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Kader A, Snellings J, Adams LC, Gottheil P, Mangarova DB, Heyl JL, Kaufmann JO, Moeckel J, Brangsch J, Auer TA, Collettini F, Sauer F, Hamm B, Käs J, Sack I, Makowski MR, Braun J. Sensitivity of magnetic resonance elastography to extracellular matrix and cell motility in human prostate cancer cell line-derived xenograft models. BIOMATERIALS ADVANCES 2024; 161:213884. [PMID: 38723432 DOI: 10.1016/j.bioadv.2024.213884] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Revised: 04/05/2024] [Accepted: 04/26/2024] [Indexed: 06/04/2024]
Abstract
Prostate cancer (PCa) is a significant health problem in the male population of the Western world. Magnetic resonance elastography (MRE), an emerging medical imaging technique sensitive to mechanical properties of biological tissues, detects PCa based on abnormally high stiffness and viscosity values. Yet, the origin of these changes in tissue properties and how they correlate with histopathological markers and tumor aggressiveness are largely unknown, hindering the use of tumor biomechanical properties for establishing a noninvasive PCa staging system. To infer the contributions of extracellular matrix (ECM) components and cell motility, we investigated fresh tissue specimens from two PCa xenograft mouse models, PC3 and LNCaP, using magnetic resonance elastography (MRE), diffusion-weighted imaging (DWI), quantitative histology, and nuclear shape analysis. Increased tumor stiffness and impaired water diffusion were observed to be associated with collagen and elastin accumulation and decreased cell motility. Overall, LNCaP, while more representative of clinical PCa than PC3, accumulated fewer ECM components, induced less restriction of water diffusion, and exhibited increased cell motility, resulting in overall softer and less viscous properties. Taken together, our results suggest that prostate tumor stiffness increases with ECM accumulation and cell adhesion - characteristics that influence critical biological processes of cancer development. MRE paired with DWI provides a powerful set of imaging markers that can potentially predict prostate tumor development from benign masses to aggressive malignancies in patients. STATEMENT OF SIGNIFICANCE: Xenograft models of human prostate tumor cell lines, allowing correlation of microstructure-sensitive biophysical imaging parameters with quantitative histological methods, can be investigated to identify hallmarks of cancer.
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Affiliation(s)
- Avan Kader
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Charitéplatz 1, 10117 Berlin, Germany; Department of Biology, Chemistry and Pharmacy, Institute of Biology, Freie Universität Berlin, Königin-Luise-Str. 1-3, 14195 Berlin, Germany; Technical University of Munich, Department of Diagnostic and Interventional Radiology, Ismaninger Str. 22, 81675 Munich, Germany.
| | - Joachim Snellings
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Charitéplatz 1, 10117 Berlin, Germany.
| | - Lisa C Adams
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Charitéplatz 1, 10117 Berlin, Germany; Technical University of Munich, Department of Diagnostic and Interventional Radiology, Ismaninger Str. 22, 81675 Munich, Germany.
| | - Pablo Gottheil
- Peter Debye Institute for Soft Matter Physics, Leipzig University, Linnéstraße 5, 04103 Leipzig, Germany
| | - Dilyana B Mangarova
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Charitéplatz 1, 10117 Berlin, Germany.
| | - Jennifer L Heyl
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Charitéplatz 1, 10117 Berlin, Germany.
| | - Jan O Kaufmann
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Charitéplatz 1, 10117 Berlin, Germany; Bundesanstalt für Materialforschung und -prüfung (BAM), Division 1.5 Protein Analysis, Richard-Willstätter-Str. 11, 12489 Berlin, Germany.
| | - Jana Moeckel
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Charitéplatz 1, 10117 Berlin, Germany.
| | - Julia Brangsch
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Charitéplatz 1, 10117 Berlin, Germany; Technical University of Munich, Department of Diagnostic and Interventional Radiology, Ismaninger Str. 22, 81675 Munich, Germany.
| | - Timo A Auer
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Charitéplatz 1, 10117 Berlin, Germany; Berlin Insitute of Health (BIH), Berlin, Germany.
| | - Federico Collettini
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Charitéplatz 1, 10117 Berlin, Germany; Berlin Insitute of Health (BIH), Berlin, Germany.
| | - Frank Sauer
- Peter Debye Institute for Soft Matter Physics, Leipzig University, Linnéstraße 5, 04103 Leipzig, Germany.
| | - Bernd Hamm
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Charitéplatz 1, 10117 Berlin, Germany.
| | - Josef Käs
- Peter Debye Institute for Soft Matter Physics, Leipzig University, Linnéstraße 5, 04103 Leipzig, Germany.
| | - Ingolf Sack
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Charitéplatz 1, 10117 Berlin, Germany.
| | - Marcus R Makowski
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Charitéplatz 1, 10117 Berlin, Germany; Technical University of Munich, Department of Diagnostic and Interventional Radiology, Ismaninger Str. 22, 81675 Munich, Germany; King's College London, School of Biomedical Engineering and Imaging Sciences, St Thomas' Hospital, Westminster Bridge Road, London SE1 7EH, United Kingdom.
| | - Jürgen Braun
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Charitéplatz 1, 10117 Berlin, Germany.
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Wang QF, Li ZW, Zhou HF, Zhu KZ, Wang YJ, Wang YQ, Zhang YW. Predicting the prognosis of hepatic arterial infusion chemotherapy in hepatocellular carcinoma. World J Gastrointest Oncol 2024; 16:2380-2393. [DOI: 10.4251/wjgo.v16.i6.2380] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/18/2023] [Revised: 01/19/2024] [Accepted: 04/03/2024] [Indexed: 06/14/2024] Open
Abstract
Hepatic artery infusion chemotherapy (HAIC) has good clinical efficacy in the treatment of advanced hepatocellular carcinoma (HCC); however, its efficacy varies. This review summarized the ability of various markers to predict the efficacy of HAIC and provided a reference for clinical applications. As of October 25, 2023, 51 articles have been retrieved based on keyword predictions and HAIC. Sixteen eligible articles were selected for inclusion in this study. Comprehensive literature analysis found that methods used to predict the efficacy of HAIC include serological testing, gene testing, and imaging testing. The above indicators and their combined forms showed excellent predictive effects in retrospective studies. This review summarized the strategies currently used to predict the efficacy of HAIC in middle and advanced HCC, analyzed each marker's ability to predict HAIC efficacy, and provided a reference for the clinical application of the prediction system.
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Affiliation(s)
- Qi-Feng Wang
- Department of Hepatobiliary Pancreatic Center, Beijing Tsinghua Changgung Hospital Affiliated to Tsinghua University, Beijing 102218, China
- Department of Hepatobiliary and Pancreatic Surgery, Qinghai University Affiliated Hospital, Xining 810000, Qinghai Province, China
| | - Zong-Wei Li
- Department of Hepatobiliary and Pancreatic Surgery, Qinghai University Affiliated Hospital, Xining 810000, Qinghai Province, China
| | - Hai-Feng Zhou
- Department of Hepatobiliary and Pancreatic Surgery, Qinghai University Affiliated Hospital, Xining 810000, Qinghai Province, China
| | - Kun-Zhong Zhu
- Department of Hepatobiliary and Pancreatic Surgery, Qinghai University Affiliated Hospital, Xining 810000, Qinghai Province, China
| | - Ya-Jing Wang
- Department of Hepatobiliary Pancreatic Center, Beijing Tsinghua Changgung Hospital Affiliated to Tsinghua University, Beijing 102218, China
| | - Ya-Qin Wang
- Department of Hepatobiliary Pancreatic Center, Beijing Tsinghua Changgung Hospital Affiliated to Tsinghua University, Beijing 102218, China
| | - Yue-Wei Zhang
- Department of Hepatobiliary Pancreatic Center, Beijing Tsinghua Changgung Hospital Affiliated to Tsinghua University, Beijing 102218, China
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Wang QF, Li ZW, Zhou HF, Zhu KZ, Wang YJ, Wang YQ, Zhang YW. Predicting the prognosis of hepatic arterial infusion chemotherapy in hepatocellular carcinoma. World J Gastrointest Oncol 2024; 16:2368-2381. [DOI: 10.4251/wjgo.v16.i6.2368] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/18/2023] [Revised: 01/19/2024] [Accepted: 04/03/2024] [Indexed: 06/13/2024] Open
Abstract
Hepatic artery infusion chemotherapy (HAIC) has good clinical efficacy in the treatment of advanced hepatocellular carcinoma (HCC); however, its efficacy varies. This review summarized the ability of various markers to predict the efficacy of HAIC and provided a reference for clinical applications. As of October 25, 2023, 51 articles have been retrieved based on keyword predictions and HAIC. Sixteen eligible articles were selected for inclusion in this study. Comprehensive literature analysis found that methods used to predict the efficacy of HAIC include serological testing, gene testing, and imaging testing. The above indicators and their combined forms showed excellent predictive effects in retrospective studies. This review summarized the strategies currently used to predict the efficacy of HAIC in middle and advanced HCC, analyzed each marker's ability to predict HAIC efficacy, and provided a reference for the clinical application of the prediction system.
