhibited a significant correlation (ρ) with ER (P < 0.01) and PR (P = 0.03). The AUC for T1 value in distinguishing benign from malignant lesions was 0.69 (95 % CI: 0.55 - 0.82, P = 0.005), and for evaluating ER status, it was 0.75 (95 % CI: 0.62 - 0.87, P = 0.002). CONCLUSIONS T1 mapping holds the potential as an imaging biomarker to assist in the discrimination of benign and malignant breast lesions and assessing the ER expression status in breast cancer.
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Affiliation(s)
- Chun Lian
- Department of Medical Imaging, Peking University Shenzhen Hospital, Shenzhen, Guangdong 518036, P. R. China
| | - Lulu Zhuang
- Department of Medical Imaging, Peking University Shenzhen Hospital, Shenzhen, Guangdong 518036, P. R. China
| | - Zehao Wang
- Department of Nuclear Medicine, Peking University Shenzhen Hospital, Shenzhen, Guangdong 518036, P. R. China
| | - Jianle Liang
- Department of Medical Imaging, Peking University Shenzhen Hospital, Shenzhen, Guangdong 518036, P. R. China
| | - Yanxia Wu
- Department of Medical Imaging, Peking University Shenzhen Hospital, Shenzhen, Guangdong 518036, P. R. China
| | - Yifan Huang
- Department of Medical Imaging, Peking University Shenzhen Hospital, Shenzhen, Guangdong 518036, P. R. China
| | - Yi Dai
- Department of Medical Imaging, Peking University Shenzhen Hospital, Shenzhen, Guangdong 518036, P. R. China.
| | - Rong Huang
- Department of Medical Imaging, Peking University Shenzhen Hospital, Shenzhen, Guangdong 518036, P. R. China.
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Cui S, Guo Y, Niu W, Li J, Bian W, Wu W, Zhang W, Zheng Q, Wang J, Niu J. The quantitative parameters based on marrow metabolism derived from synthetic MRI: A pilot study of prognostic value in participants with newly diagnosed multiple myeloma. Cancer Med 2024; 13:e7109. [PMID: 38553942 PMCID: PMC10980927 DOI: 10.1002/cam4.7109] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Revised: 01/16/2024] [Accepted: 03/02/2024] [Indexed: 04/02/2024] Open
Abstract
BACKGROUND The value of SyMRI-derived parameters from lumbar marrow for predicting early treatment response and optimizing the risk stratification of the Revised International Staging System (R-ISS) in participants with multiple myeloma (MM) is unknown. METHODS We prospectively enrolled participants with newly diagnosed MM before treatment. The SyMRI of lumbar marrow was used to calculate T1, T2, and PD values and the clinical features were collected. All participants were divided into good response (≥VGPR) and poor response ( RESULTS Fifty-nine participants (good response, n = 33; poor response, n = 26) were evaluated. The bone marrow plasma cell percentage, β2-microglobulin, T1 and T2 value were difference between two groups (all p < 0.05). The T1 (odds ratio 1.003, p = 0.005) and T2 values (odds ratio 0.910, p = 0.002) were independent predictors and the AUC and cut-off values were 0.787, 967.2 ms and 0.784, 75.9 ms, respectively. There were no significant differences in SyMRI parameters between genders. Participants with both T1 value ≥967.2 ms and T2 value ≤75.9 ms in the R-ISS II stage were potentially to get poor response. CONCLUSIONS Synthetic MRI is a promising tool for predicting early treatment response to MM and promoting R-ISS II stage risk stratification.
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Affiliation(s)
- Sha Cui
- Department of Medical ImagingShanxi Medical UniversityTaiyuanChina
- Department of RadiologySecond Hospital of Shanxi Medical UniversityTaiyuanChina
| | - Yinnan Guo
- Department of PainFifth Hospital of Shanxi Medical UniversityTaiyuanChina
| | - Weiran Niu
- Department of Medical ImagingShanxi Medical UniversityTaiyuanChina
| | - Jianting Li
- Department of RadiologySecond Hospital of Shanxi Medical UniversityTaiyuanChina
| | - Wenjin Bian
- Department of Medical ImagingShanxi Medical UniversityTaiyuanChina
| | - Wenqi Wu
- Department of RadiologySecond Hospital of Shanxi Medical UniversityTaiyuanChina
| | - Wenjia Zhang
- Department of RadiologySecond Hospital of Shanxi Medical UniversityTaiyuanChina
| | - Qian Zheng
- Department of RadiologySecond Hospital of Shanxi Medical UniversityTaiyuanChina
| | - Jun Wang
- Department of RadiologySecond Hospital of Shanxi Medical UniversityTaiyuanChina
| | - Jinliang Niu
- Department of RadiologySecond Hospital of Shanxi Medical UniversityTaiyuanChina
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Ge X, Ma Y, Huang X, Gan T, Ma W, Liu G, Xiong Y, Li M, Wang X, Zhang J. Distinguishment between high-grade gliomas and solitary brain metastases in peritumoural oedema: quantitative analysis using synthetic MRI at 3 T. Clin Radiol 2024; 79:e361-e368. [PMID: 38103981 DOI: 10.1016/j.crad.2023.10.026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Revised: 09/12/2023] [Accepted: 10/21/2023] [Indexed: 12/19/2023]
Abstract
AIM To investigate the efficacy of synthetic magnetic resonance imaging (MRI) in distinguishing high-grade gliomas (HGGs) from solitary brain metastases (SBMs) in peritumoural oedema. MATERIALS AND METHODS Thirty-five patients with HGGs and 25 patients with SBMs were recruited and scanned using synthetic MRI using a 3 T scanner. Two radiologists measured synthetic MRI-derived relaxation values independently (T1, T2, proton density [PD]) in the peritumoural oedema, which was used to generate quantitative metrics before (T1native, T2native, and PDnative) and after (T1post, T2post, and PDpost) contrast agent injection. Student's t-test or the Mann-Whitney U-test was performed to detect statistically significant differences in the aforementioned metrics in peritumoural oedema between HGGs and SBMs. The receiver operating characteristic (ROC) curves were plotted to evaluate the efficacy of each metric in distinguishing the two groups, and the areas under the curves (AUCs) were compared pairwise by performing the Delong test. RESULTS The mean T1native, T2native, and T1post values in the peritumoural oedema of HGGs were significantly lower compared with SBMs (all p<0.05). The T1post value had a higher AUC (0.843) in differentiating HGGs and SBMs than all other individual metrics (all p<0.05). The combined T1native, T2native, and T1post model had the best distinguishing performance with an AUC, sensitivity, and specificity of 0.987, 94.3%, and 100%, respectively. CONCLUSIONS Synthetic MRI may be a potential supplement to the preoperative diagnosis of HGGs and SBMs in clinical practice, as the synthetic MRI-derived tri-parametric model in the peritumoural oedema showed significantly improved diagnostic performance in distinguishing HGGs from SBMs.
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Affiliation(s)
- X Ge
- Second Clinical School, Lanzhou University, Lanzhou 70030, China; Department of Magnetic Resonance, Lanzhou University Second Hospital, Lanzhou 70030, China; Gansu Province Clinical Research Center for Functional and Molecular Imaging, Lanzhou 730030, China
| | - Y Ma
- Department of Magnetic Resonance, Lanzhou University Second Hospital, Lanzhou 70030, China; Gansu Province Clinical Research Center for Functional and Molecular Imaging, Lanzhou 730030, China
| | - X Huang
- Department of Radiology, General Hospital of Ningxia Medical University, Yinchuan 750003, China
| | - T Gan
- Department of Magnetic Resonance, Lanzhou University Second Hospital, Lanzhou 70030, China; Gansu Province Clinical Research Center for Functional and Molecular Imaging, Lanzhou 730030, China
| | - W Ma
- School of Clinical Medicine, Ningxia Medical University, Yinchuan 750004, China
| | - G Liu
- Department of Magnetic Resonance, Lanzhou University Second Hospital, Lanzhou 70030, China; Gansu Province Clinical Research Center for Functional and Molecular Imaging, Lanzhou 730030, China
| | - Y Xiong
- GE Healthcare, MR Research, Beijing 100004, China
| | - M Li
- GE Healthcare, MR Enhancement Application, Beijing 100004, China
| | - X Wang
- Department of Radiology, General Hospital of Ningxia Medical University, Yinchuan 750003, China.
| | - J Zhang
- Department of Magnetic Resonance, Lanzhou University Second Hospital, Lanzhou 70030, China; Gansu Province Clinical Research Center for Functional and Molecular Imaging, Lanzhou 730030, China.
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Guo L, Zhang R, Xu Y, Wu W, Zheng Q, Li J, Wang J, Niu J. Predicting the status of lymphovascular space invasion using quantitative parameters from synthetic MRI in cervical squamous cell carcinoma without lymphatic metastasis. Front Oncol 2024; 14:1304793. [PMID: 38380361 PMCID: PMC10876895 DOI: 10.3389/fonc.2024.1304793] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2023] [Accepted: 01/16/2024] [Indexed: 02/22/2024] Open
Abstract
Purpose To investigate the value of quantitative longitudinal relaxation time (T1), transverse relaxation time (T2), and proton density (PD) maps derived from synthetic magnetic resonance imaging (MRI) for evaluating the status of lymphovascular space invasion (LVSI) in cervical squamous cell carcinoma (CSCC) without lymph node metastasis (LNM). Material and methods Patients with suspected cervical cancer who visited our hospital from May 2020 to March 2023 were collected. All patients underwent preoperative MRI, including routine sequences and synthetic MRI. Patients with pathologically confirmed CSCC without lymphatic metastasis were included in this study. The subjects were divided into negative- and positive-LVSI groups based on the status of LVSI. Quantitative parameters of T1, T2, and PD values derived from synthetic MRI were compared between the two groups using independent samples t-test. Receiver operating characteristic curves were used to determine the diagnostic efficacy of the parameters. Results 59 patients were enrolled in this study and were classified as positive (n = 32) and negative LVSI groups (n = 27). T1 and T2 values showed significant differences in differentiating negative-LVSI from positive-LVSI CSCC (1307.39 ± 122.02 vs. 1193.03 ± 107.86, P<0.0001; 88.42 ± 7.24 vs. 80.99 ± 5.50, P<0.0001, respectively). The area under the curve (AUC) for T1, T2 values and a combination of T1 and T2 values were 0.756, 0.799, 0.834 respectively, and there is no statistically significant difference in the diagnostic efficacy between individual and combined diagnosis of each parameter. Conclusions Quantitative parameters derived from synthetic MRI can be used to evaluate the LVSI status in patients with CSCC without LNM.