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Affiliation(s)
- Qi-Feng Wang
- Department of Hepatobiliary Pancreatic Center, Beijing Tsinghua Changgung Hospital Affiliated to Tsinghua University, Beijing 102218, China
- Department of Hepatobiliary and Pancreatic Surgery, Qinghai University Affiliated Hospital, Xining 810000, Qinghai Province, China
| | - Zong-Wei Li
- Department of Hepatobiliary and Pancreatic Surgery, Qinghai University Affiliated Hospital, Xining 810000, Qinghai Province, China
| | - Hai-Feng Zhou
- Department of Hepatobiliary and Pancreatic Surgery, Qinghai University Affiliated Hospital, Xining 810000, Qinghai Province, China
| | - Kun-Zhong Zhu
- Department of Hepatobiliary and Pancreatic Surgery, Qinghai University Affiliated Hospital, Xining 810000, Qinghai Province, China
| | - Ya-Jing Wang
- Department of Hepatobiliary Pancreatic Center, Beijing Tsinghua Changgung Hospital Affiliated to Tsinghua University, Beijing 102218, China
| | - Ya-Qin Wang
- Department of Hepatobiliary Pancreatic Center, Beijing Tsinghua Changgung Hospital Affiliated to Tsinghua University, Beijing 102218, China
| | - Yue-Wei Zhang
- Department of Hepatobiliary Pancreatic Center, Beijing Tsinghua Changgung Hospital Affiliated to Tsinghua University, Beijing 102218, China
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Zheng T, Zhang Y, Wang H, Tang L, Xie X, Fu Q, Wu PY, Song B. Thyroid imaging reporting and data system with MRI morphological features for thyroid nodules: diagnostic performance and unnecessary biopsy rate. Cancer Imaging 2024; 24:74. [PMID: 38872150 DOI: 10.1186/s40644-024-00721-8] [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: 11/16/2023] [Accepted: 06/10/2024] [Indexed: 06/15/2024] Open
Abstract
BACKGROUND To assess MRI-based morphological features in improving the American College of Radiology Thyroid Imaging Reporting and Data System (ACR-TIRADS) for categorizing thyroid nodules. METHODS A retrospective analysis was performed on 728 thyroid nodules (453 benign and 275 malignant) that postoperative pathology confirmed. Univariate and multivariate logistic regression analyses were used to find independent predictors of MRI morphological features in benign and malignant thyroid nodules. The improved method involved increasing the ACR-TIRADS level by one when there are independent predictors of MRI-based morphological features, whether individually or in combination, and conversely decreasing it by one. The study compared the performance of conventional ACR-TIRADS and different improved versions. RESULTS Among the various MRI morphological features analyzed, restricted diffusion and reversed halo sign were determined to be significant independent risk factors for malignant thyroid nodules (OR = 45.1, 95% CI = 23.2-87.5, P < 0.001; OR = 38.0, 95% CI = 20.4-70.7, P < 0.001) and were subsequently included in the final assessment of performance. The areas under the receiver operating characteristic curves (AUCs) for both the conventional and four improved ACR-TIRADSs were 0.887 (95% CI: 0.861-0.909), 0.945 (95% CI: 0.926-0.961), 0.947 (95% CI: 0.928-0.962), 0.945 (95% CI: 0.926-0.961) and 0.951 (95% CI: 0.932-0.965), respectively. The unnecessary biopsy rates for the conventional and four improved ACR-TIRADSs were 62.8%, 30.0%, 27.1%, 26.8% and 29.1%, respectively, while the malignant missed diagnosis rates were 1.1%, 2.8%, 3.7%, 5.4% and 1.2%. CONCLUSIONS MRI morphological features with ACR-TIRADS has improved diagnostic performance and reduce unnecessary biopsy rate while maintaining a low malignant missed diagnosis rate.
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Affiliation(s)
- Tingting Zheng
- Department of Radiology, Minhang Hospital, Fudan University, No 170, Xinsong Road, Minhang District, Shanghai, 201199, China
| | - Yuan Zhang
- Department of Radiology, Minhang Hospital, Fudan University, No 170, Xinsong Road, Minhang District, Shanghai, 201199, China
| | - Hao Wang
- Department of Radiology, Minhang Hospital, Fudan University, No 170, Xinsong Road, Minhang District, Shanghai, 201199, China
| | - Lang Tang
- Department of Ultrasound, Minhang Hospital, Fudan University, No 170, Xinsong Road, Minhang District, Shanghai, 201199, China
| | - Xiaoli Xie
- Department of Pathology, Minhang Hospital, Fudan University, No 170, Xinsong Road, Minhang District, Shanghai, 201199, China
| | - Qingyin Fu
- Department of Ultrasound, Minhang Hospital, Fudan University, No 170, Xinsong Road, Minhang District, Shanghai, 201199, China
| | - Pu-Yeh Wu
- GE Healthcare, MR Research China, Beijing, China
| | - Bin Song
- Department of Radiology, Minhang Hospital, Fudan University, No 170, Xinsong Road, Minhang District, Shanghai, 201199, China.
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Kong L, Ling J, Cao W, Wen Z, Lin Y, Cai Q, Chen Y, Guo Y, Chen J, Wang H. Multiparametric MR characterization for human epithelial growth factor receptor 2 expression in bladder cancer: an exploratory study. Abdom Radiol (NY) 2024:10.1007/s00261-024-04378-6. [PMID: 38867120 DOI: 10.1007/s00261-024-04378-6] [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: 11/16/2023] [Revised: 05/06/2024] [Accepted: 05/12/2024] [Indexed: 06/14/2024]
Abstract
PURPOSE To investigate the application value of multiparametric MRI in evaluating the expression status of human epithelial growth factor receptor 2 (HER2) in bladder cancer (BCa). METHODS From April 2021 to July 2023, preoperative imaging manifestations of 90 patients with pathologically confirmed BCa were retrospectively collected and analyzed. All patients underwent multiparametric MRI including synthetic MRI, DWI, from which the T1, T2, proton density (PD) and apparent diffusion coefficient (ADC) values were obtained. The clinical and imaging characteristics as well as quantitative parameters (T1, T2, PD and ADC values) between HER2-positive and -negative BCa were compared using student t test and chi-square test. The diagnostic efficacy of parameters in predicting HER2 expression status was evaluated by calculating the area under ROC curve (AUC). RESULTS In total, 76 patients (mean age, 63.59 years ± 12.84 [SD]; 55 men) were included: 51 with HER2-negative and 25 with HER2-positive BCa. HER2-positive group demonstrated significantly higher ADC, T1, and T2 values than HER2-negative group (all P < 0.05). The combination of ADC values and tumor grade yielded the best diagnostic performance in evaluating HER2 expression level with an AUC of 0.864. CONCLUSION The multiparametric MR characterization can accurately evaluate the HER2 expression status in BCa, which may further guide the determination of individualized anti-HER2 targeted therapy strategies.
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Affiliation(s)
- Lingmin Kong
- Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, 58 Zhongshan Road 2, Guangzhou, Guangdong, People's Republic of China
| | - Jian Ling
- Department of Radiology, The Eastern Hospital of the First Affiliated Hospital, Sun Yat-Sen University, 58 Zhongshan Road 2, Guangzhou, Guangdong, People's Republic of China
| | - Wenxin Cao
- Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, 58 Zhongshan Road 2, Guangzhou, Guangdong, People's Republic of China
| | - Zhihua Wen
- Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, 58 Zhongshan Road 2, Guangzhou, Guangdong, People's Republic of China
| | - Yingyu Lin
- Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, 58 Zhongshan Road 2, Guangzhou, Guangdong, People's Republic of China
| | - Qian Cai
- Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, 58 Zhongshan Road 2, Guangzhou, Guangdong, People's Republic of China
| | - Yanling Chen
- Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, 58 Zhongshan Road 2, Guangzhou, Guangdong, People's Republic of China
| | - Yan Guo
- Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, 58 Zhongshan Road 2, Guangzhou, Guangdong, People's Republic of China
| | - Junxing Chen
- Department of Urology, The First Affiliated Hospital, Sun Yat-Sen University, 58 Zhongshan Road 2, Guangzhou, Guangdong, People's Republic of China.
| | - Huanjun Wang
- Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, 58 Zhongshan Road 2, Guangzhou, Guangdong, People's Republic of China.
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Chen J, Wu Z, Zhang Z, Chen Y, Yin M, Ehman RL, Yuan Y, Song B. Apparent diffusion coefficient and tissue stiffness are associated with different tumor microenvironment features of hepatocellular carcinoma. Eur Radiol 2024:10.1007/s00330-024-10743-2. [PMID: 38767658 DOI: 10.1007/s00330-024-10743-2] [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: 11/09/2023] [Revised: 02/27/2024] [Accepted: 03/07/2024] [Indexed: 05/22/2024]
Abstract
OBJECTIVES To investigate associations between tissue diffusion, stiffness, and different tumor microenvironment features in resected hepatocellular carcinoma (HCC). METHODS Seventy-two patients were prospectively included for preoperative magnetic resonance (MR) diffusion-weighted imaging and MR elastography examination. The mean apparent diffusion coefficient (ADC) and stiffness value were measured on the central three slices of the tumor and peri-tumor area. Cell density, tumor-stroma ratio (TSR), lymphocyte-rich HCC (LR-HCC), and CD8 + T cell infiltration were estimated in resected tumors. The interobserver agreement of MRI measurements and subjective pathological evaluation was assessed. Variables influencing ADC and stiffness were screened with univariate analyses, and then identified with multivariable linear regression. The potential relationship between explored imaging biomarkers and histopathological features was assessed with linear regression after adjustment for other influencing factors. RESULTS Seventy-two patients (male/female: 59/13, mean age: 56 ± 10.2 years) were included for analysis. Inter-reader agreement was good or excellent regarding MRI measurements and histopathological evaluation. No correlation between tumor ADC and tumor stiffness was found. Multivariable linear regression confirmed that cell density was the only factor associated with tumor ADC (Estimate = -0.03, p = 0.006), and tumor-stroma ratio was the only factor associated with tumor stiffness (Estimate = -0.18, p = 0.03). After adjustment for fibrosis stage (Estimate = 0.43, p < 0.001) and age (Estimate = 0.04, p < 0.001) in the multivariate linear regression, intra-tumoral CD8 + T cell infiltration remained a significant factor associated with peri-tumor stiffness (Estimate = 0.63, p = 0.02). CONCLUSIONS Tumor ADC surpasses tumor stiffness as a biomarker of cellularity. Tumor stiffness is associated with tumor-stroma ratio and peri-tumor stiffness might be an imaging biomarker of intra-tumoral immune microenvironment. CLINICAL RELEVANCE STATEMENT Tissue stiffness could potentially serve as an imaging biomarker of the intra-tumoral immune microenvironment of hepatocellular carcinoma and aid in patient selection for immunotherapy. KEY POINTS Apparent diffusion coefficient reflects cellularity of hepatocellular carcinoma. Tumor stiffness reflects tumor-stroma ratio of hepatocellular carcinoma and is associated with tumor-infiltrating lymphocytes. Tumor and peri-tumor stiffness might serve as imaging biomarkers of intra-tumoral immune microenvironment.
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Affiliation(s)
- Jie Chen
- Department of Radiology, West China Hospital, Sichuan University, No. 37 Guoxue Alley, Chengdu, 610041, China
- Department of Radiology, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, 610041, China
| | - Zhenru Wu
- Laboratory of Pathology, West China Hospital, Sichuan University, No. 88 South Keyuan Road, Chengdu, 610041, China
| | - Zhen Zhang
- Department of Radiology, West China Hospital, Sichuan University, No. 37 Guoxue Alley, Chengdu, 610041, China
- Department of Radiology, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, 610041, China
| | - Yidi Chen
- Department of Radiology, West China Hospital, Sichuan University, No. 37 Guoxue Alley, Chengdu, 610041, China
- Department of Radiology, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, 610041, China
| | - Meng Yin
- Department of Radiology, Mayo Clinic, Rochester, MN, 55905, USA
| | - Richard L Ehman
- Department of Radiology, Mayo Clinic, Rochester, MN, 55905, USA
| | - Yuan Yuan
- Department of Radiology, West China Hospital, Sichuan University, No. 37 Guoxue Alley, Chengdu, 610041, China.