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Affiliation(s)
| | | | | | | | | | | | | | - Jinliang Niu
- Department of Radiology, The Second Hospital of Shanxi Medical University, Taiyuan, Shanxi, China
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Zhang Q, Zhao Y, Nie J, Long Q, Wang X, Wang X, Gong G, Liao L, Yi X, Chen BT. Pretreatment synthetic MRI features for triple-negative breast cancer. Clin Radiol 2024; 79:e219-e226. [PMID: 37935611 DOI: 10.1016/j.crad.2023.10.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2023] [Revised: 10/08/2023] [Accepted: 10/11/2023] [Indexed: 11/09/2023]
Abstract
AIM To evaluate the quantitative parameters derived from synthetic magnetic resonance imaging (SyMRI) for predicting triple-negative breast cancer (TNBC). MATERIALS AND METHODS This prospective study enrolled participants with invasive ductal breast carcinoma (IDBC) and separated them into a TNBC group and a Non-TNBC group. Preoperative breast MRI included both the SyMRI and conventional MRI sequences. The quantitative parameters derived from the SyMRI included T1 and T2 relaxation times, proton density (PD), and their standard deviations (SD). Clinicopathological characteristics, conventional MRI findings, and quantitative synthetic parameters were assessed for all participants. Multivariable logistic regression analysis was performed to determine the potential independent imaging predictors for TNBC preoperatively. Receiver operating characteristic (ROC) curve analysis was used to evaluate the performance of these parameters. RESULTS A total of 231 participants with histopathological proven IDBC were included in this study (n=46 in the TNBC group and n=185 in the Non-TNBC group). The TNBC group had significantly larger tumour size (p=0.011) and more frequent intratumoural cystic or necrotic lesions (p<0.001) as compared to the Non-TNBC group. The univariate analysis showed that the TNBC tumours had significantly higher T1 (p=0.006) and T2 (p<0.001) values than Non-TNBC tumours. Subsequent multivariable analysis indicated that T2 values and the presence of cystic or necrotic lesions were the independent predictors for TNBC. CONCLUSION The T2 from synthetic imaging and the presence of cystic degeneration or necrosis within the breast cancer may serve as potential imaging biomarkers for preoperative differentiation of TNBC from Non-TNBC.
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Affiliation(s)
- Q Zhang
- Department of Breast Surgery, Xiangya Hospital, Central South University, Changsha 410008, Hunan, PR China; Clinical Research Center for Breast Cancer, Xiangya Hospital, Central South University, Changsha 410008, Hunan, PR China; National Clinical Research Center for Geriatric Disorders (Xiangya Hospital), Central South University, Changsha 410008, Hunan, PR China
| | - Y Zhao
- National Clinical Research Center for Geriatric Disorders (Xiangya Hospital), Central South University, Changsha 410008, Hunan, PR China; Department of Radiology, Xiangya Hospital, Central South University, Changsha 410008, Hunan, PR China
| | - J Nie
- National Clinical Research Center for Geriatric Disorders (Xiangya Hospital), Central South University, Changsha 410008, Hunan, PR China; Department of Radiology, Xiangya Hospital, Central South University, Changsha 410008, Hunan, PR China
| | - Q Long
- National Clinical Research Center for Geriatric Disorders (Xiangya Hospital), Central South University, Changsha 410008, Hunan, PR China; Department of Radiology, Xiangya Hospital, Central South University, Changsha 410008, Hunan, PR China
| | - X Wang
- Department of Breast Surgery, Xiangya Hospital, Central South University, Changsha 410008, Hunan, PR China; Clinical Research Center for Breast Cancer, Xiangya Hospital, Central South University, Changsha 410008, Hunan, PR China; National Clinical Research Center for Geriatric Disorders (Xiangya Hospital), Central South University, Changsha 410008, Hunan, PR China
| | - X Wang
- Department of Breast Surgery, Xiangya Hospital, Central South University, Changsha 410008, Hunan, PR China; Clinical Research Center for Breast Cancer, Xiangya Hospital, Central South University, Changsha 410008, Hunan, PR China; National Clinical Research Center for Geriatric Disorders (Xiangya Hospital), Central South University, Changsha 410008, Hunan, PR China
| | - G Gong
- Department of Pathology, Xiangya School of Medicine, Central South University, Changsha 410008, Hunan, PR China
| | - L Liao
- Department of Breast Surgery, Xiangya Hospital, Central South University, Changsha 410008, Hunan, PR China; Clinical Research Center for Breast Cancer, Xiangya Hospital, Central South University, Changsha 410008, Hunan, PR China; National Clinical Research Center for Geriatric Disorders (Xiangya Hospital), Central South University, Changsha 410008, Hunan, PR China.
| | - X Yi
- Department of Radiology, Xiangya Hospital, Central South University, Changsha 410008, Hunan, PR China; National Engineering Research Center of Personalized Diagnostic and Therapeutic Technology, Xiangya Hospital, Changsha 410008, Hunan, PR China; Hunan Key Laboratory of Skin Cancer and Psoriasis, Xiangya Hospital, Central South University, Changsha 410008, Hunan, PR China; Hunan Engineering Research Center of Skin Health and Disease, Xiangya Hospital, Central South University, Changsha 410008, Hunan, PR China; Department of Dermatology, Xiangya Hospital, Central South University, Changsha 410008, Hunan, PR China.
| | - B T Chen
- Department of Diagnostic Radiology, City of Hope National Medical Center, Duarte, CA, USA
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Wang W, Dou B, Wang Q, Li H, Li C, Zhao W, Fang L, Pylypenko D, Chu Y. Comparison of MUSE-DWI and conventional DWI in the application of invasive breast cancer and malignancy grade prediction: A comparative study. Heliyon 2024; 10:e24379. [PMID: 38304790 PMCID: PMC10830508 DOI: 10.1016/j.heliyon.2024.e24379] [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: 08/09/2023] [Revised: 12/20/2023] [Accepted: 01/08/2024] [Indexed: 02/03/2024] Open
Abstract
Objective To compare MUSE-DWI with conventional DWI in assessing lesions of invasive breast cancer and evaluating the ADC values for preoperative histological grading. Methods A retrospective analysis was conducted on 63 lesions confirmed as invasive breast cancer by surgical or biopsy pathology. Preoperatively, all patients underwent MUSE-DWI, conventional DWI, and dynamic contrast-enhanced (DCE) scans. Two radiologists with over 5 years of experience (intermediate and senior levels, respectively) subjectively evaluated the images for clarity, image artifacts, and distortion. Objective evaluation included signal-to-noise ratio (SNR) of lesions and fibrous tissue, as well as the ADC values of both imaging techniques. Due to the limited number of cases classified as grade I and the insignificant difference in disease-specific survival and recurrence scores between grades I and II tumors, grades I and II were grouped as low-grade, while grade III was classified as high-grade. Receiver operating characteristic (ROC) curves were used to evaluate the efficacy of ADC values in preoperatively predicting the grading of invasive breast cancer. Results The SNR and subjective quality scores of MUSE-DWI images were significantly higher than those of conventional DWI (p < 0.05). For the same case, the ADC values of MUSE-DWI were lower than those of conventional DWI. The AUC values for predicting the grading of invasive breast cancer were 0.849 for MUSE-DWI and 0.801 for conventional DWI. Conclusion Compared to conventional DWI, MUSE-DWI significantly reduces artifacts and distortions, greatly improving image quality. Moreover, MUSE-DWI demonstrates higher diagnostic efficacy for preoperative histological grading of invasive breast cancer.
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Affiliation(s)
| | - Bowen Dou
- Weifang Medical University, Weifang, 261053, China
| | - Qi Wang
- Department of Radiology, Weifang People's Hospital, Weifang, Shandong, 261041, China
| | - Haogang Li
- Department of Radiology, Weifang People's Hospital, Weifang, Shandong, 261041, China
| | - Changshuai Li
- Department of Radiology, Weifang People's Hospital, Weifang, Shandong, 261041, China
| | - Wenjing Zhao
- Department of Radiology, Weifang People's Hospital, Weifang, Shandong, 261041, China
| | - Longjiang Fang
- Department of Radiology, Weifang People's Hospital, Weifang, Shandong, 261041, China
| | | | - Yujing Chu
- Department of Radiology, Weifang People's Hospital, Weifang, Shandong, 261041, China
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Zhang Z, Liu J, Zhang Y, Qu F, Grimm R, Cheng J, Wang W, Zhu J, Li S. T1 mapping as a quantitative imaging biomarker for diagnosing cervical cancer: a comparison with diffusion kurtosis imaging. BMC Med Imaging 2024; 24:16. [PMID: 38200447 PMCID: PMC10782683 DOI: 10.1186/s12880-024-01191-x] [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: 02/01/2023] [Accepted: 01/01/2024] [Indexed: 01/12/2024] Open
Abstract
BACKGROUND T1 mapping can potentially quantitatively assess the intrinsic properties of tumors. This study was conducted to explore the ability of T1 mapping in distinguishing cervical cancer type, grade, and stage and compare the diagnostic performance of T1 mapping with diffusion kurtosis imaging (DKI). METHODS One hundred fifty-seven patients with pathologically confirmed cervical cancer were enrolled in this prospectively study. T1 mapping and DKI were performed. The native T1, difference between native and postcontrast T1 (T1diff), mean kurtosis (MK), mean diffusivity (MD), and apparent diffusion coefficient (ADC) were calculated. Cervical squamous cell carcinoma (CSCC) and adenocarcinoma (CAC), low- and high-grade carcinomas, and early- and advanced-stage groups were compared using area under the receiver operating characteristic (AUROC) curves. RESULTS The native T1 and MK were higher, and the MD and ADC were lower for CSCC than for CAC (all p < 0.05). Compared with low-grade CSCC, high-grade CSCC had decreased T1diff, MD, ADC, and increased MK (p < 0.05). Compared with low-grade CAC, high-grade CAC had decreased T1diff and increased MK (p < 0.05). Native T1 was significantly higher in the advanced-stage group than in the early-stage group (p < 0.05). The AUROC curves of native T1, MK, ADC and MD were 0,772, 0.731, 0.715, and 0.627, respectively, for distinguishing CSCC from CAC. The AUROC values were 0.762 between high- and low-grade CSCC and 0.835 between high- and low-grade CAC, with T1diff and MK showing the best discriminative values, respectively. For distinguishing between advanced-stage and early-stage cervical cancer, only the AUROC of native T1 was statistically significant (AUROC = 0.651, p = 0.002). CONCLUSIONS Compared with DKI-derived parameters, native T1 exhibits better efficacy for identifying cervical cancer subtype and stage, and T1diff exhibits comparable discriminative value for cervical cancer grade.