- Department of Radiology, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, 610041, China.
| | - Bin Song
- Department of Radiology, West China Hospital, Sichuan University, No. 37 Guoxue Alley, Chengdu, 610041, China.
- Department of Radiology, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, 610041, China.
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Ehrengut C, Schindler A, Seehofer D, Ebel S, Steinhoff K, Sabri O, Berg T, Denecke T, Bömmel FVAN, Meyer HJ. The Apparent Diffusion Coefficient of the Paraspinal and Psoas Muscles Are of Prognostic Relevance in Patients With Hepatocellular Carcinoma Undergoing Transarterial Radioembolization. CANCER DIAGNOSIS & PROGNOSIS 2024; 4:281-287. [PMID: 38707727 PMCID: PMC11062171 DOI: 10.21873/cdp.10321] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Received: 01/17/2024] [Accepted: 02/26/2024] [Indexed: 05/07/2024]
Abstract
Background/Aim Transarterial radioembolization (TARE) is a treatment option for early or intermediate stage hepatocellular carcinoma (HCC). Sarcopenia is defined as loss of muscle strength and quality which can be estimated by imaging modalities and has been associated with prognosis and treatment response in HCC patients. Apparent diffusion coefficient (ADC) values derived from diffusion-weighted imaging (DWI) can reflect the tissue composition and might be better to determine muscle changes of sarcopenia than the standard method of computed tomography (CT). The present study sought to elucidate ADC values of the abdominal wall muscles as a prognostic factor in patients undergoing TARE. Patients and Methods A retrospective analysis was performed between 2016 and 2020. Overall, 52 patients, 9 women (17.3%) and 43 men (82.7%), with a mean age of 69±8.5 years were included into the analysis. In every case, the first pre-interventional magnetic resonance imaging (MRI) including DWI was used to measure the ADC values of paraspinal and psoas muscle. The 12-month survival after TARE was used as the primary study outcome. Results Overall, 40 patients (76.9%) of the patient cohort died within the 12-month observation period. Mean overall survival was 10.9 months after TARE for all patients. Mean ADC values for all muscles were 1.31±0.13×10-3mm2/s. The ADC values of the paraspinal muscles were statistically significantly higher compared to the ADC values of the psoas muscles (p=0.0031). A positive correlation was identified between mean ADC and the thrombocyte count (r=0.37, p=0.005) and serum bilirubin (r=-0.30, p=0.03). In the multivariate Cox regression analysis, the mean ADC values of all muscles were associated with the survival after 12 months (HR=0.98, 95% CI=0.97-0.99, p=0.04). Conclusion ADC values of the abdominal wall muscles could be used as a prognostic biomarker in patients with HCC undergoing TARE. These preliminary results should be confirmed by further studies using external validation cohorts and other treatment modalities.
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Affiliation(s)
- Constantin Ehrengut
- Department of Diagnostic and Interventional Radiology, University of Leipzig, Leipzig, Germany
| | - Aaron Schindler
- Department of Hepatology, University of Leipzig, Leipzig, Germany
| | - Daniel Seehofer
- Department of Visceral, Transplant, Thoracic and Vascular Surgery, University of Leipzig, Leipzig, Germany
| | - Sebastian Ebel
- Department of Diagnostic and Interventional Radiology, University of Leipzig, Leipzig, Germany
| | - Karen Steinhoff
- Department of Nuclear Medicine University of Leipzig, Leipzig, Germany
| | - Osama Sabri
- Department of Nuclear Medicine University of Leipzig, Leipzig, Germany
| | - Thomas Berg
- Department of Hepatology, University of Leipzig, Leipzig, Germany
| | - Timm Denecke
- Department of Diagnostic and Interventional Radiology, University of Leipzig, Leipzig, Germany
| | | | - Hans-Jonas Meyer
- Department of Diagnostic and Interventional Radiology, University of Leipzig, Leipzig, Germany
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Sanvito F, Raymond C, Cho NS, Yao J, Hagiwara A, Orpilla J, Liau LM, Everson RG, Nghiemphu PL, Lai A, Prins R, Salamon N, Cloughesy TF, Ellingson BM. Simultaneous quantification of perfusion, permeability, and leakage effects in brain gliomas using dynamic spin-and-gradient-echo echoplanar imaging MRI. Eur Radiol 2024; 34:3087-3101. [PMID: 37882836 PMCID: PMC11045669 DOI: 10.1007/s00330-023-10215-z] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2023] [Revised: 07/05/2023] [Accepted: 07/27/2023] [Indexed: 10/27/2023]
Abstract
OBJECTIVE To determine the feasibility and biologic correlations of dynamic susceptibility contrast (DSC), dynamic contrast enhanced (DCE), and quantitative maps derived from contrast leakage effects obtained simultaneously in gliomas using dynamic spin-and-gradient-echo echoplanar imaging (dynamic SAGE-EPI) during a single contrast injection. MATERIALS AND METHODS Thirty-eight patients with enhancing brain gliomas were prospectively imaged with dynamic SAGE-EPI, which was processed to compute traditional DSC metrics (normalized relative cerebral blood flow [nrCBV], percentage of signal recovery [PSR]), DCE metrics (volume transfer constant [Ktrans], extravascular compartment [ve]), and leakage effect metrics: ΔR2,ss* (reflecting T2*-leakage effects), ΔR1,ss (reflecting T1-leakage effects), and the transverse relaxivity at tracer equilibrium (TRATE, reflecting the balance between ΔR2,ss* and ΔR1,ss). These metrics were compared between patient subgroups (treatment-naïve [TN] vs recurrent [R]) and biological features (IDH status, Ki67 expression). RESULTS In IDH wild-type gliomas (IDHwt-i.e., glioblastomas), previous exposure to treatment determined lower TRATE (p = 0.002), as well as higher PSR (p = 0.006), Ktrans (p = 0.17), ΔR1,ss (p = 0.035), ve (p = 0.006), and ADC (p = 0.016). In IDH-mutant gliomas (IDHm), previous treatment determined higher Ktrans and ΔR1,ss (p = 0.026). In TN-gliomas, dynamic SAGE-EPI metrics tended to be influenced by IDH status (p ranging 0.09-0.14). TRATE values above 142 mM-1s-1 were exclusively seen in TN-IDHwt, and, in TN-gliomas, this cutoff had 89% sensitivity and 80% specificity as a predictor of Ki67 > 10%. CONCLUSIONS Dynamic SAGE-EPI enables simultaneous quantification of brain tumor perfusion and permeability, as well as mapping of novel metrics related to cytoarchitecture (TRATE) and blood-brain barrier disruption (ΔR1,ss), with a single contrast injection. CLINICAL RELEVANCE STATEMENT Simultaneous DSC and DCE analysis with dynamic SAGE-EPI reduces scanning time and contrast dose, respectively alleviating concerns about imaging protocol length and gadolinium adverse effects and accumulation, while providing novel leakage effect metrics reflecting blood-brain barrier disruption and tumor tissue cytoarchitecture. KEY POINTS • Traditionally, perfusion and permeability imaging for brain tumors requires two separate contrast injections and acquisitions. • Dynamic spin-and-gradient-echo echoplanar imaging enables simultaneous perfusion and permeability imaging. • Dynamic spin-and-gradient-echo echoplanar imaging provides new image contrasts reflecting blood-brain barrier disruption and cytoarchitecture characteristics.
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Affiliation(s)
- Francesco Sanvito
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California Los Angeles, 924 Westwood Blvd, Los Angeles, CA, 90024, USA
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, 885 Tiverton Dr, Los Angeles, CA, 90095, USA
- Unit of Radiology, Department of Clinical, Surgical, Diagnostic, and Pediatric Sciences, University of Pavia, Viale Camillo Golgi 19, 27100, Pavia, Italy
| | - Catalina Raymond
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California Los Angeles, 924 Westwood Blvd, Los Angeles, CA, 90024, USA
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, 885 Tiverton Dr, Los Angeles, CA, 90095, USA
| | - Nicholas S Cho
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California Los Angeles, 924 Westwood Blvd, Los Angeles, CA, 90024, USA
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, 885 Tiverton Dr, Los Angeles, CA, 90095, USA
- Medical Scientist Training Program, David Geffen School of Medicine, University of California Los Angeles, 885 Tiverton Dr, Los Angeles, CA, 90095, USA
- Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California Los Angeles, 7400 Boelter Hall, Los Angeles, CA, 90095, USA
| | - Jingwen Yao
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California Los Angeles, 924 Westwood Blvd, Los Angeles, CA, 90024, USA
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, 885 Tiverton Dr, Los Angeles, CA, 90095, USA
| | - Akifumi Hagiwara
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California Los Angeles, 924 Westwood Blvd, Los Angeles, CA, 90024, USA
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, 885 Tiverton Dr, Los Angeles, CA, 90095, USA
- Department of Radiology, Juntendo University School of Medicine, Bunkyo City, 2-Chōme-1-1 Hongō, Tokyo, 113-8421, Japan
| | - Joey Orpilla
- Department of Neurosurgery, David Geffen School of Medicine, University of California Los Angeles, 885 Tiverton Dr, Los Angeles, CA, 90095, USA
| | - Linda M Liau
- Department of Neurosurgery, David Geffen School of Medicine, University of California Los Angeles, 885 Tiverton Dr, Los Angeles, CA, 90095, USA
| | - Richard G Everson
- Department of Neurosurgery, David Geffen School of Medicine, University of California Los Angeles, 885 Tiverton Dr, Los Angeles, CA, 90095, USA
| | - Phioanh L Nghiemphu
- Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, 885 Tiverton Dr, Los Angeles, CA, 90095, USA
| | - Albert Lai
- Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, 885 Tiverton Dr, Los Angeles, CA, 90095, USA
| | - Robert Prins
- Department of Neurosurgery, David Geffen School of Medicine, University of California Los Angeles, 885 Tiverton Dr, Los Angeles, CA, 90095, USA
| | - Noriko Salamon
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, 885 Tiverton Dr, Los Angeles, CA, 90095, USA
| | - Timothy F Cloughesy
- Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, 885 Tiverton Dr, Los Angeles, CA, 90095, USA
| | - Benjamin M Ellingson
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California Los Angeles, 924 Westwood Blvd, Los Angeles, CA, 90024, USA.
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, 885 Tiverton Dr, Los Angeles, CA, 90095, USA.
- Medical Scientist Training Program, David Geffen School of Medicine, University of California Los Angeles, 885 Tiverton Dr, Los Angeles, CA, 90095, USA.
- Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California Los Angeles, 7400 Boelter Hall, Los Angeles, CA, 90095, USA.
- Department of Neurosurgery, David Geffen School of Medicine, University of California Los Angeles, 885 Tiverton Dr, Los Angeles, CA, 90095, USA.
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California Los Angeles, 885 Tiverton Dr, Los Angeles, CA, 90095, USA.
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9
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Latreche A, Dissaux G, Querellou S, Mazouz Fatmi D, Lucia F, Bordron A, Vu A, Touati R, Nguyen V, Hamya M, Dissaux B, Bourbonne V. Correlation between rCBV Delineation Similarity and Overall Survival in a Prospective Cohort of High-Grade Gliomas Patients: The Hidden Value of Multimodal MRI? Biomedicines 2024; 12:789. [PMID: 38672146 PMCID: PMC11048661 DOI: 10.3390/biomedicines12040789] [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: 03/08/2024] [Revised: 03/18/2024] [Accepted: 03/26/2024] [Indexed: 04/28/2024] Open
Abstract
PURPOSE The accuracy of target delineation in radiation treatment planning of high-grade gliomas (HGGs) is crucial to achieve high tumor control, while minimizing treatment-related toxicity. Magnetic resonance imaging (MRI) represents the standard imaging modality for delineation of gliomas with inherent limitations in accurately determining the microscopic extent of tumors. The purpose of this study was to assess the survival impact of multi-observer delineation variability of multiparametric MRI (mpMRI) and [18F]-FET PET/CT. MATERIALS AND METHODS Thirty prospectively included patients with histologically confirmed HGGs underwent a PET/CT and mpMRI including diffusion-weighted imaging (DWI: b0, b1000, ADC), contrast-enhanced T1-weighted imaging (T1-Gado), T2-weighted fluid-attenuated inversion recovery (T2Flair), and perfusion-weighted imaging with computation of relative cerebral blood volume (rCBV) and K2 maps. Nine radiation oncologists delineated the PET/CT and MRI sequences. Spatial similarity (Dice similarity coefficient: DSC) was calculated between the readers for each sequence. Impact of the DSC on progression-free survival (PFS) and overall survival (OS) was assessed using Kaplan-Meier curves and the log-rank test. RESULTS The highest DSC mean values were reached for morphological sequences, ranging from 0.71 +/- 0.18 to 0.84 +/- 0.09 for T2Flair and T1Gado, respectively, while metabolic volumes defined by PET/CT achieved a mean DSC of 0.75 +/- 0.11. rCBV variability (mean DSC0.32 +/- 0.20) significantly impacted PFS (p = 0.02) and OS (p = 0.002). CONCLUSIONS Our data suggest that the T1-Gado and T2Flair sequences were the most reproducible sequences, followed by PET/CT. Reproducibility for functional sequences was low, but rCBV inter-reader similarity significantly impacted PFS and OS.
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Affiliation(s)
- Amina Latreche
- Radiation Oncology Department, University Hospital, 29200 Brest, France; (A.L.); (G.D.); (F.L.); (A.B.); (A.V.); (V.N.); (M.H.)
| | - Gurvan Dissaux
- Radiation Oncology Department, University Hospital, 29200 Brest, France; (A.L.); (G.D.); (F.L.); (A.B.); (A.V.); (V.N.); (M.H.)
| | - Solène Querellou
- Nuclear Medicine Department, University Hospital, 29200 Brest, France;
- Groupe d’Etude de la Thrombose Occidentale GETBO (INSERM UMR 1304), Université de Bretagne Occidentale, 29200 Brest, France
| | | | - François Lucia
- Radiation Oncology Department, University Hospital, 29200 Brest, France; (A.L.); (G.D.); (F.L.); (A.B.); (A.V.); (V.N.); (M.H.)
- LaTIM UMR 1101, INSERM, Université de Bretagne Occidentale, 29200 Brest, France
| | - Anais Bordron
- Radiation Oncology Department, University Hospital, 29200 Brest, France; (A.L.); (G.D.); (F.L.); (A.B.); (A.V.); (V.N.); (M.H.)
| | - Alicia Vu
- Radiation Oncology Department, University Hospital, 29200 Brest, France; (A.L.); (G.D.); (F.L.); (A.B.); (A.V.); (V.N.); (M.H.)
| | - Ruben Touati
- Radiation Oncology Department, University Hospital, 29200 Brest, France; (A.L.); (G.D.); (F.L.); (A.B.); (A.V.); (V.N.); (M.H.)
| | - Victor Nguyen
- Radiation Oncology Department, University Hospital, 29200 Brest, France; (A.L.); (G.D.); (F.L.); (A.B.); (A.V.); (V.N.); (M.H.)
| | - Mohamed Hamya
- Radiation Oncology Department, University Hospital, 29200 Brest, France; (A.L.); (G.D.); (F.L.); (A.B.); (A.V.); (V.N.); (M.H.)
| | - Brieg Dissaux
- Groupe d’Etude de la Thrombose Occidentale GETBO (INSERM UMR 1304), Université de Bretagne Occidentale, 29200 Brest, France
- Radiology Department, University Hospital, 29200 Brest, France;
| | - Vincent Bourbonne
- Radiation Oncology Department, University Hospital, 29200 Brest, France; (A.L.); (G.D.); (F.L.); (A.B.); (A.V.); (V.N.); (M.H.)
- LaTIM UMR 1101, INSERM, Université de Bretagne Occidentale, 29200 Brest, France
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10
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Sim Y, Choi SH, Lee N, Park YW, Ahn SS, Chang JH, Kim SH, Lee SK. Clinical, qualitative imaging biomarkers, and tumor oxygenation imaging biomarkers for differentiation of midline-located IDH wild-type glioblastomas and H3 K27-altered diffuse midline gliomas in adults. Eur J Radiol 2024; 173:111384. [PMID: 38422610 DOI: 10.1016/j.ejrad.2024.111384] [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: 09/25/2023] [Revised: 01/09/2024] [Accepted: 02/16/2024] [Indexed: 03/02/2024]
Abstract
PURPOSE To compare the clinical, qualitative and quantitative imaging phenotypes, including tumor oxygenation characteristics of midline-located IDH-wildtype glioblastomas (GBMs) and H3 K27-altered diffuse midline gliomas (DMGs) in adults. METHODS Preoperative MRI data of 55 adult patients with midline-located IDH-wildtype GBM or H3 K27-altered DMG (32 IDH-wildtype GBM and 23 H3 K27-altered DMG patients) were included. Qualitative imaging assessment was performed. Quantitative imaging assessment including the tumor volume, normalized cerebral blood volume, capillary transit time heterogeneity (CTH), oxygen extraction fraction (OEF), relative cerebral metabolic rate of oxygen values, and mean ADC value were performed from the tumor mask via automatic segmentation. Univariable and multivariable logistic analyses were performed. RESULTS On multivariable analysis, age (odds ratio [OR] = 0.92, P = 0.015), thalamus or medulla location (OR = 10.48, P = 0.013), presence of necrosis (OR = 0.15, P = 0.038), and OEF (OR = 0.01, P = 0.042) were independent predictors to differentiate H3 K27-altered DMG from midline-located IDH-wildtype GBM. The area under the curve, accuracy, sensitivity, and specificity of the multivariable model were 0.88 (95 % confidence interval: 0.77-0.95), 81.8 %, 82.6 %, and 81.3 %, respectively. CONCLUSIONS Along with younger age, tumor location, less frequent necrosis, and lower OEF may be useful imaging biomarkers to differentiate H3 K27-altered DMG from midline-located IDH-wildtype GBM. Tumor oxygenation imaging biomarkers may reflect the less hypoxic nature of H3 K27-altered DMG than IDH-wildtype GBM and may contribute to differentiation.
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Affiliation(s)
- Yongsik Sim
- Department of Radiology and Research Institute of Radiological Science and Center for Clinical Imaging Data Science, Yonsei University College of Medicine, Seoul, Republic of Korea.
| | - Seo Hee Choi
- Department of Radiation Oncology, Yonsei University College of Medicine, Seoul, Republic of Korea.
| | - Narae Lee
- Department of Nuclear Medicine, Yonsei University Wonju College of Medicine, Wonju, Republic of Korea.
| | - Yae Won Park
- Department of Radiology and Research Institute of Radiological Science and Center for Clinical Imaging Data Science, Yonsei University College of Medicine, Seoul, Republic of Korea.
| | - Sung Soo Ahn
- Department of Radiology and Research Institute of Radiological Science and Center for Clinical Imaging Data Science, Yonsei University College of Medicine, Seoul, Republic of Korea.
| | - Jong Hee Chang
- Department of Neurosurgery, Yonsei University College of Medicine, Seoul, Republic of Korea.
| | - Se Hoon Kim
- Department of Pathology, Yonsei University College of Medicine, Seoul, Republic of Korea.
| | - Seung-Koo Lee
- Department of Radiology and Research Institute of Radiological Science and Center for Clinical Imaging Data Science, Yonsei University College of Medicine, Seoul, Republic of Korea.
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11
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Yang T, Ye Z, Yao S, Wu Y, Yin T, Song B. Quantitative diffusion weighted imaging in patients with hepatocellular carcinoma: effects of simultaneous multi-slice acceleration and gadoxetic acid administration. Abdom Radiol (NY) 2024; 49:683-693. [PMID: 37930449 DOI: 10.1007/s00261-023-04100-y] [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: 07/24/2023] [Revised: 10/13/2023] [Accepted: 10/18/2023] [Indexed: 11/07/2023]
Abstract
PURPOSE To investigate whether simultaneous multi-slice (SMS) acceleration and gadoxetic acid administration affect the quantitative apparent diffusion coefficient (ADC) and signal-to-noise ratio (SNR) measurement of DWI in patients with HCC. METHODS This prospective study initially enrolled 208 patients with clinically suspected HCC. Free breathing SMS-DWI and conventional DWI (CON-DWI) were performed before and after gadoxetic acid administration. Lesion conspicuity, ADCs and SNRs of the HCC lesion and normal liver parenchyma were independently measured by two radiologists. The paired t test or Wilcoxon signed rank test was used to evaluate the differences of lesion conspicuity, ADCs and SNRs between SMS-DWI and CON-DWI, as well as those before and after gadoxetic acid administration. RESULTS A total of 102 HCC patients (90 men and 12 women; mean age, 54.6 ± 11.7 years) were finally included for analysis. SMS-DWI and CON-DWI demonstrated comparable lesion conspicuity (P = 0.081-0.566). For the influence of SMS acceleration, the SNRs of liver parenchyma on enhanced SMS-DWI were significantly higher than enhanced CON-DWI (P = 0.015). For the influence of gadoxetic acid administration, the mean ADCs were significantly higher on enhanced SMS-DWI than unenhanced SMS-DWI (HCC, P = 0.013; liver parenchyma, P = 0.032). CONCLUSION Quantitative ADC measurements of HCC and liver parenchyma were not affected by SMS acceleration, and SMS-DWI can provide higher SNR than CON-DWI. However, the ADC measurements can be affected by gadoxetic acid administration on SMS-DWI, so it is recommended to perform SMS-DWI before gadoxetic acid administration.