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Affiliation(s)
- Zanxia Zhang
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, No. 1 Jianshe Dong Road, 450052, Zhengzhou, Henan, China
| | - Jie Liu
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, No. 1 Jianshe Dong Road, 450052, Zhengzhou, Henan, China
| | - Yong Zhang
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, No. 1 Jianshe Dong Road, 450052, Zhengzhou, Henan, China
| | - Feifei Qu
- MR Collaboration, Siemens Healthcare Ltd, Beijing, China
| | - Robert Grimm
- MR Application, Siemens Healthcare GmbH, Predevelopment, Erlangen, Germany
| | - Jingliang Cheng
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, No. 1 Jianshe Dong Road, 450052, Zhengzhou, Henan, China
| | - Weijian Wang
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, No. 1 Jianshe Dong Road, 450052, Zhengzhou, Henan, China
| | - Jinxia Zhu
- MR Collaboration, Siemens Healthcare Ltd, Beijing, China
| | - Shujian Li
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, No. 1 Jianshe Dong Road, 450052, Zhengzhou, Henan, China.
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Kataoka M, Iima M, Miyake KK, Honda M. Multiparametric Approach to Breast Cancer With Emphasis on Magnetic Resonance Imaging in the Era of Personalized Breast Cancer Treatment. Invest Radiol 2024; 59:26-37. [PMID: 37994113 DOI: 10.1097/rli.0000000000001044] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2023]
Abstract
ABSTRACT A multiparametric approach to breast cancer imaging offers the advantage of integrating the diverse contributions of various parameters. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is the most important MRI sequence for breast imaging. The vascularity and permeability of lesions can be estimated through the use of semiquantitative and quantitative parameters. The increased use of ultrafast DCE-MRI has facilitated the introduction of novel kinetic parameters. In addition to DCE-MRI, diffusion-weighted imaging provides information associated with tumor cell density, with advanced diffusion-weighted imaging techniques such as intravoxel incoherent motion, diffusion kurtosis imaging, and time-dependent diffusion MRI opening up new horizons in microscale tissue evaluation. Furthermore, T2-weighted imaging plays a key role in measuring the degree of tumor aggressiveness, which may be related to the tumor microenvironment. Magnetic resonance imaging is, however, not the only imaging modality providing semiquantitative and quantitative parameters from breast tumors. Breast positron emission tomography demonstrates superior spatial resolution to whole-body positron emission tomography and allows comparable delineation of breast cancer to MRI, as well as providing metabolic information, which often precedes vascular and morphological changes occurring in response to treatment. The integration of these imaging-derived factors is accomplished through multiparametric imaging. In this article, we explore the relationship among the key imaging parameters, breast cancer diagnosis, and histological characteristics, providing a technical and theoretical background for these parameters. Furthermore, we review the recent studies on the application of multiparametric imaging to breast cancer and the significance of the key imaging parameters.
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Affiliation(s)
- Masako Kataoka
- From the Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine Kyoto University, Kyoto, Japan (M.K., M.I., M.H.); Institute for Advancement of Clinical and Translational Science, Kyoto University Hospital, Kyoto, Japan (M.I.); Department of Advanced Imaging in Medical Magnetic Resonance, Graduate School of Medicine Kyoto University, Kyoto, Japan (K.K.M); and Department of Diagnostic Radiology, Kansai Electric Power Hospital, Osaka, Japan (M.H.)
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Li J, Kou P, Lin L, Xiao Y, Jin H, Zhang Y, Cheng J. T1 mapping in evaluation of clinicopathologic factors for rectal adenocarcinoma. Abdom Radiol (NY) 2024; 49:279-287. [PMID: 37839066 DOI: 10.1007/s00261-023-04045-2] [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: 06/08/2023] [Revised: 08/31/2023] [Accepted: 09/03/2023] [Indexed: 10/17/2023]
Abstract
OBJECTIVE T1 mapping has been increasingly applied in the study of tumor. The purpose of this study was to evaluate the value of T1 mapping in evaluating clinicopathologic factors for rectal adenocarcinoma. MATERIALS AND METHODS Eighty-six patients with rectal adenocarcinoma confirmed by surgical pathology who underwent preoperative pelvic MRI were retrospectively analyzed. High-resolution T2-weighted imaging (T2WI), T1 mapping, and diffusion-weighted imaging (DWI) were performed. T1 and apparent diffusion coefficient (ADC) parameters were compared among different associated tumor markers, tumor grades, stages, and structure invasion statuses. A receiver operating characteristic (ROC) analysis was estimated. RESULTS T1 value showed significant difference between high- and low-grade tumors ([1531.5 ± 84.7 ms] vs. [1437.1 ± 80.3 ms], P < 0.001). T1 value was significant higher in positive than in negative perineural invasion ([1495.7 ± 89.2 ms] vs. [1449.4 ± 88.8 ms], P < 0.05). No significant difference of T1 or ADC was observed in different CEA, CA199, T stage, N stage, lymphovascular invasions, extramural vascular invasion (EMVI), and circumferential resection margin (CRM) (P > 0.05). The AUC under ROC curve of T1 value were 0.796 in distinguishing high- from low-grade rectal adenocarcinoma. The AUC of T1 value in distinguishing perineural invasion was 0.637. CONCLUSION T1 value was helpful in assessing pathologic grade and perineural invasion correlated with rectal cancer.
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Affiliation(s)
- Juan Li
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, No. 1, Jianshe Dong Road, Zhengzhou, 450052, China.
| | - Peisi Kou
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, No. 1, Jianshe Dong Road, Zhengzhou, 450052, China
| | - Liangjie Lin
- Advanced Technical Support, Philips Healthcare, Beijing, China
| | - Yunfei Xiao
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, No. 1, Jianshe Dong Road, Zhengzhou, 450052, China
| | - Hongrui Jin
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, No. 1, Jianshe Dong Road, Zhengzhou, 450052, China
| | - Yong Zhang
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, No. 1, Jianshe Dong Road, Zhengzhou, 450052, China
| | - Jingliang Cheng
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, No. 1, Jianshe Dong Road, Zhengzhou, 450052, China
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Qu J, Pan B, Su T, Chen Y, Zhang T, Chen X, Zhu X, Xu Z, Wang T, Zhu J, Zhang Z, Feng F, Jin Z. T1 and T2 mapping for identifying malignant lymph nodes in head and neck squamous cell carcinoma. Cancer Imaging 2023; 23:125. [PMID: 38105217 PMCID: PMC10726506 DOI: 10.1186/s40644-023-00648-6] [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] [Received: 09/05/2023] [Accepted: 12/04/2023] [Indexed: 12/19/2023] Open
Abstract
BACKGROUND This study seeks to assess the utility of T1 and T2 mapping in distinguishing metastatic lymph nodes from reactive lymphadenopathy in patients with head and neck squamous cell carcinoma (HNSCC), using diffusion-weighted imaging (DWI) as a comparison. METHODS Between July 2017 and November 2019, 46 HNSCC patients underwent neck MRI inclusive of T1 and T2 mapping and DWI. Quantitative measurements derived from preoperative T1 and T2 mapping and DWI of metastatic and non-metastatic lymph nodes were compared using independent samples t-test or Mann-Whitney U test. Receiver operating characteristic curves and the DeLong test were employed to determine the most effective diagnostic methodology. RESULTS We examined a total of 122 lymph nodes, 45 (36.9%) of which were metastatic proven by pathology. Mean T2 values for metastatic lymph nodes were significantly lower than those for benign lymph nodes (p < 0.001). Conversely, metastatic lymph nodes exhibited significantly higher apparent diffusion coefficient (ADC) and standard deviation of T1 values (T1SD) (p < 0.001). T2 generated a significantly higher area under the curve (AUC) of 0.890 (0.826-0.954) compared to T1SD (0.711 [0.613-0.809]) and ADC (0.660 [0.562-0.758]) (p = 0.007 and p < 0.001). Combining T2, T1SD, ADC, and lymph node size achieved an AUC of 0.929 (0.875-0.983), which did not significantly enhance diagnostic performance over using T2 alone (p = 0.089). CONCLUSIONS The application of T1 and T2 mapping is feasible in differentiating metastatic from non-metastatic lymph nodes in HNSCC and can improve diagnostic efficacy compared to DWI.
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Affiliation(s)
- Jiangming Qu
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical Union Medical College, No.1 Shuaifuyuan Wangfujing Dongcheng District, Beijing, 100730, China
| | - Boju Pan
- Department of Pathology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical Union Medical College, No.1 Shuaifuyuan Wangfujing Dongcheng District, Beijing, 100730, China
| | - Tong Su
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical Union Medical College, No.1 Shuaifuyuan Wangfujing Dongcheng District, Beijing, 100730, China
| | - Yu Chen
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical Union Medical College, No.1 Shuaifuyuan Wangfujing Dongcheng District, Beijing, 100730, China.
| | - Tao Zhang
- Department of Stomatology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical Union Medical College, No.1 Shuaifuyuan Wangfujing Dongcheng District, Beijing, 100730, China
| | - Xingming Chen
- Department of Otolaryngology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical Union Medical College, No.1 Shuaifuyuan Wangfujing Dongcheng District, Beijing, 100730, China
| | - Xiaoli Zhu
- Department of Otolaryngology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical Union Medical College, No.1 Shuaifuyuan Wangfujing Dongcheng District, Beijing, 100730, China
| | - Zhentan Xu
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical Union Medical College, No.1 Shuaifuyuan Wangfujing Dongcheng District, Beijing, 100730, China
| | - Tianjiao Wang
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical Union Medical College, No.1 Shuaifuyuan Wangfujing Dongcheng District, Beijing, 100730, China
| | - Jinxia Zhu
- MR Research Collaboration, Siemens Healthineers Ltd, Beijing, China
| | - Zhuhua Zhang
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical Union Medical College, No.1 Shuaifuyuan Wangfujing Dongcheng District, Beijing, 100730, China.
| | - Feng Feng
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical Union Medical College, No.1 Shuaifuyuan Wangfujing Dongcheng District, Beijing, 100730, China
| | - Zhengyu Jin
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical Union Medical College, No.1 Shuaifuyuan Wangfujing Dongcheng District, Beijing, 100730, China.