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Affiliation(s)
- Ting Yang
- Department of Radiology, West China Hospital, Sichuan University, No. 37 Guoxue Alley, Chengdu, 610041, China
| | - Zheng Ye
- Department of Radiology, West China Hospital, Sichuan University, No. 37 Guoxue Alley, Chengdu, 610041, China
| | - Shan Yao
- Department of Radiology, West China Hospital, Sichuan University, No. 37 Guoxue Alley, Chengdu, 610041, China
| | - Yingyi Wu
- Department of Radiology, West China Hospital, Sichuan University, No. 37 Guoxue Alley, Chengdu, 610041, China
| | - Ting Yin
- MR Collaborations, Siemens Healthineers Ltd, Chengdu, China
| | - Bin Song
- Department of Radiology, West China Hospital, Sichuan University, No. 37 Guoxue Alley, Chengdu, 610041, China.
- Department of Radiology, Sanya People's Hospital, Sanya, Hainan, China.
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12
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Chikui T, Ohga M, Kami Y, Togao O, Kawano S, Kiyoshima T, Yoshiura K. Correlation between diffusion-weighted image-derived parameters and dynamic contrast-enhanced magnetic resonance imaging-derived parameters in the orofacial region. Acta Radiol Open 2024; 13:20584601241244777. [PMID: 38559449 PMCID: PMC10979534 DOI: 10.1177/20584601241244777] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2023] [Accepted: 03/18/2024] [Indexed: 04/04/2024] Open
Abstract
Background Diffusion-weighted imaging (DWI) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) are widely used in the orofacial region. Furthermore, quantitative analyses have proven useful. However, a few reports have described the correlation between DWI-derived parameters and DCE-MRI-derived parameters, and the results have been controversial. Purpose To evaluate the correlation among parameters obtained by DWI and DCE-MRI and to compare them between benign and malignant lesions. Material and Methods Fifty orofacial lesions were analysed. The apparent diffusion coefficient (ADC), true diffusion coefficient (D), pseudodiffusion coefficient (D*) and perfusion fraction (f) were estimated by DWI. For DCE-MRI, TK model analysis was performed to estimate physiological parameters, for example, the influx forward volume transfer constant into the extracellular-extravascular space (EES) (Ktrans) and fractional volumes of EES and plasma components (ve and vp). Results Both ADC and D showed a moderate positive correlation with ve (ρ = 0.640 and 0.645, respectively). Ktrans showed a marginally weak correlation with f (ρ = 0.296), while vp was not correlated with f or D*; therefore, IVIM perfusion-related parameters and TK model perfusion-related parameters were not straightforward. Both D and ve yielded high diagnostic power between benign lesions and malignant tumours with areas under the curve (AUCs) of 0.830 and 0.782, respectively. Conclusion Both D and ve were reliable parameters that were useful for the differential diagnosis. In addition, the true diffusion coefficient (D) was affected by the fractional volume of EES.
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Affiliation(s)
- Toru Chikui
- Section of Oral and Maxillofacial Radiology, Division of Maxillofacial Diagnostic and Surgical Sciences, Faculty of Dental Science, Kyushu University, Fukuoka, Japan
| | - Masahiro Ohga
- Department of Medical Technology, Kyushu University Hospital, Fukuoka, Japan
| | - Yukiko Kami
- Section of Oral and Maxillofacial Radiology, Division of Maxillofacial Diagnostic and Surgical Sciences, Faculty of Dental Science, Kyushu University, Fukuoka, Japan
| | - Osamu Togao
- Department of Molecular Imaging & Diagnosis, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Shintaro Kawano
- Section of Oral and Maxillofacial Oncology, Division of Maxillofacial Diagnostic and Surgical Sciences, Faculty of Dental Science, Kyushu University, Fukuoka, Japan
| | - Tamotsu Kiyoshima
- Laboratory of Oral Pathology, Division of Maxillofacial Diagnostic and Surgical Sciences, Faculty of Dental Science, Kyushu University, Fukuoka, Japan
| | - Kazunori Yoshiura
- Section of Oral and Maxillofacial Radiology, Division of Maxillofacial Diagnostic and Surgical Sciences, Faculty of Dental Science, Kyushu University, Fukuoka, Japan
- Department of Medical Technology, Kyushu University Hospital, Fukuoka, Japan
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13
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Hassan RMA, Almalki YE, Basha MAA, Alduraibi SK, Hassan AH, Aboualkheir M, Almushayti ZA, Alduraibi AK, Amer MM, Basha AMA, Refaat MM. Predicting the Consistency of Pituitary Macroadenomas: The Utility of Diffusion-Weighted Imaging and Apparent Diffusion Coefficient Measurements for Surgical Planning. Diagnostics (Basel) 2024; 14:493. [PMID: 38472965 DOI: 10.3390/diagnostics14050493] [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: 02/06/2024] [Revised: 02/21/2024] [Accepted: 02/22/2024] [Indexed: 03/14/2024] Open
Abstract
Understanding the consistency of pituitary macroadenomas is crucial for neurosurgeons planning surgery. This retrospective study aimed to evaluate the utility of diffusion-weighted imaging (DWI) and the apparent diffusion coefficient (ADC) as non-invasive imaging modalities for predicting the consistency of pituitary macroadenomas. This could contribute to appropriate surgical planning and therefore reduce the likelihood of incomplete resections. The study included 45 patients with pathologically confirmed pituitary macroadenomas. Conventional MRI sequences, DWIs, ADC maps, and pre- and post-contrast MRIs were performed. Two neuroradiologists assessed all of the images. Neurosurgeons assessed the consistency of the tumor macroscopically, and histopathologists examined it microscopically. The MRI findings were compared with postoperative data. According to the operative data, macroadenomas were divided into the two following categories based on their consistency: aspirable (n = 27) and non-aspirable tumors (n = 18). A statistically significant difference in DWI findings was found when comparing macroadenomas of different consistencies (p < 0.001). Most aspirable macroadenomas (66.7%) were hyperintense according to DWI and hypointense on ADC maps, whereas most non-aspirable macroadenomas (83.3%) were hypointense for DWI and hyperintense on ADC maps. At a cut-off value of 0.63 × 10-3 mm2/s, the ADC showed a sensitivity of 85.7% and a specificity of 75% for the detection of non-aspirable macroadenomas (AUC, 0.946). The study concluded that DWI should be routinely performed in conjunction with ADC measurements in the preoperative evaluation of pituitary macroadenomas. This approach may aid in surgical planning, ensure that appropriate techniques are utilized, and reduce the risk of incomplete resection.
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Affiliation(s)
- Rania Mostafa A Hassan
- Department of Diagnostic Radiology, Faculty of Human Medicine, Zagazig University, Zagazig 44519, Egypt
| | - Yassir Edrees Almalki
- Division of Radiology, Department of Internal Medicine, Medical College, Najran University, Najran 61441, Saudi Arabia
| | | | | | - Alshehri Hanan Hassan
- Internal Medicine Department, College of Medicine, King Khalid University, Abha 62529, Saudi Arabia
| | - Mervat Aboualkheir
- Department of Radiology and Medical Imaging, College of Medicine, Taibah University, Madinah 42353, Saudi Arabia
| | - Ziyad A Almushayti
- Department of Radiology, College of Medicine, Qassim University, Buraidah 52571, Saudi Arabia
| | - Alaa K Alduraibi
- Department of Radiology, College of Medicine, Qassim University, Buraidah 52571, Saudi Arabia
| | - Mona M Amer
- Department of Neurology, Faculty of Human Medicine, Zagazig University, Zagazig 44519, Egypt
| | | | - Mona Mohammed Refaat
- Department of Diagnostic Radiology, Faculty of Human Medicine, Zagazig University, Zagazig 44519, Egypt
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14
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Bušić M, Rumboldt Z, Čerina D, Bušić Ž, Dolić K. Prognostic Value of Apparent Diffusion Coefficient (ADC) in Patients with Diffuse Gliomas. Cancers (Basel) 2024; 16:681. [PMID: 38398073 PMCID: PMC10886867 DOI: 10.3390/cancers16040681] [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: 01/14/2024] [Revised: 01/30/2024] [Accepted: 02/03/2024] [Indexed: 02/25/2024] Open
Abstract
This study aimed to evaluate potential posttreatment changes in ADC values within the tissue surrounding the enhancing lesion, particularly in areas not exhibiting MRI characteristics of involvement. Additionally, the objective was to investigate the correlations among ADC values, treatment response, and survival outcomes in individuals diagnosed with gliomas. This retrospective study included a total of 49 patients that underwent either stereotactic biopsy or maximal surgical resection. Histologically confirmed as Grade III or IV gliomas, all cases adhered to the 2016 and 2021 WHO classifications, with subsequent radio-chemotherapy administered post-surgery. Patients were divided into two groups: short and long survival groups. Baseline and follow-up MRI scans were obtained on a 1.5 T MRI scanner. Two ROI circles were positioned near the enhancing area, one ROI in the NAWM ipsilateral to the neoplasm and another symmetrically in the contralateral hemisphere on ADC maps. At follow-up there was a significant difference in both ipsilateral and contralateral NAWM between the two groups, -0.0857 (p = 0.004) and -0.0607 (p = 0.037), respectively. There was a weak negative correlation between survival and ADC values in ipsilateral and contralateral NAWM at the baseline with the correlation coefficient -0.328 (p = 0.02) and -0.302 (p = 0.04), respectively. The correlation was stronger at the follow-up. The findings indicate that ADC values in normal-appearing white matter (NAWM) may function as a prognostic biomarker in patients with diffuse gliomas.
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Affiliation(s)
- Marija Bušić
- Department of Diagnostic and Interventional Radiology, University Hospital Split, Spinčićeva 1, 21000 Split, Croatia; (M.B.); (Ž.B.)
| | - Zoran Rumboldt
- School of Medicine, University of Rijeka, Ulica Braće Branchetta 20/1, 51000 Rijeka, Croatia;
| | - Dora Čerina
- Department of Oncology, University Hospital Split, Spinčićeva 1, 21000 Split, Croatia;
| | - Željko Bušić
- Department of Diagnostic and Interventional Radiology, University Hospital Split, Spinčićeva 1, 21000 Split, Croatia; (M.B.); (Ž.B.)
| | - Krešimir Dolić
- Department of Diagnostic and Interventional Radiology, University Hospital Split, Spinčićeva 1, 21000 Split, Croatia; (M.B.); (Ž.B.)
- School of Medicine, University of Split, Šoltanska 1, 21000 Split, Croatia
- University Department of Health Studies, University of Split, Ulica Ruđera Boškovića 35, 21000 Split, Croatia
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Bian W, Wang L, Li J, Cui S, Wu W, Fan R, Niu J. Comparison of reduced field-of-view DWI and conventional DWI techniques for the assessment of lumbar bone marrow infiltration in patients with acute leukemia. Front Oncol 2024; 13:1321080. [PMID: 38260859 PMCID: PMC10800863 DOI: 10.3389/fonc.2023.1321080] [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: 10/16/2023] [Accepted: 11/28/2023] [Indexed: 01/24/2024] Open
Abstract
Objectives To compare the imaging quality, apparent diffusion coefficient (ADC), and the value of assessing bone marrow infiltration between reduced field-of-view diffusion-weighted imaging (r-FOV DWI) and conventional DWI in the lumbar spine of acute leukemia (AL). Methods Patients with newly diagnosed AL were recruited and underwent both r-FOV DWI and conventional DWI in the lumbar spine. Two radiologists evaluated image quality scores using 5-Likert-type scales qualitatively and measured signal-to-noise ratio (SNR), contrast-to-noise (CNR), signal intensity ratio (SIR), and ADC quantitatively. Patients were divided into hypo- and normocellular group, moderately hypercellular group, and severely hypercellular group according to bone marrow cellularity (BMC) obtained from bone marrow biopsies. The image quality parameters and ADC value between the two sequences were compared. One-way analysis of variance followed by LSD post hoc test was used for the comparisons of the ADC values among the three groups. The performance of ADC obtained with r-FOV DWI (ADCr) and conventional DWI(ADCc) in evaluating BMC and their correlations with BMC and white blood cells (WBC) were analyzed and compared. Results 71 AL patients (hypo- and normocellular: n=20; moderately hypercellular: n=19; severely hypercellular: n=32) were evaluated. The image quality scores, CNR, SIR, and ADC value of r-FOV DWI were significantly higher than those of conventional DWI (all p<0.05), and the SNR of r-FOV DWI was significantly lower (p<0.001). ADCr showed statistical differences in all pairwise comparisons among the three groups (all p<0.05), while ADCc showed significant difference only between hypo- and normocellular group and severely hypercellular group (p=0.014). The performance of ADCr in evaluating BMC (Z=2.380, p=0.017) and its correlations with BMC (Z=-2.008, p = 0.045) and WBC (Z=-2.022, p = 0.043) were significantly higher than those of ADCc. Conclusion Compared with conventional DWI, r-FOV DWI provides superior image quality of the lumbar spine in AL patients, thus yielding better performance in assessing bone marrow infiltration.
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Affiliation(s)
- Wenjin Bian
- Department of Medical Imaging, Shanxi Medical University, Taiyuan, Shanxi, China
- Department of Radiology, The Second Hospital of Shanxi Medical University, Taiyuan, Shanxi, China
| | - Luyao Wang
- Department of Medical Imaging, Shanxi Medical University, Taiyuan, Shanxi, China
| | - Jianting Li
- Department of Radiology, The Second Hospital of Shanxi Medical University, Taiyuan, Shanxi, China
| | - Sha Cui
- Department of Radiology, The Second Hospital of Shanxi Medical University, Taiyuan, Shanxi, China
| | - Wenqi Wu
- Department of Radiology, The Second Hospital of Shanxi Medical University, Taiyuan, Shanxi, China
| | - Rong Fan
- Department of Radiology, The Second Hospital of Shanxi Medical University, Taiyuan, Shanxi, China
| | - Jinliang Niu
- Department of Radiology, The Second Hospital of Shanxi Medical University, Taiyuan, Shanxi, China
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Zheng T, Xie X, Ni Z, Tang L, Wu PY, Song B. Quantitative evaluation of diffusion-weighted MRI for differentiating benign and malignant thyroid nodules larger than 4 cm. BMC Med Imaging 2023; 23:212. [PMID: 38093189 PMCID: PMC10720093 DOI: 10.1186/s12880-023-01141-z] [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: 07/11/2023] [Accepted: 10/26/2023] [Indexed: 12/17/2023] Open
Abstract
PURPOSE Our study aimed to diagnose benign or malignant thyroid nodules larger than 4 cm using quantitative diffusion-weighted imaging (DWI) analysis. METHODS Eighty-two thyroid nodules were investigated retrospectively and divided them into benign (n = 62) and malignant groups (n = 20). We calculated quantitative features DWI and apparent diffusion coefficient (ADC) signal intensity standard deviation (DWISD and ADCSD), DWI and ADC signal intensity ratio (DWISIR and ADCSIR), mean ADC and minimum ADC value (ADCmean and ADCmin) and ADC value standard deviation (ADCVSD). Univariate and multivariate logistic regression were conducted to identify independent predictors, and develop a prediction model. We performed receiver operating characteristic (ROC) analysis to determine the optimal threshold of risk factors, and constructed combined threshold models. Our study calculated diagnostic performance including area under the ROC curve (AUC), accuracy, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and unnecessary biopsy rate of all models were calculated and compared them with the American College of Radiology Thyroid Imaging Reporting and Data System (ACR-TIRADS) result. RESULTS Two independent predictors of malignant nodules were identified by multivariate analysis: DWISIR (P = 0.007) and ADCmin (P < 0.001). The AUCs for multivariate prediction model, combined DWISIR and ADCmin thresholds model, combined DWISIR and ADCSIR thresholds model and ACR-TIRADS were 0.946 (0.896-0.996), 0.875 (0.759-0.991), 0.777 (0.648-0.907) and 0.722 (0.588-0.857). The combined DWISIR and ADCmin threshold model had the lowest unnecessary biopsy rate of 0%, compared with 56.3% for ACR-TIRADS. CONCLUSION Quantitative DWI demonstrated favorable malignant thyroid nodule diagnostic efficacy. The combined DWISIR and ADCmin thresholds model significantly reduced the unnecessary biopsy rate.
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Affiliation(s)
- Tingting Zheng
- Department of Radiology, Minhang Hospital, Fudan University, No 170, Xinsong Road, Minhang District, Shanghai, 201199, China
| | - Xiaoli Xie
- Department of Pathology, Minhang Hospital, Fudan University, No 170, Xinsong Road, Minhang District, Shanghai, 201199, China
| | - Zhaoxian Ni
- Department of General Surgery, Minhang Hospital, Fudan University, No 170, Xinsong Road, Minhang District, Shanghai, 201199, China
| | - Lang Tang
- Department of Ultrasound, Minhang Hospital, Fudan University, No 170, Xinsong Road, Minhang District, Shanghai, 201199, China
| | - Pu-Yeh Wu
- GE Healthcare, MR Research China, Beijing, China
| | - Bin Song
- Department of Radiology, Minhang Hospital, Fudan University, No 170, Xinsong Road, Minhang District, Shanghai, 201199, China.
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Sumiyoshi A, Shibata S, Lazarova D, Zhelev Z, Aoki I, Bakalova R. Tolerable treatment of glioblastoma with redox-cycling 'mitocans': a comparative study in vivo. Redox Rep 2023; 28:2220531. [PMID: 37581329 PMCID: PMC10435007 DOI: 10.1080/13510002.2023.2220531] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/16/2023] Open
Abstract
Objectives: The present study describes a pharmacological strategy for the treatment of glioblastoma by redoxcycling 'mitocans' such as quinone/ascorbate combination drugs, based on their tumor-selective redox-modulating effects and tolerance to normal cells and tissues.Methods: Experiments were performed on glioblastoma mice (orthotopic model) treated with coenzyme Q0/ascorbate (Q0/A). The drug was injected intracranially in a single dose. The following parameters were analyzed in vivo using MRI orex vivo using conventional assays: tumor growth, survival, cerebral and tumor perfusion, tumor cell density, tissue redox-state, and expression of tumor-associated NADH oxidase (tNOX).Results: Q0/A markedly suppressed tumor growth and significantly increased survival of glioblastoma mice. This was accompanied by increased oxidative stress in the tumor but not in non-cancerous tissues, increased tumor blood flow, and downregulation of tNOX. The redox-modulating and anticancer effects of Q0/A were more pronounced than those of menadione/ascorbate (M/A) obtained in our previous study. No adverse drug-related side-effects were observed in glioblastoma mice treated with Q0/A.Discussion: Q0/A differentiated cancer cells and tissues, particularly glioblastoma, from normal ones by redox targeting, causing a severe oxidative stress in the tumor but not in non-cancerous tissues. Q0/A had a pronounced anticancer activity and could be considered safe for the organism within certain concentration limits. The results suggest that the rate of tumor resorption and metabolism of toxic residues must be controlled and maintained within tolerable limits to achieve longer survival, especially at intracranial drug administration.