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Li X, Fan Z, Jiang H, Niu J, Bian W, Wang C, Wang Y, Zhang R, Zhang H. Synthetic MRI in breast cancer: differentiating benign from malignant lesions and predicting immunohistochemical expression status. Sci Rep 2023; 13:17978. [PMID: 37864025 PMCID: PMC10589282 DOI: 10.1038/s41598-023-45079-2] [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] [Received: 07/25/2022] [Accepted: 10/16/2023] [Indexed: 10/22/2023] Open
Abstract
To evaluate and compare the performance of synthetic magnetic resonance imaging (SyMRI) in classifying benign and malignant breast lesions and predicting the expression status of immunohistochemistry (IHC) markers. We retrospectively analysed 121 patients with breast lesions who underwent dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and SyMRI before surgery in our hospital. DCE-MRI was used to assess the lesions, and then regions of interest (ROIs) were outlined on SyMRI (before and after enhancement), and apparent diffusion coefficient (ADC) maps to obtain quantitative values. After being grouped according to benign and malignant status, the malignant lesions were divided into high and low expression groups according to the expression status of IHC markers. Logistic regression was used to analyse the differences in independent variables between groups. The performance of the modalities in classification and prediction was evaluated by receiver operating characteristic (ROC) curves. In total, 57 of 121 lesions were benign, the other 64 were malignant, and 56 malignant lesions performed immunohistochemical staining. Quantitative values from proton density-weighted imaging prior to an injection of the contrast agent (PD-Pre) and T2-weighted imaging (T2WI) after the injection (T2-Gd), as well as its standard deviation (SD of T2-Gd), were valuable SyMRI parameters for the classification of benign and malignant breast lesions, but the performance of SyMRI (area under the curve, AUC = 0.716) was not as good as that of ADC values (AUC = 0.853). However, ADC values could not predict the expression status of breast cancer markers, for which SyMRI had excellent performance. The AUCs of androgen receptor (AR), estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER-2), p53 and Ki-67 were 0.687, 0.890, 0.852, 0.746, 0.813 and 0.774, respectively. SyMRI had certain value in distinguishing between benign and malignant breast lesions, and ADC values were still the ideal method. However, to predict the expression status of IHC markers, SyMRI had an incomparable value compared with ADC values.
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Affiliation(s)
- Xiaojun Li
- Department of Medical Imaging, Shanxi Medical University, Taiyuan, Shanxi, China
- Department of Radiology, Cancer Hospital Chinese Academy of Medical Sciences, Shenzhen Center, Shenzhen, China
| | - Zhichang Fan
- Department of Medical Imaging, Shanxi Medical University, Taiyuan, Shanxi, China
| | - Hongnan Jiang
- Department of Breast Surgery, Cancer Hospital Chinese Academy of Medical Sciences, Shenzhen Center, Shenzhen, China
| | - Jinliang Niu
- Department of Radiology, The 2nd Affiliated Hospital of Shanxi Medical University, Taiyuan, Shanxi, China
| | - Wenjin Bian
- Department of Medical Imaging, Shanxi Medical University, Taiyuan, Shanxi, China
| | - Chen Wang
- Department of Pathology, The 2nd Affiliated Hospital of Shanxi Medical University, Taiyuan, Shanxi, China
| | - Ying Wang
- Department of Pathology, The 2nd Affiliated Hospital of Shanxi Medical University, Taiyuan, Shanxi, China
| | - Runmei Zhang
- Department of Radiology, The 2nd Affiliated Hospital of Shanxi Medical University, Taiyuan, Shanxi, China
| | - Hui Zhang
- Department of Radiology, First Hospital of Shanxi Medical University, No. 85, South Jiefang Road, Yingze District, Taiyuan, 030001, Shanxi, China.
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Li S, Liu J, Zhang W, Lu H, Wang W, Lin L, Zhang Y, Cheng J. T1 mapping and multimodel diffusion-weighted imaging in the assessment of cervical cancer: a preliminary study. Br J Radiol 2023; 96:20220952. [PMID: 37183908 PMCID: PMC10392640 DOI: 10.1259/bjr.20220952] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2022] [Revised: 03/22/2023] [Accepted: 04/23/2023] [Indexed: 05/16/2023] Open
Abstract
OBJECTIVE To evaluate the clinical feasibility of T1 mapping and multimodel diffusion-weighted imaging (DWI) for assessing the histological type, grade, and lymphovascular space invasion (LVSI) of cervical cancer. METHODS Eighty patients with cervical cancer and 43 patients with a normal cervix underwent T1 mapping and DWI with 11 b-values (0-2000 s/mm2). Monoexponential, biexponential, and kurtosis models were fitted to calculate the apparent diffusion coefficient (ADC), pure molecular diffusion (D), pseudo-diffusion (D*), perfusion fraction (f), mean diffusivity (MD), and mean kurtosis (MK). Native T1 and DWI-derived parameters (ADCmean, ADCmin, Dmean, Dmin, D*, f, MDmean, MDmin, MKmean, and MKmax) were compared based on histological type, grade, and LVSI status. RESULTS Native T1 and DWI-derived parameters differed significantly between cervical cancer and normal cervix (all p < 0.05), except D* (p = 0.637). Native T1 and MKmean varied significantly between squamous cell carcinoma (SCC) and adenocarcinoma (both p < 0.05). ADCmin, Dmin, and MDmin were significantly lower while MKmax was significantly higher in the high-grade SCC group than in the low-grade SCC group (all p < 0.05). LVSI-positive SCC had a significantly higher MKmean than LVSI-negative SCC (p < 0.05). CONCLUSION Both T1 mapping and multimodel DWI can effectively differentiate cervical cancer from a normal cervix and cervical adenocarcinoma from SCC. Furthermore, multimodel DWI may provide quantitative metrics for non-invasively predicting histological grade and LVSI status in SCC patients. ADVANCES IN KNOWLEDGE Combined use of T1 mapping and multimodel DWI may provide more comprehensive information for non-invasive pre-operative evaluation of cervical cancer.
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Affiliation(s)
- Shujian Li
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Jie Liu
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Wenhua Zhang
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Huifang Lu
- Department of Gynecology and Obstetrics, Huaihe Hospital of Henan University, Kaifeng, China
| | - Weijian Wang
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Liangjie Lin
- Advanced Technical Support, Philips Healthcare, Beijing, China
| | - Yong Zhang
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Jingliang Cheng
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
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Yang F, Li X, Li Y, Lei H, Du Q, Yu X, Li L, Zhao Y, Xie L, Lin M. Histogram analysis of quantitative parameters from synthetic MRI: correlations with prognostic factors in nasopharyngeal carcinoma. Eur Radiol 2023; 33:5344-5354. [PMID: 37036478 DOI: 10.1007/s00330-023-09553-9] [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: 08/31/2022] [Revised: 01/30/2023] [Accepted: 02/17/2023] [Indexed: 04/11/2023]
Abstract
OBJECTIVES To evaluate the correlation between histogram parameters derived from synthetic magnetic resonance imaging (SyMRI) and prognostically relevant factors in nasopharyngeal carcinoma (NPC). METHODS Fifty-nine consecutive NPC patients were prospectively enrolled. Quantitative parameters (T1, T2, and proton density (PD)) were obtained by outlining the three-dimensional volume of interest (VOI) of all lesions. Then, histogram analysis of these quantitative parameters was performed and the correlations with prognostically relevant factors were assessed. By choosing appropriate cutoff, we divided the sample into two groups. Independent-samples t test/Mann-Whitney U test was used and ROC curve analysis was further processed. RESULTS Histogram parameters of the T1, T2, and PD maps were positively correlated with the Ki-67 expression levels, and PD_mean was the most representative parameter (AUC: 0.861). The PD map exhibited good performance in differentiating epidermal growth factor receptor (EGFR) expression levels (AUC: 0.706~0.732) and histological type (AUC: 0.650~0.660). T2_minimum was highest correlated with Epstein-Barr virus (EBV) DNA levels (r = - 0.419), and PD_75th percentile exhibited the highest performance in distinguishing positive and negative EBV DNA groups (AUC: 0.721). T1_minimum was statistically correlated with EA-IgA expression (r = - 0.313). Additionally, several histogram parameters were negatively correlated with tumor stage (T stage: r = - 0.259 ~ - 0.301; N stage: r = - 0.348 ~ - 0.456; clinical stage: r = - 0.419). CONCLUSIONS Histogram parameters of SyMRI could reflect tissue intrinsic characteristics and showed potential value in assessing the Ki-67 and EGFR expression levels, histological type, EBV DNA level, EA-IgA, and tumor stage. KEY POINTS • SyMRI combined with histogram analysis may help clinicians to assess different prognostic factor statuses in nasopharyngeal carcinoma. • The PD map exhibited good discriminating performance in the Ki-67 and EGFR expression levels. • Histogram parameters of SyMRI were negatively correlated with EBV-related blood biomarkers and TNM stage.
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Affiliation(s)
- Fan Yang
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Xiaolu Li
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Yujie Li
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Huizi Lei
- Department of Pathology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Qiang Du
- Department of Pathology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Xiaoduo Yu
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Lin Li
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Yanfeng Zhao
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Lizhi Xie
- MR Research China, GE Healthcare, Beijing, China
| | - Meng Lin
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China.
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Li M, Fu W, Ouyang L, Cai Q, Huang Y, Yang X, Pan W, Qian L, Guo Y, Wang H. Potential clinical feasibility of synthetic MRI in bladder tumors: a comparative study with conventional MRI. Quant Imaging Med Surg 2023; 13:5109-5118. [PMID: 37581035 PMCID: PMC10423390 DOI: 10.21037/qims-22-1419] [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: 12/21/2022] [Accepted: 05/19/2023] [Indexed: 08/16/2023]
Abstract
Background Synthetic magnetic resonance imaging (MRI) can provide quantitative information about inherent tissue properties and synthesize tailored contrast-weighted images simultaneously in a single scan. This study aimed to investigate the clinical feasibility of synthetic MRI in bladder tumors. Methods A total of 47 patients (37 males; mean age: 66±10 years old) with postoperative pathology-confirmed papillary urothelial neoplasms of the bladder were enrolled in this retrospective study. A 2-dimensional (2D) multi-dynamic multi-echo pulse sequence was performed for synthetic MRI at 3T. The overall image quality, lesion conspicuity, contrast resolution, resolution of subtle anatomic structures, motion artifact, blurring, and graininess of images were subjectively evaluated by 2 radiologists independently using a 5-point Likert scale for qualitative analysis. The signal intensity ratio (SIR), signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were measured for quantitative analysis. Linear weighted Kappa, Wilcoxon's signed-rank test, and the Mann-Whitney U-test were used for statistical analysis. Results The interobserver consistency was excellent (κ values: 0.607-1). Synthetic T1-weighted (syn-T1w) and synthetic T2-weighted (syn-T2w) images obtained scores of 4 in most subjective terms, which were relatively smaller than those of conventional images. The SIR and SNR of syn-T1w were significantly higher than those of con-T1w images (SIR 2.37±0.86 vs. 1.47±0.20, P<0.001; SNR 21.83±9.43 vs. 14.81±3.30, P<0.001). No difference was found in SIR between syn-T2w and conventional T2-weighted (con-T2w) images, whereas the SNR of the syn-T2w was significantly lower (8.79±4.06 vs. 26.49±6.80, P<0.001). Additionally, the CNR of synthetic images was significantly lower than that of conventional images (T1w 1.41±0.72 vs. 2.68±1.04; T2w 1.40±0.87 vs. 4.03±1.55, all P<0.001). Conclusions Synthetic MRI generates morphologic magnetic resonance (MR) images with diagnostically acceptable image quality in bladder tumors, especially T1-weighted images with high image contrast of tumors relative to urine. Further technological improvements are needed for synthetic MRI to reduce noise. Combined with T1, T2, and proton density (PD) quantitative data, synthetic MRI has potential for clinical application in bladder tumors.
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Affiliation(s)
- Meiqin Li
- Department of Radiology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Wenhao Fu
- Department of Radiology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Longyuan Ouyang
- Department of Radiology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Qian Cai
- Department of Radiology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Yiping Huang
- Department of Radiology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Xiaoyu Yang
- Department of Radiology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Weibin Pan
- Department of Radiology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Long Qian
- MR Research, GE Healthcare, Beijing, China
| | - Yan Guo
- Department of Radiology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Huanjun Wang
- Department of Radiology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
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Bortolotto C, Messana G, Lo Tito A, Stella GM, Pinto A, Podrecca C, Bellazzi R, Gerbasi A, Agustoni F, Han F, Nickel MD, Zacà D, Filippi AR, Bottinelli OM, Preda L. The Role of Native T1 and T2 Mapping Times in Identifying PD-L1 Expression and the Histological Subtype of NSCLCs. Cancers (Basel) 2023; 15:3252. [PMID: 37370861 DOI: 10.3390/cancers15123252] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2023] [Revised: 06/08/2023] [Accepted: 06/16/2023] [Indexed: 06/29/2023] Open
Abstract
We investigated the association of T1/T2 mapping values with programmed death-ligand 1 protein (PD-L1) expression in lung cancer and their potential in distinguishing between different histological subtypes of non-small cell lung cancers (NSCLCs). Thirty-five patients diagnosed with stage III NSCLC from April 2021 to December 2022 were included. Conventional MRI sequences were acquired with a 1.5 T system. Mean T1 and T2 mapping values were computed for six manually traced ROIs on different areas of the tumor. Data were analyzed through RStudio. Correlation between T1/T2 mapping values and PD-L1 expression was studied with a Wilcoxon-Mann-Whitney test. A Kruskal-Wallis test with a post-hoc Dunn test was used to study the correlation between T1/T2 mapping values and the histological subtypes: squamocellular carcinoma (SCC), adenocarcinoma (ADK), and poorly differentiated NSCLC (PD). There was no statistically significant correlation between T1/T2 mapping values and PD-L1 expression in NSCLC. We found statistically significant differences in T1 mapping values between ADK and SCC for the periphery ROI (p-value 0.004), the core ROI (p-value 0.01), and the whole tumor ROI (p-value 0.02). No differences were found concerning the PD NSCLCs.
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Affiliation(s)
- Chandra Bortolotto
- Diagnostic Imaging and Radiotherapy Unit, Department of Clinical, Surgical, Diagnostic, and Pediatric Sciences, University of Pavia, 27100 Pavia, Italy
- Radiology Institute, Fondazione IRCCS Policlinico San Matteo, 27100 Pavia, Italy
| | - Gaia Messana
- Diagnostic Imaging and Radiotherapy Unit, Department of Clinical, Surgical, Diagnostic, and Pediatric Sciences, University of Pavia, 27100 Pavia, Italy
| | - Antonio Lo Tito
- Diagnostic Imaging and Radiotherapy Unit, Department of Clinical, Surgical, Diagnostic, and Pediatric Sciences, University of Pavia, 27100 Pavia, Italy
| | - Giulia Maria Stella
- Unit of Respiratory Diseases, Department of Medical Sciences and Infective Diseases, Fondazione IRCCS Policlinico San Matteo, 27100 Pavia, Italy
- Department of Internal Medicine and Medical Therapeutics, University of Pavia, 27100 Pavia, Italy
| | - Alessandra Pinto
- Diagnostic Imaging and Radiotherapy Unit, Department of Clinical, Surgical, Diagnostic, and Pediatric Sciences, University of Pavia, 27100 Pavia, Italy
| | - Chiara Podrecca
- Department of Electrical, Computer and Biomedical Engineering, University of Pavia, 27100 Pavia, Italy
| | - Riccardo Bellazzi
- Department of Electrical, Computer and Biomedical Engineering, University of Pavia, 27100 Pavia, Italy
| | - Alessia Gerbasi
- Department of Electrical, Computer and Biomedical Engineering, University of Pavia, 27100 Pavia, Italy
| | - Francesco Agustoni
- Department of Medical Oncology, Fondazione IRCCS Policlinico San Matteo, 27100 Pavia, Italy
| | - Fei Han
- MR Application Predevelopment, Siemens Healthcare GmbH, Allee am Roethelheimpark 2, 91052 Erlangen, Germany
| | - Marcel Dominik Nickel
- MR Application Predevelopment, Siemens Healthcare GmbH, Allee am Roethelheimpark 2, 91052 Erlangen, Germany
| | | | - Andrea Riccardo Filippi
- Diagnostic Imaging and Radiotherapy Unit, Department of Clinical, Surgical, Diagnostic, and Pediatric Sciences, University of Pavia, 27100 Pavia, Italy
- Department of Radiation Oncology, Fondazione IRCCS Policlinico San Matteo, 27100 Pavia, Italy
| | - Olivia Maria Bottinelli
- Diagnostic Imaging and Radiotherapy Unit, Department of Clinical, Surgical, Diagnostic, and Pediatric Sciences, University of Pavia, 27100 Pavia, Italy
| | - Lorenzo Preda
- Diagnostic Imaging and Radiotherapy Unit, Department of Clinical, Surgical, Diagnostic, and Pediatric Sciences, University of Pavia, 27100 Pavia, Italy
- Radiology Institute, Fondazione IRCCS Policlinico San Matteo, 27100 Pavia, Italy
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Yang F, Wei H, Li X, Yu X, Zhao Y, Li L, Li Y, Xie L, Wang S, Lin M. Pretreatment synthetic magnetic resonance imaging predicts disease progression in nonmetastatic nasopharyngeal carcinoma after intensity modulation radiation therapy. Insights Imaging 2023; 14:59. [PMID: 37016104 PMCID: PMC10073373 DOI: 10.1186/s13244-023-01411-y] [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: 11/03/2022] [Accepted: 03/22/2023] [Indexed: 04/06/2023] Open
Abstract
BACKGROUND To investigate the potential of synthetic MRI (SyMRI) in the prognostic assessment of patients with nonmetastatic nasopharyngeal carcinoma (NPC), and the predictive value when combined with diffusion-weighted imaging (DWI) as well as clinical factors. METHODS Fifty-three NPC patients who underwent SyMRI were prospectively included. 10th Percentile, Mean, Kurtosis, and Skewness of T1, T2, and PD maps and ADC value were obtained from the primary tumor. Cox regression analysis was used for analyzing the association between SyMRI and DWI parameters and progression-free survival (PFS), and then age, sex, staging, and treatment as confounding factors were also included. C-index was obtained by bootstrap. Moreover, significant parameters were used to construct models in predicting 3-year disease progression. ROC curves and leave-one-out cross-validation were used to evaluate the performance and stability. RESULTS Disease progression occurred in 16 (30.2%) patients at a follow-up of 39.6 (3.5, 48.2) months. T1_Kurtosis, T1_Skewness, T2_10th, PD_Mean, and ADC were correlated with PFS, and T1_Kurtosis (HR: 1.093) and ADC (HR: 1.009) were independent predictors of PFS. The C-index of SyMRI and SyMRI + DWI + Clinic models was 0.687 and 0.779. Moreover, the SyMRI + DWI + Clinic model predicted 3-year disease progression better than DWI or Clinic model (p ≤ 0.008). Interestingly, there was no significant difference between the SyMRI model (AUC: 0.748) and SyMRI + DWI + Clinic model (AUC: 0.846, p = 0.092). CONCLUSION SyMRI combined with histogram analysis could predict disease progression in NPC patients, and SyMRI + DWI + Clinic model further improved the predictive performance.
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Affiliation(s)
- Fan Yang
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Haoran Wei
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Xiaolu Li
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Xiaoduo Yu
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Yanfeng Zhao
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Lin Li
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Yujie Li
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Lizhi Xie
- MR Research China, GE Healthcare, Beijing, China
| | - Sicong Wang
- MR Research China, GE Healthcare, Beijing, China
| | - Meng Lin
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China.
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Histogram analysis of synthetic magnetic resonance imaging: Correlations with histopathological factors in head and neck squamous cell carcinoma. Eur J Radiol 2023; 160:110715. [PMID: 36753947 DOI: 10.1016/j.ejrad.2023.110715] [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: 12/31/2022] [Accepted: 01/24/2023] [Indexed: 01/30/2023]
Abstract
PURPOSE To analyse the association between histogram parameters derived from synthetic MRI (SyMRI) and different histopathological factors in head and neck squamous cell carcinoma (HNSCC). METHOD Sixty-one patients with histologically proven primary HNSCC were prospectively enrolled. The correlations between histogram parameters of SyMRI (T1, T2 and proton density (PD) maps) and histopathological factors were analysed using Spearman analysis. The Mann-Whitney U test or Student's t test was utilized to differentiate histological grades and human papillomavirus (HPV) status. The ROC curves and leave-one-out cross-validation (LOOCV) were used to evaluate the differentiation performance. Bootstrapping was applied to avoid overfitting. RESULTS Several histogram parameters were associated with histological grade: T1 map (r = 0.291) and PD map (r = 0.294 - 0.382/-0.343), and PD_75th Percentile showed the highest differentiation performance (AUC: 0.721 (ROC) and 0.719 (LOOCV)). Moderately negative correlations were found between p16 status and the histogram parameters: T1 map (r = -0.587 - -0.390), T2 map (r = -0.649 - -0.357) and PD map (r = -0.537 - -0.338). In differentiating HPV infection, Entropy was the most discriminative parameter in each map and T2_Entropy showed the highest diagnostic performance (AUC: 0.851 [ROC] and 0.851 [LOOCV]). Additionally, several histogram parameters were correlated with Ki-67 (r = -0.379/-0.397), epidermal growth factor receptor (EGFR) (r = 0.318/0.322) status and p53 (r = 0.452 - 0.665/-0.607) status. CONCLUSIONS Histogram parameters derived from SyMRI may serve as a potential biomarker for discriminating relevant histopathological features, including histological differentiation grade, HPV infection, Ki-67, EGFR and p53 statuses.