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Affiliation(s)
- Akira Sumiyoshi
- Department of Molecular Imaging and Theranostics, National Institutes for Quantum Science and Technology (QST), Chiba, Japan
| | - Sayaka Shibata
- Department of Molecular Imaging and Theranostics, National Institutes for Quantum Science and Technology (QST), Chiba, Japan
| | - Dessislava Lazarova
- Faculty of Medicine, Sofia University, “St. Kliment Ohridski”, Sofia, Bulgaria
| | - Zhivko Zhelev
- Faculty of Medicine, Trakia University, Stara Zagora, Bulgaria
- Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, Sofia, Bulgaria
| | - Ichio Aoki
- Department of Molecular Imaging and Theranostics, National Institutes for Quantum Science and Technology (QST), Chiba, Japan
| | - Rumiana Bakalova
- Department of Molecular Imaging and Theranostics, National Institutes for Quantum Science and Technology (QST), Chiba, Japan
- Faculty of Medicine, Sofia University, “St. Kliment Ohridski”, Sofia, Bulgaria
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Janse MHA, Janssen LM, van der Velden BHM, Moman MR, Wolters-van der Ben EJM, Kock MCJM, Viergever MA, van Diest PJ, Gilhuijs KGA. Deep Learning-Based Segmentation of Locally Advanced Breast Cancer on MRI in Relation to Residual Cancer Burden: A Multi-Institutional Cohort Study. J Magn Reson Imaging 2023; 58:1739-1749. [PMID: 36928988 DOI: 10.1002/jmri.28679] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2022] [Revised: 02/22/2023] [Accepted: 02/24/2023] [Indexed: 03/18/2023] Open
Abstract
BACKGROUND While several methods have been proposed for automated assessment of breast-cancer response to neoadjuvant chemotherapy on breast MRI, limited information is available about their performance across multiple institutions. PURPOSE To assess the value and robustness of deep learning-derived volumes of locally advanced breast cancer (LABC) on MRI to infer the presence of residual disease after neoadjuvant chemotherapy. STUDY TYPE Retrospective. SUBJECTS Training cohort: 102 consecutive female patients with LABC scheduled for neoadjuvant chemotherapy (NAC) from a single institution (age: 25-73 years). Independent testing cohort: 55 consecutive female patients with LABC from four institutions (age: 25-72 years). FIELD STRENGTH/SEQUENCE Training cohort: single vendor 1.5 T or 3.0 T. Testing cohort: multivendor 3.0 T. Gradient echo dynamic contrast-enhanced sequences. ASSESSMENT A convolutional neural network (nnU-Net) was trained to segment LABC. Based on resulting tumor volumes, an extremely randomized tree model was trained to assess residual cancer burden (RCB)-0/I vs. RCB-II/III. An independent model was developed using functional tumor volume (FTV). Models were tested on an independent testing cohort and response assessment performance and robustness across multiple institutions were assessed. STATISTICAL TESTS The receiver operating characteristic (ROC) was used to calculate the area under the ROC curve (AUC). DeLong's method was used to compare AUCs. Correlations were calculated using Pearson's method. P values <0.05 were considered significant. RESULTS Automated segmentation resulted in a median (interquartile range [IQR]) Dice score of 0.87 (0.62-0.93), with similar volumetric measurements (R = 0.95, P < 0.05). Automated volumetric measurements were significantly correlated with FTV (R = 0.80). Tumor volume-derived from deep learning of DCE-MRI was associated with RCB, yielding an AUC of 0.76 to discriminate between RCB-0/I and RCB-II/III, performing similar to the FTV-based model (AUC = 0.77, P = 0.66). Performance was comparable across institutions (IQR AUC: 0.71-0.84). DATA CONCLUSION Deep learning-based segmentation estimates changes in tumor load on DCE-MRI that are associated with RCB after NAC and is robust against variations between institutions. EVIDENCE LEVEL 2. TECHNICAL EFFICACY Stage 4.
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Affiliation(s)
- Markus H A Janse
- Image Sciences Institute, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Liselore M Janssen
- Image Sciences Institute, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Bas H M van der Velden
- Image Sciences Institute, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Maaike R Moman
- Image Sciences Institute, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
- Alexander Monro Hospital, Bilthoven, The Netherlands
| | | | - Marc C J M Kock
- Department of Radiology, Albert Schweitzer Hospital, Dordrecht, The Netherlands
| | - Max A Viergever
- Image Sciences Institute, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Paul J van Diest
- Department of Pathology, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Kenneth G A Gilhuijs
- Image Sciences Institute, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
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Sim KC, Han NY, Cho Y, Sung DJ, Park BJ, Kim MJ, Han YE. Machine Learning-Based Magnetic Resonance Radiomics Analysis for Predicting Low- and High-Grade Clear Cell Renal Cell Carcinoma. J Comput Assist Tomogr 2023; 47:873-881. [PMID: 37948361 DOI: 10.1097/rct.0000000000001453] [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: 11/12/2023]
Abstract
PURPOSE To explore whether high- and low-grade clear cell renal cell carcinomas (ccRCC) can be distinguished using radiomics features extracted from magnetic resonance imaging. METHODS In this retrospective study, 154 patients with pathologically proven clear ccRCC underwent contrast-enhanced 3 T magnetic resonance imaging and were assigned to the development (n = 122) and test (n = 32) cohorts in a temporal-split setup. A total of 834 radiomics features were extracted from whole-tumor volumes using 3 sequences: T2-weighted imaging (T2WI), diffusion-weighted imaging, and contrast-enhanced T1-weighted imaging. A random forest regressor was used to extract important radiomics features that were subsequently used for model development using the random forest algorithm. Tumor size, apparent diffusion coefficient value, and percentage of tumor-to-renal parenchymal signal intensity drop in the tumors were recorded by 2 radiologists for quantitative analysis. The area under the receiver operating characteristic curve (AUC) was generated to predict ccRCC grade. RESULTS In the development cohort, the T2WI-based radiomics model demonstrated the highest performance (AUC, 0.82). The T2WI-based radiomics and radiologic feature hybrid model showed AUCs of 0.79 and 0.83, respectively. In the test cohort, the T2WI-based radiomics model achieved an AUC of 0.82. The range of AUCs of the hybrid model of T2WI-based radiomics and radiologic features was 0.73 to 0.80. CONCLUSION Magnetic resonance imaging-based classifier models using radiomics features and machine learning showed satisfactory diagnostic performance in distinguishing between high- and low-grade ccRCC, thereby serving as a helpful noninvasive tool for predicting ccRCC grade.
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Affiliation(s)
- Ki Choon Sim
- From the Department of Radiology, Korea University Anam Hospital, Korea University College of Medicine
| | - Na Yeon Han
- From the Department of Radiology, Korea University Anam Hospital, Korea University College of Medicine
| | - Yongwon Cho
- Department of Radiology and AI Center, Korea University Anam Hospital, Korea University College of Medicine, Seoul, Republic of Korea
| | - Deuk Jae Sung
- From the Department of Radiology, Korea University Anam Hospital, Korea University College of Medicine
| | - Beom Jin Park
- From the Department of Radiology, Korea University Anam Hospital, Korea University College of Medicine
| | - Min Ju Kim
- From the Department of Radiology, Korea University Anam Hospital, Korea University College of Medicine
| | - Yeo Eun Han
- From the Department of Radiology, Korea University Anam Hospital, Korea University College of Medicine
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20
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Bizzarri N, Russo L, Dolciami M, Zormpas-Petridis K, Boldrini L, Querleu D, Ferrandina G, Pedone Anchora L, Gui B, Sala E, Scambia G. Radiomics systematic review in cervical cancer: gynecological oncologists' perspective. Int J Gynecol Cancer 2023; 33:1522-1541. [PMID: 37714669 DOI: 10.1136/ijgc-2023-004589] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/17/2023] Open
Abstract
OBJECTIVE Radiomics is the process of extracting quantitative features from radiological images, and represents a relatively new field in gynecological cancers. Cervical cancer has been the most studied gynecological tumor for what concerns radiomics analysis. The aim of this study was to report on the clinical applications of radiomics combined and/or compared with clinical-pathological variables in patients with cervical cancer. METHODS A systematic review of the literature from inception to February 2023 was performed, including studies on cervical cancer analysing a predictive/prognostic radiomics model, which was combined and/or compared with a radiological or a clinical-pathological model. RESULTS A total of 57 of 334 (17.1%) screened studies met inclusion criteria. The majority of studies used magnetic resonance imaging (MRI), but positron emission tomography (PET)/computed tomography (CT) scan, CT scan, and ultrasound scan also underwent radiomics analysis. In apparent early-stage disease, the majority of studies (16/27, 59.3%) analysed the role of radiomics signature in predicting lymph node metastasis; six (22.2%) investigated the prediction of radiomics to detect lymphovascular space involvement, one (3.7%) investigated depth of stromal infiltration, and one investigated (3.7%) parametrial infiltration. Survival prediction was evaluated both in early-stage and locally advanced settings. No study focused on the application of radiomics in metastatic or recurrent disease. CONCLUSION Radiomics signatures were predictive of pathological and oncological outcomes, particularly if combined with clinical variables. These may be integrated in a model using different clinical-pathological and translational characteristics, with the aim to tailor and personalize the treatment of each patient with cervical cancer.
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Affiliation(s)
- Nicolò Bizzarri
- UOC Ginecologia Oncologica, Dipartimento per la salute della Donna e del Bambino e della Salute Pubblica, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, Italy
| | - Luca Russo
- Department of Bioimaging, Radiation Oncology and Hematology, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, Italy
| | - Miriam Dolciami
- Department of Bioimaging, Radiation Oncology and Hematology, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, Italy
| | - Konstantinos Zormpas-Petridis
- Department of Bioimaging, Radiation Oncology and Hematology, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, Italy
| | - Luca Boldrini
- Department of Bioimaging, Radiation Oncology and Hematology, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, Italy
| | - Denis Querleu
- UOC Ginecologia Oncologica, Dipartimento per la salute della Donna e del Bambino e della Salute Pubblica, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, Italy
| | - Gabriella Ferrandina
- UOC Ginecologia Oncologica, Dipartimento per la salute della Donna e del Bambino e della Salute Pubblica, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, Italy
- Università Cattolica del Sacro Cuore, Rome, Italy
| | - Luigi Pedone Anchora
- UOC Ginecologia Oncologica, Dipartimento per la salute della Donna e del Bambino e della Salute Pubblica, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, Italy
| | - Benedetta Gui
- Department of Bioimaging, Radiation Oncology and Hematology, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, Italy
| | - Evis Sala
- Department of Bioimaging, Radiation Oncology and Hematology, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, Italy
- Università Cattolica del Sacro Cuore, Rome, Italy
| | - Giovanni Scambia
- UOC Ginecologia Oncologica, Dipartimento per la salute della Donna e del Bambino e della Salute Pubblica, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, Italy
- Università Cattolica del Sacro Cuore, Rome, Italy
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Ai X, Wang H, Yang Y, Feng Y, Xie X, Zhao X, Li J, Yao P, Zhu Q. Four indices on Gd-EOB-DTPA-enhanced MRI can estimate liver functional reserve compared to ICG-R15: A systematic review and meta-analysis. Clin Imaging 2023; 102:1-8. [PMID: 37437466 DOI: 10.1016/j.clinimag.2023.06.018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2023] [Revised: 05/19/2023] [Accepted: 06/29/2023] [Indexed: 07/14/2023]
Abstract
AIMS To evaluate the value of four indices of gadolinium-ethoxybenzyl-diethylenetriamine pentaacetic acid-enhanced (Gd-EOB-DTPA) magnetic resonance as a potential imaging marker of liver functional reserve. METHODS PubMed/Medline, Embase, Cochrane Library, and Web of Science were searched for studies concerning the relationship between Gd-EOB-DTPA-enhanced MRI and liver functional reserve estimated by ICG-R15, Pooled correlation coefficient (r) and 95% confidence intervals (CIs) were calculated, Meanwhile, Sensitivity and subgroup analyses were performed along with Egger's test for the estimation of publication bias and potential heterogeneity. RESULTS 14 publications with 1285 patients were included. The pooled r between relative liver enhancement (RLE), reduction rate of T1 relaxation time of the liver (rrT1), liver-to-spleen ratio (LSR), liver-to-muscle ratio (LMR), and ICG-R15 were -0.49 (95% CI, -0.56 to -0.41, p < 0.05), -0.47 (95% CI, -0.57 to -0.36, p < 0.05), -0.45 (95% CI, -0.55 to -0.34, p < 0.05), -0.50 (95% CI, -0.61 to -0.38, p < 0.05). moderate heterogeneity was observed between studies on rrT1, LSR, LMR, and ICG-R15 (p ≤ 0.05), but no significant heterogeneity was observed between RLE and ICG-R15. Further analysis shows that there was a notable heterogeneity between subgroup analysis of LSR and ICG-R15 stratified by years of publication, as well as rrT1 and LMR stratified by total patients and study design, the distribution funnel plots and the results of Egger's test showed no evidence of publication bias. CONCLUSIONS RLE, LSR, LMR, and rrT1 all correlated significantly with ICG-R15-estimated hepatic functional reserve. The four indices represent a promising imaging biomarker in the prediction of liver functional reserve.