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Bober Z, Podgórski R, Aebisher D, Cieślar G, Kawczyk-Krupka A, Bartusik-Aebisher D. Cellular 1H MR Relaxation Times in Healthy and Cancer Three-Dimensional (3D) Breast Cell Culture. Int J Mol Sci 2023; 24:ijms24054735. [PMID: 36902163 PMCID: PMC10002569 DOI: 10.3390/ijms24054735] [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: 11/22/2022] [Revised: 02/24/2023] [Accepted: 02/26/2023] [Indexed: 03/05/2023] Open
Abstract
Noninvasive measurements of 1H Magnetic Resonance Imaging (MR) relaxation times in a three-dimensional (3D) cell culture construct are presented. Trastuzumab was used as a pharmacological component delivered to the cells in vitro. The purpose of this study was to evaluate the Trastuzumab delivery by relaxation times in 3D cell cultures. The bioreactor has been designed and used for 3D cell cultures. Four bioreactors were prepared, two with normal cells and two with breast cancer cells. The relaxation times of HTB-125 and CRL 2314 cell cultures were determined. An immunohistochemistry (IHC) test was performed before MRI measurements to confirm the amount of HER2 protein in the CRL-2314 cancer cells. The results showed that the relaxation time of CRL2314 cells is lower than normal HTB-125 cells in both cases, before and after treatment. An analysis of the results showed that 3D culture studies have potential in evaluating treatment efficacy using relaxation times measurements with a field of 1.5 Tesla. The use 1H MRI relaxation times allows for the visualization of cell viability in response to treatment.
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Affiliation(s)
- Zuzanna Bober
- Department of Photomedicine and Physical Chemistry, Medical College, Rzeszów University, 35-310 Rzeszów, Poland
| | - Rafał Podgórski
- Department of Biochemistry and General Chemistry, Medical College, Rzeszów University, 35-310 Rzeszów, Poland
| | - David Aebisher
- Department of Photomedicine and Physical Chemistry, Medical College, Rzeszów University, 35-310 Rzeszów, Poland
| | - Grzegorz Cieślar
- Department of Internal Medicine, Angiology and Physical Medicine, Center for Laser Diagnostics and Therapy, Faculty of Medical Sciences in Zabrze, Medical University of Silesia, 40-055 Katowice, Poland
| | - Aleksandra Kawczyk-Krupka
- Department of Internal Medicine, Angiology and Physical Medicine, Center for Laser Diagnostics and Therapy, Faculty of Medical Sciences in Zabrze, Medical University of Silesia, 40-055 Katowice, Poland
- Correspondence: (A.K.-K.); (D.B.-A.)
| | - Dorota Bartusik-Aebisher
- Department of Biochemistry and General Chemistry, Medical College, Rzeszów University, 35-310 Rzeszów, Poland
- Correspondence: (A.K.-K.); (D.B.-A.)
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Yang F, Li Y, Li X, Yu X, Zhao Y, Li L, Xie L, Lin M. The utility of texture analysis based on quantitative synthetic magnetic resonance imaging in nasopharyngeal carcinoma: a preliminary study. BMC Med Imaging 2023; 23:15. [PMID: 36698156 PMCID: PMC9875491 DOI: 10.1186/s12880-023-00968-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2022] [Accepted: 01/13/2023] [Indexed: 01/27/2023] Open
Abstract
BACKGROUND Magnetic resonance imaging (MRI) is commonly used for the diagnosis of nasopharyngeal carcinoma (NPC) and occipital clivus (OC) invasion, but a proportion of lesions may be missed using non-enhanced MRI. The purpose of this study is to investigate the diagnostic performance of synthetic magnetic resonance imaging (SyMRI) in differentiating NPC from nasopharyngeal hyperplasia (NPH), as well as evaluating OC invasion. METHODS Fifty-nine patients with NPC and 48 volunteers who underwent SyMRI examination were prospectively enrolled. Eighteen first-order features were extracted from VOIs (primary tumours, benign mucosa, and OC). Statistical comparisons were conducted between groups using the independent-samples t-test and the Mann-Whitney U test to select significant parameters. Multiple diagnostic models were then constructed using multivariate logistic analysis. The diagnostic performance of the models was calculated by receiver operating characteristics (ROC) curve analysis and compared using the DeLong test. Bootstrap and 5-folds cross-validation were applied to avoid overfitting. RESULTS The T1, T2 and PD map-derived models had excellent diagnostic performance in the discrimination between NPC and NPH in volunteers, with area under the curves (AUCs) of 0.975, 0.972 and 0.986, respectively. Besides, SyMRI models also showed excellent performance in distinguishing OC invasion from non-invasion (AUC: 0.913-0.997). Notably, the T1 map-derived model showed the highest diagnostic performance with an AUC, sensitivity, specificity, and accuracy of 0.997, 96.9%, 97.9% and 97.5%, respectively. By using 5-folds cross-validation, the bias-corrected AUCs were 0.965-0.984 in discriminating NPC from NPH and 0.889-0.975 in discriminating OC invasion from OC non-invasion. CONCLUSIONS SyMRI combined with first-order parameters showed excellent performance in differentiating NPC from NPH, as well as discriminating OC invasion from non-invasion.
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Affiliation(s)
- Fan Yang
- grid.506261.60000 0001 0706 7839Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021 China
| | - Yujie Li
- grid.506261.60000 0001 0706 7839Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021 China
| | - Xiaolu Li
- grid.506261.60000 0001 0706 7839Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021 China
| | - Xiaoduo Yu
- grid.506261.60000 0001 0706 7839Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021 China
| | - Yanfeng Zhao
- grid.506261.60000 0001 0706 7839Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021 China
| | - Lin Li
- grid.506261.60000 0001 0706 7839Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021 China
| | - Lizhi Xie
- MR Research China, GE Healthcare, Beijing, China
| | - Meng Lin
- grid.506261.60000 0001 0706 7839Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021 China
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Zhu L, Lu W, Wang F, Wang Y, Wu PY, Zhou J, Liu H. Study of T2 mapping in quantifying and discriminating uterine lesions under different magnetic field strengths: 1.5 T vs. 3.0 T. BMC Med Imaging 2023; 23:1. [PMID: 36600192 PMCID: PMC9811773 DOI: 10.1186/s12880-022-00960-w] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2022] [Accepted: 12/30/2022] [Indexed: 01/06/2023] Open
Abstract
BACKGROUND MRI is the best imaging tool for the evaluation of uterine tumors, but conventional MRI diagnosis results rely on radiologists and contrast agents (if needed). As a new objective, reproducible and contrast-agent free quantification technique, T2 mapping has been applied to a number of diseases, but studies on the evaluation of uterine lesions and the influence of magnetic field strength are few. Therefore, the aim of this study was to systematically investigate and compare the performance of T2 mapping as a nonenhanced imaging tool in discriminating common uterine lesions between 1.5 T and 3.0 T MRI systems. METHODS A total of 50 healthy subjects and 126 patients with suspected uterine lesions were enrolled in our study, and routine uterine MRI sequences with additional T2 mapping sequences were performed. T2 maps were calculated by monoexponential fitting using a custom code in MATLAB. T2 values of normal uterine structures in the healthy group and lesions (benign: adenomyosis, myoma, endometrial polyps; malignant: cervical cancer, endometrial carcinoma) in the patient group were collected. The differences in T2 values between 1.5 T MRI and 3.0 T MRI in any normal structure or lesion were compared. The comparison of T2 values between benign and malignant lesions was also performed under each magnetic field strength, and the diagnostic efficacies of the T2 value obtained through receiver operating characteristic (ROC) analysis were compared between 1.5 T and 3.0 T. RESULTS The mean T2 value of any normal uterine structure or uterine lesion under 3.0 T MRI was significantly lower than that under 1.5 T MRI (p < 0.05). There were significant differences in T2 values between each lesion subgroup under both 1.5 T and 3.0 T MRI. Moreover, the T2 values of benign lesions (71.1 ± 22.0 ms at 1.5 T and 63.4 ± 19.1 ms at 3.0 T) were also significantly lower than those of malignant lesions (101.1 ± 4.5 ms at 1.5 T and 93.5 ± 5.1 ms at 3.0 T) under both field strengths. In the aspect of differentiating benign from malignant lesions, the area under the curve of the T2 value under 3.0 T (0.94) was significantly higher than that under 1.5 T MRI (0.90) (p = 0.02). CONCLUSION T2 mapping can be a potential tool for quantifying common uterine lesions, and it has better performance in distinguishing benign from malignant lesions under 3.0 T MRI.
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Affiliation(s)
- Liuhong Zhu
- grid.8547.e0000 0001 0125 2443Department of Radiology, Zhongshan Hospital (Xiamen), Fudan University, Jihun Road No. 668, Huli District, Xiamen, Fujian China ,Xiamen Municipal Clinical Research Center, Xiamen for Medical Imaging, Xiamen, 361015 China
| | - Weihong Lu
- grid.413087.90000 0004 1755 3939Department of Gynaecology Department, Zhongshan Hospital (Xiamen), Fudan University, Xiamen, Fujian China
| | - Funan Wang
- grid.8547.e0000 0001 0125 2443Department of Radiology, Zhongshan Hospital (Xiamen), Fudan University, Jihun Road No. 668, Huli District, Xiamen, Fujian China
| | - Yanwei Wang
- Department of Radiology, The Second Affiliated Hospital of Xiamen Medical College, Xiamen, Fujian China
| | | | - Jianjun Zhou
- grid.8547.e0000 0001 0125 2443Department of Radiology, Zhongshan Hospital (Xiamen), Fudan University, Jihun Road No. 668, Huli District, Xiamen, Fujian China ,grid.413087.90000 0004 1755 3939Department of Radiology, Zhongshan Hospital Fudan University, Xuhui District, Fenglin Road No.180, Shanghai, 200032 China
| | - Hao Liu
- grid.413087.90000 0004 1755 3939Department of Radiology, Zhongshan Hospital Fudan University, Xuhui District, Fenglin Road No.180, Shanghai, 200032 China
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Wang P, Hu S, Wang X, Ge Y, Zhao J, Qiao H, Chang J, Dou W, Zhang H. Synthetic MRI in differentiating benign from metastatic retropharyngeal lymph node: combination with diffusion-weighted imaging. Eur Radiol 2023; 33:152-161. [PMID: 35951044 DOI: 10.1007/s00330-022-09027-4] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2022] [Revised: 06/29/2022] [Accepted: 07/13/2022] [Indexed: 06/15/2023]
Abstract
OBJECTIVES This study aimed to evaluate the synthetic MRI (syMRI), its combination with diffusion-weighted imaging (DWI), and morphological features for discriminating benign from metastatic retropharyngeal lymph nodes (RLNs). METHODS Fifty-eight patients with a total of 63 RLNs (21 benign and 42 metastatic) were enrolled. The mean and standard deviation of syMRI-derived relaxometry parameters (T1, T2, PD; T1SD, T2SD, PDSD) were obtained from two different regions of interest (namely, partial-lesion and full-lesion ROI). The parameters derived from benign and metastatic RLNs were compared using Student's t or chi-square tests. Logistic regression analysis was used to construct a multi-parameter model of syMRI, syMRI + DWI, and syMRI + DWI + morphological features. Areas under the curve (AUC) were compared using the DeLong test to determine the best diagnostic approach. RESULTS Benign RLNs had significantly higher T1, T2, PD, and T1SD values compared with metastatic RLNs in both partial-lesion and full-lesion ROI (all p < 0.05). The T1SD obtained from full-lesion ROI showed the best diagnostic performance among all syMRI-derived single parameters. The AUC of combined syMRI multiple parameters (T1, T2, PD, T1SD) were higher than those of any single parameter from syMRI. The combination of synthetic MRI and DWI can improve the AUC regardless of ROI delineation. Furthermore, the combination of synthetic MRI, DWI-derived quantitative parameters, and morphological features can significantly improve the overall diagnostic performance. CONCLUSIONS The value of syMRI has been validated in differential diagnosis of benign and metastatic RLNs, and syMRI + DWI + morphological features can further improve the diagnostic efficiency for discriminating these two entities. KEY POINTS • Synthetic MRI was useful in differential diagnosis of benign and metastatic RLNs. • The combination of syMRI, DWI, and morphological features can significantly improve the diagnostic efficiency.
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Affiliation(s)
- Peng Wang
- Department of Radiology, Affiliated Hospital of Jiangnan University, 1000 Hefeng Road, Wuxi, 214122, People's Republic of China
| | - Shudong Hu
- Department of Radiology, Affiliated Hospital of Jiangnan University, 1000 Hefeng Road, Wuxi, 214122, People's Republic of China
| | - Xiuyu Wang
- Department of Radiology, Affiliated Hospital of Jiangnan University, 1000 Hefeng Road, Wuxi, 214122, People's Republic of China
| | - Yuxi Ge
- Department of Radiology, Affiliated Hospital of Jiangnan University, 1000 Hefeng Road, Wuxi, 214122, People's Republic of China
| | - Jing Zhao
- Department of Radiology, Affiliated Hospital of Jiangnan University, 1000 Hefeng Road, Wuxi, 214122, People's Republic of China
| | - Hongyan Qiao
- Department of Radiology, Affiliated Hospital of Jiangnan University, 1000 Hefeng Road, Wuxi, 214122, People's Republic of China
| | - Jun Chang
- Department of Radiology, Affiliated Hospital of Jiangnan University, 1000 Hefeng Road, Wuxi, 214122, People's Republic of China
| | - Weiqiang Dou
- GE Healthcare, MR Research China, Beijing, 100176, People's Republic of China
| | - Heng Zhang
- Department of Radiology, Affiliated Hospital of Jiangnan University, 1000 Hefeng Road, Wuxi, 214122, People's Republic of China.
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Zhang L, Hao J, Guo J, Zhao X, Yin X. Predicting of Ki-67 Expression Level Using Diffusion-Weighted and Synthetic Magnetic Resonance Imaging in Invasive Ductal Breast Cancer. Breast J 2023; 2023:6746326. [PMID: 37063453 PMCID: PMC10098409 DOI: 10.1155/2023/6746326] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2022] [Revised: 02/26/2023] [Accepted: 03/27/2023] [Indexed: 04/18/2023]
Abstract
Objectives To investigate the association between quantitative parameters generated using synthetic magnetic resonance imaging (SyMRI) and diffusion-weighted imaging (DWI) and Ki-67 expression level in patients with invasive ductal breast cancer (IDC). Method We retrospectively reviewed the records of patients with IDC who underwent SyMRI and DWI before treatment. Precontrast and postcontrast relaxation times (T1, longitudinal; T2, transverse), proton density (PD) parameters, and apparent diffusion coefficient (ADC) values were measured in breast lesions. Univariate and multivariate regression analyses were performed to screen for statistically significant variables to differentiate the high (≥30%) and low (<30%) Ki-67 expression groups. Their performance was evaluated by receiver operating characteristic (ROC) curve analysis. Results We analyzed 97 patients. Multivariate regression analysis revealed that the high Ki-67 expression group (n = 57) had significantly higher parameters generated using SyMRI (pre-T1, p=0.001) and lower ADC values (p=0.036) compared with the low Ki-67 expression group (n = 40). Pre-T1 showed the best diagnostic performance for predicting the Ki-67 expression level in patients with invasive ductal breast cancer (areas under the ROC curve (AUC), 0.711; 95% confidence interval (CI), 0.609-0.813). Conclusions Pre-T1 could be used to predict the pretreatment Ki-67 expression level in invasive ductal breast cancer.
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Affiliation(s)
- Liying Zhang
- Third Affiliated Hospital of Zhengzhou University, Department of Radiology, Zhengzhou, China
| | - Jisen Hao
- Third Affiliated Hospital of Zhengzhou University, Department of Radiology, Zhengzhou, China
| | - Jia Guo
- Third Affiliated Hospital of Zhengzhou University, Department of Radiology, Zhengzhou, China
| | - Xin Zhao
- Third Affiliated Hospital of Zhengzhou University, Department of Radiology, Zhengzhou, China
| | - Xing Yin
- Third Affiliated Hospital of Zhengzhou University, Department of Radiology, Zhengzhou, China
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Zhang W, Lu N, He H, Liu H, Zhu F, Ma L, Luo Y, Qian L, Meng T, Xie C. Application of synthetic magnetic resonance imaging and DWI for evaluation of prognostic factors in cervical carcinoma: a prospective preliminary study. Br J Radiol 2023; 96:20220596. [PMID: 36341699 PMCID: PMC10997024 DOI: 10.1259/bjr.20220596] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2022] [Revised: 10/13/2022] [Accepted: 10/29/2022] [Indexed: 11/09/2022] Open
Abstract
OBJECTIVES To determine the values of quantitative metrics derived from synthetic MRI (SyMRI) and apparent diffusion coefficient (ADC) in evaluating the prognostic factors of cervical carcinoma (CC). METHODS In this prospective study, 74 patients with pathologically confirmed CC were enrolled. Pretreatment quantitative metrics including T1, T2 and ADC values were obtained from SyMRI and diffusion-weighted imaging (DWI) sequences. The values of all metrics were compared for different prognostic features using Student's t-test or Mann-Whitney U-test. The receiver operating characteristic (ROC) curve and multivariate logistic regression analysis were utilized to evaluate the diagnostic performance of quantitative variables. RESULTS T1 and T2 values of parametrial involvement (PMI)-negative were significantly higher than those of PMI-positive (p = 0.002 and < 0.001), while ADC values did not show a significant difference. The area under curve (AUC) of T1 and T2 values for identifying PMI were 0.743 and 0.831. Only the T2 values showed a significant difference between the lymphovascular space involvement (LVSI)-negative and LVSI-positive (p < 0.001), and the AUC of T2 values for discriminating LVSI was 0.814. The differences of T1, T2, and ADC values between the well/moderately and the poorly differentiated CC were significant (all p < 0.001). The AUCs of T1, T2 and ADC values for predicting differentiation grades were 0.762, 0.830, and 0.808. The combined model of all metrics proved to achieve good diagnostic performance with the AUC of 0.866. CONCLUSION SyMRI may be a potential noninvasive tool for assessing the prognostic factors such as PMI, LVSI, and differentiation grades in CC. Moreover, the overall diagnostic performances of synthetic quantitative metrics were superior to the ADC values, especially in identifying PMI and LVSI. ADVANCES IN KNOWLEDGE This is the first study to assess the utility of SyMRI-derived parameters and ADC value in evaluating the prognostic factors in CC.
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Affiliation(s)
- Weijing Zhang
- Department of Medical imaging, Sun Yat-Sen University Cancer
Center, State Key Laboratory of Oncology in South China, Collaborative
Innovation Center for Cancer Medicine, Guangdong Key Laboratory of
Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangzhou,
China
| | - Nian Lu
- Department of Medical imaging, Sun Yat-Sen University Cancer
Center, State Key Laboratory of Oncology in South China, Collaborative
Innovation Center for Cancer Medicine, Guangdong Key Laboratory of
Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangzhou,
China
| | - Haoqiang He
- Department of Medical imaging, Sun Yat-Sen University Cancer
Center, State Key Laboratory of Oncology in South China, Collaborative
Innovation Center for Cancer Medicine, Guangdong Key Laboratory of
Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangzhou,
China
| | - Huiming Liu
- Department of Medical imaging, Sun Yat-Sen University Cancer
Center, State Key Laboratory of Oncology in South China, Collaborative
Innovation Center for Cancer Medicine, Guangdong Key Laboratory of
Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangzhou,
China
| | - Fengting Zhu
- Department of Medical imaging, Sun Yat-Sen University Cancer
Center, State Key Laboratory of Oncology in South China, Collaborative
Innovation Center for Cancer Medicine, Guangdong Key Laboratory of
Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangzhou,
China
| | - Lidi Ma
- Department of Medical imaging, Sun Yat-Sen University Cancer
Center, State Key Laboratory of Oncology in South China, Collaborative
Innovation Center for Cancer Medicine, Guangdong Key Laboratory of
Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangzhou,
China
| | - Yingwei Luo
- Department of Medical imaging, Sun Yat-Sen University Cancer
Center, State Key Laboratory of Oncology in South China, Collaborative
Innovation Center for Cancer Medicine, Guangdong Key Laboratory of
Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangzhou,
China
| | - Long Qian
- Department of Biomedical Engineering, College of Engineering,
Peking University, Beijing, China
| | - Tiebao Meng
- Department of Medical imaging, Sun Yat-Sen University Cancer
Center, State Key Laboratory of Oncology in South China, Collaborative
Innovation Center for Cancer Medicine, Guangdong Key Laboratory of
Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangzhou,
China
| | - Chuanmiao Xie
- Department of Medical imaging, Sun Yat-Sen University Cancer
Center, State Key Laboratory of Oncology in South China, Collaborative
Innovation Center for Cancer Medicine, Guangdong Key Laboratory of
Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangzhou,
China
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Meng L, Zhao X, Guo J, Lu L, Cheng M, Xing Q, Shang H, Wang K, Zhang B, Lei D, Zhang X. Evaluation of the differentiation of benign and malignant breast lesions using synthetic relaxometry and the Kaiser score. Front Oncol 2022; 12:964078. [PMID: 36303839 PMCID: PMC9595598 DOI: 10.3389/fonc.2022.964078] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2022] [Accepted: 09/26/2022] [Indexed: 12/24/2022] Open
Abstract
Objective To investigate whether there is added value of quantitative parameters from synthetic magnetic resonance imaging (SyMRI) as a complement to the Kaiser score (KS) to differentiate benign and malignant breast lesions. Materials and methods In this single-institution study, 122 patients who underwent breast MRI from March 2020 to May 2021 were retrospectively analyzed. SyMRI and dynamic contrast-enhanced MRI were performed using a 3.0-T system. Two experienced radiologists independently assigned the KS and measured the quantitative values of T1 relaxation time (T1), T2 relaxation time (T2), and proton density (PD) from SyMRI. Pathology was regarded as the gold standard. The diagnostic values were compared using the appropriate statistical tests. Results There were 122 lesions (86 malignant and 36 benign) in 122 women. The T1 value was identified as the only independent factor for the differentiation of malignant and benign lesions. The diagnostic accuracy of incorporating the T1 into the KS protocol (T1+KS) was 95.1% and 92.1% for all lesions (ALL) and The American College of Radiology (ACR) Breast Imaging Reporting and Data System (BI-RADS) category 4 lesions, respectively, which was significantly higher than that of either T1 (ALL: 82.8%, P = 0.0001; BI-RADS 4: 78.9%, P = 0.002) or KS (ALL: 90.2%, P = 0.031; BI-RADS 4: 84.2%, P = 0.031) alone. The sensitivity and specificity of T1+KS were also higher than those of the T1 or KS alone. The combined diagnosis could have avoided another 15.6% biopsies compared with using KS alone. Conclusions Incorporating T1 into the KS protocol improved both the sensitivity and specificity to differentiate benign and malignant breast lesions, thus avoiding unnecessary invasive procedures.
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Affiliation(s)
- Lingsong Meng
- Department of Radiology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Academy of Medical Sciences, Zhengzhou University, Zhengzhou, China
| | - Xin Zhao
- Department of Radiology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Jinxia Guo
- General Electric (GE) Healthcare, MR Research China, Beijing, China
| | - Lin Lu
- Department of Radiology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Meiying Cheng
- Department of Radiology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Qingna Xing
- Department of Radiology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Honglei Shang
- Department of Radiology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Kaiyu Wang
- General Electric (GE) Healthcare, MR Research China, Beijing, China
| | - Bohao Zhang
- Henan Key Laboratory of Child Brain Injury, Institute of Neuroscience and the Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Dongmei Lei
- Department of Pathology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Xiaoan Zhang
- Department of Radiology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- *Correspondence: Xiaoan Zhang,
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Li J, Gao X, Dominik Nickel M, Cheng J, Zhu J. Native T1 mapping for differentiating the histopathologic type, grade, and stage of rectal adenocarcinoma: a pilot study. Cancer Imaging 2022; 22:30. [PMID: 35715848 PMCID: PMC9204907 DOI: 10.1186/s40644-022-00461-7] [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: 11/11/2021] [Accepted: 05/12/2022] [Indexed: 11/10/2022] Open
Abstract
Background Previous studies have indicated that T1 relaxation time could be utilized for the analysis of tissue characteristics. T1 mapping technology has been gradually used on research of body tumor. In this study, the application of native T1 relaxation time for differentiating the histopathologic type, grade, and stage of rectal adenocarcinoma was investigated. Methods One hundred and twenty patients with pathologically confirmed rectal adenocarcinoma were retrospectively evaluated. All patients underwent high-resolution anatomical magnetic resonance imaging (MRI), diffusion-weighted imaging (DWI), and T1 mapping sequences. Parameters of T1 relaxation time and apparent diffusion coefficient (ADC) were measured between the different groups. The diagnostic power was evaluated though the receiver operating characteristic (ROC) curve. Results The T1 and ADC values varied significantly between rectal mucinous adenocarcinoma (MC) and non-mucinous rectal adenocarcinoma (AC) ([1986.1 ± 163.3 ms] vs. [1562.3 ± 244.2 ms] and [1.38 ± 0.23 × 10−3mm2/s] vs. [1.03 ± 0.15 × 10−3mm2/s], respectively; P < 0.001). In the AC group, T1 relaxation time were significantly different between the low- and high-grade adenocarcinoma cases ([1508.7 ± 188.6 ms] vs. [1806.5 ± 317.5 ms], P < 0.001), while no differences were apparent in the ADC values ([1.03 ± 0.14 × 10−3mm2/s] vs. [1.04 ± 0.18 × 10−3mm2/s], P > 0.05). No significant differences in T1 and ADC values were identified between the different T and N stage groups for both MC and AC (all P > 0.05). Conclusions Native T1 relaxation time can be used to discriminate MC from AC. The T1 relaxation time was helpful for differentiating the low- and high-grade of AC.
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Affiliation(s)
- Juan Li
- Department of MRI, the First Affiliated Hospital of Zhengzhou University, No.1, Jianshe Dong Road, Zhengzhou, 450052, China
| | - Xuemei Gao
- Department of MRI, the First Affiliated Hospital of Zhengzhou University, No.1, Jianshe Dong Road, Zhengzhou, 450052, China
| | | | - Jingliang Cheng
- Department of MRI, the First Affiliated Hospital of Zhengzhou University, No.1, Jianshe Dong Road, Zhengzhou, 450052, China.
| | - Jinxia Zhu
- MR Collaboration, Siemens Healthcare Ltd, Beijing, 100000, China
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Quantitative Synthetic Magnetic Resonance Imaging for Brain Metastases: A Feasibility Study. Cancers (Basel) 2022; 14:cancers14112651. [PMID: 35681631 PMCID: PMC9179589 DOI: 10.3390/cancers14112651] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Revised: 05/16/2022] [Accepted: 05/20/2022] [Indexed: 02/01/2023] Open
Abstract
Simple Summary This preliminary study aims to characterize brain metastases (BM) using T1 and T2 maps generated from newer, rapid, synthetic MRI (MAGnetic resonance image Compilation; MAGiC) in a clinical setting. In addition, synthetic MR could provide contrast images analogous to standard T1- and T2-weighted images. The reproducibility and repeatability of this method have been previously established for brain imaging. This study reports and analyzes the quantitative T1 and T2 values for 11 BM patients (17 BM lesions) with a total of 82 regions of interest (ROIs) delineated by an experienced neuroradiologist. The initial results, which need to be further validated in a larger patient cohort, demonstrated the ability of T1 and T2 metric values to characterize BMs and normal-appearing brain tissues. The T1 and T2 metrics could be potential surrogate biomarkers for BM free water content (cellularity) and tumor morphology, respectively. Abstract The present preliminary study aims to characterize brain metastases (BM) using T1 and T2 maps generated from newer, rapid, synthetic MRI (MAGnetic resonance image Compilation; MAGiC) in a clinical setting. We acquired synthetic MRI data from 11 BM patients on a 3T scanner. A multiple-dynamic multiple-echo (MDME) sequence was used for data acquisition and synthetic image reconstruction, including post-processing. MDME is a multi-contrast sequence that enables absolute quantification of physical tissue properties, including T1 and T2, independent of the scanner settings. In total, 82 regions of interest (ROIs) were analyzed, which were obtained from both normal-appearing brain tissue and BM lesions. The mean values obtained from the 48 normal-appearing brain tissue regions and 34 ROIs of BM lesions (T1 and T2) were analyzed using standard statistical methods. The mean T1 and T2 values were 1143 ms and 78 ms, respectively, for normal-appearing gray matter, 701 ms and 64 ms for white matter, and 4206 ms and 390 ms for cerebrospinal fluid. For untreated BMs, the mean T1 and T2 values were 1868 ms and 100 ms, respectively, and 2211 ms and 114 ms for the treated group. The quantitative T1 and T2 values generated from synthetic MRI can characterize BM and normal-appearing brain tissues.
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[Differential diagnosis of benign and malignant breast lesions using quantitative synthetic magnetic resonance imaging]. NAN FANG YI KE DA XUE XUE BAO = JOURNAL OF SOUTHERN MEDICAL UNIVERSITY 2022; 42:457-462. [PMID: 35527481 PMCID: PMC9085598 DOI: 10.12122/j.issn.1673-4254.2022.04.01] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 01/24/2023]
Abstract
OBJECTIVE To investigate the value of quantitative synthetic magnetic resonance imaging (SyMRI) in distinguishing between benign and malignant breast lesions. METHODS We retrospectively collected data of preoperative conventional MRI and multi-dynamic multi-echo sequences from 95 patients with breast lesions showing mass-type enhancement on DCE-MRI, including 27 patients with benign lesions and 68 with malignant lesions. The MRI features of the lesions (shape, margin, internal enhancement pattern, time-signal intensity curve, and T2WI signal) were analyzed, and for each lesion, SyMRI-generated quantitative parameters including T1 and T2 relaxation time and proton density (PD) were measured before and after enhancement and recorded as T1p, T2p, PDp and T1e, T2e, and PDe, respectively. The relative change rate of each parameter was calculated. Logistic regression and all-subset regression analyses were performed for variable selection to construct diagnostic models of the breast lesions, and receiver-operating characteristic (ROC) analysis was used to assess the performance of each model for differentiation of benign and malignant lesions. RESULTS There were significant differences in the MRI features between benign and malignant lesions (P < 0.05). All the SyMRI-generated quantitative parameters, with the exception of T2e and Pdp, showed significant differences between benign and malignant lesions (P < 0.05). Among the constructed diagnostic models, the model based on all the DCE-MRI features combined with SyMRI parameters T2p and T1e (DCE-MRI+T2p+T1e) showed the best performance in the differential diagnosis malignant breast masses with an AUC of 0.995 (95% CI: 0.983-1.000). CONCLUSION Quantitative SyMRI can be used for differential diagnosis of benign and malignant breast lesions.
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Feasibility study of 2D Dixon-Magnetic Resonance Fingerprinting (MRF) of breast cancer. Eur J Radiol Open 2022; 9:100453. [DOI: 10.1016/j.ejro.2022.100453] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2022] [Revised: 10/31/2022] [Accepted: 11/05/2022] [Indexed: 11/17/2022] Open
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