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Affiliation(s)
- Xin Ai
- Department of Infectious Disease, Jining No. 1 People's Hospital, No. 6, Health Road, Rencheng District, Jining, Shandong Province 272002, China
| | - Haikun Wang
- Department of Gastroenterology, The First Affiliated Hospital of Xinjiang Medical University, No. 137, Liyushan Road, Xinshi District, Urumqi, Xinjiang Uygur Autonomous Region 830000, China
| | - Yao Yang
- Department of Gastroenterology, Shandong Provincial Hospital Affiliated to Shandong University, 324, Jing 5 Rd, Jinan, Shandong Province 250021, China
| | - Yuemin Feng
- Department of Gastroenterology, Shandong Provincial Hospital Affiliated to Shandong University, 324, Jing 5 Rd, Jinan, Shandong Province 250021, China
| | - Xiaoyu Xie
- Department of Gastroenterology, Qilu Hospital Affiliated to Shandong University, No. 107, Wenhua West Road, Jinan, Shandong Province 250021, China
| | - Xinya Zhao
- Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong University, 324, Jing 5 Rd, Ji'nan, Shandong Province 250021, China
| | - Jie Li
- Department of Infectious Diseases, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, No. 321, Zhongshan Road, Nanjing 210008, China
| | - Ping Yao
- Department of Gastroenterology, The First Affiliated Hospital of Xinjiang Medical University, No. 137, Liyushan Road, Xinshi District, Urumqi, Xinjiang Uygur Autonomous Region 830000, China.
| | - Qiang Zhu
- Department of Gastroenterology, The First Affiliated Hospital of Xinjiang Medical University, No. 137, Liyushan Road, Xinshi District, Urumqi, Xinjiang Uygur Autonomous Region 830000, China; Department of Gastroenterology, Shandong Provincial Hospital Affiliated to Shandong University, 324, Jing 5 Rd, Jinan, Shandong Province 250021, China.
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Gülçin Bozbeyoğlu S, Perçem Orhan Söylemez U, Gündüz N. MRI reliability in pediatric abdominal lymph node metastases? Acta Radiol 2023; 64:2777-2782. [PMID: 37464785 DOI: 10.1177/02841851231184620] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/20/2023]
Abstract
BACKGROUND Although positron emission tomography-computed tomography (PET-CT) is an effective imaging method used in the detection of lymph node metastases, repeated imaging increases X-ray exposure, especially in pediatric patients. Magnetic resonance imaging (MRI) may detect abdominal lymph nodes and provide subtle anatomic detail, and functional information without radiation. PURPOSE To evaluate the reliability of MRI in detecting lymph node metastases in pediatric abdominal malignancies and to determine whether X-ray dose can be reduced by comparing its effectiveness with PET-CT. MATERIAL AND METHODS Patients aged <18 years, diagnosed with abdominal malignant solid lesions between January 2015 and 2022 were included in this retrospective single-center study. A total of 14 A total of 14 different anatomic locations were defined for lymph nodes in MRI and PET-CT examinations. Cohen's kappa test was used to evaluate the consistency between PET-CT and MRI. P < 0.05 was considered statistically significant. RESULTS In total, 25 patients (18 [72%] girls, 7 [28%] boys; mean age = 9.32 ± 16.9 years; age range = 1-18 years) with abdominal solid malignant tumors were included. The reliability of MRI and inter-observer reliability differed depending on the location of the lymph nodes. The reliability was almost perfect for the internal iliac (k = 0.915), porta hepatis, and aortocaval lymph node stations, while fair reliability was observed for the mesenteric lymph nodes (k = 0.525). CONCLUSION The results showed that MRI was as reliable as PET-CT in detecting some intra-abdominal metastatic lymph nodes, while its reliability was lower in some lymph node stations.
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Affiliation(s)
| | | | - Nesrin Gündüz
- Department of Radiology, Faculty of Medicine, Goztepe Prof. Dr. Suleyman Yalcin City Hospital, Istanbul Medeniyet University, Istanbul, Turkey
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Sui H, Yang J, Xiang H, Yan C. Combining ADC values in DWI with rCBF values in arterial spin labeling (ASL) for the diagnosis of mild cognitive impairment (MCI). Medicine (Baltimore) 2023; 102:e34979. [PMID: 37713879 PMCID: PMC10508430 DOI: 10.1097/md.0000000000034979] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/24/2023] [Accepted: 08/07/2023] [Indexed: 09/17/2023] Open
Abstract
We aimed to investigate the role of combined apparent diffusion coefficient (ADC) values and relative cerebral blood flow (rCBF) values in the diagnosis of mild cognitive impairment (MCI) patients. The present prospective research enrolled 156 MCI patients and 58 healthy elderly people who came to our hospital from January 2021 to February 2023. T1W, T2W, diffusion-weighted imaging, and arterial spin labeling sequences were performed on all subjects, and ADC values and rCBF values were measured at the workstation. Clinical and demographic data of all patients were collected while mini-mental state examination (MMSE) and Montreal cognitive assessment (MoCA) scores were used to assess patients' cognitive abilities. The MCI group had significantly lower rCBF values in the left frontal lobe, left occipital lobe, right frontal lobe, and right occipital lobe than the HC group. The ADC values in the left frontal lobe as well as the right frontal lobe were remarkably elevated in the MCI group than in the HC group. MoCA and MMSE scores were positively correlated with rCBF values in the left frontal, right frontal, left occipital, and right occipital lobes and negatively correlated with ADC values in the left and right frontal lobes. Combined ADC values and rCBF values from the left frontal lobe for the diagnosis of MCI had a higher sensitivity and specificity with the AUC was 0.877, sensitivity 81.0%, specificity 82.7%. Additionally, pressure fasting plasma glucose, ADC of the left frontal lobe, right frontal lobe, rCBF of left frontal lobe and rCBF of left frontal lobe were the risk factors of patients with MCI. In summary, our results indicated that the ADC values and rCBF values were changed in MCI group compared to HC group and correlated with MMSE and MoCA scores.
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Affiliation(s)
- Haijing Sui
- Department of Radiology, Shanghai Pudong New Area People’s Hospital, Shanghai, China
| | - Juan Yang
- Department of Neurology, Shanghai Pudong New Area People’s Hospital, Shanghai, China
| | - Honggang Xiang
- Department of Surgery, Shanghai Pudong New Area People’s Hospital, Shanghai, China
| | - Chenggong Yan
- Department of Radiology, Shanghai Pudong New Area Hospital of Traditional Chinese Medicine, Shanghai, China
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Nalbant MO, Erdil I, Akcay N, Inci E, Palabiyik F. Volumetric apparent diffusion coefficient (ADC) histogram analysis of the brain in paediatric patients with hypoxic ischaemic encephalopathy. Pol J Radiol 2023; 88:e399-e406. [PMID: 37808174 PMCID: PMC10551736 DOI: 10.5114/pjr.2023.131696] [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: 05/17/2023] [Accepted: 07/30/2023] [Indexed: 10/10/2023] Open
Abstract
Purpose To evaluate the whole brain, hippocampus, thalamus, and lentiform nucleus by volumetric apparent diffusion coefficient (ADC) histogram analysis in paediatric patients with hypoxic-ischaemic encephalopathy (HIE). Material and methods This retrospective study included 25 patients with HIE and 50 patients as the control group. Diffusion-weighted imaging was obtained at b-values of 1000 mm2/s. The histogram parameters of ADC values, including the mean, minimum, maximum, 5th, 10th, 25th, 50th, 75th, 90th, and 95th percentiles, as well as skewness, kurtosis, and variance were determined. The interclass correlation coefficient (ICC) was used to assess the inter-observer agreement. Results ADCmin, ADCmean, and ADCmax, as well as the 5th, 10th, 25th, 50th, 75th, 90th, and 95th percentiles of ADC values for the HIE group were all lower than those of the control group (p < 0.001) in the volumetric histogram analysis of the hippocampus, thalamus, and lentiform nucleus. In the whole-brain histogram analysis, ADC min, and the 50th and 75th percentiles of ADC values did not differ significantly, while other parameters were lower in the HIE group. The ROC curve revealed that the ADC histogram parameters of the hippocampus provided the most accurate results for the diagnosis of HIE. The area under the curve (AUC) of the 95th percentile of ADC values was the highest (AUC = 0.915; cut-off 1.262 × 10-3 mm2/s; sensitivity 88% and specificity 84%). Conclusions Volumetric ADC histogram analysis of the whole brain, hippocampus, thalamus, and lentiform nucleus with b-values of 1000 mm2/s can serve as an imaging marker for determining HIE.
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Affiliation(s)
- Mustafa Orhan Nalbant
- Department of Radiology, Bakirkoy Dr. Sadi Konuk Training and Research Hospital, University of Health Sciences, Bakırkoy, Istanbul, Turkey
| | - Irem Erdil
- Department of Radiology, Bakirkoy Dr. Sadi Konuk Training and Research Hospital, University of Health Sciences, Bakırkoy, Istanbul, Turkey
| | - Nihal Akcay
- Department of Paediatric Intensive Care, Bakirkoy Dr. Sadi Konuk Training and Research Hospital, University of Health Sciences, Bakırkoy, Istanbul, Turkey
| | - Ercan Inci
- Department of Radiology, Bakirkoy Dr. Sadi Konuk Training and Research Hospital, University of Health Sciences, Bakırkoy, Istanbul, Turkey
| | - Figen Palabiyik
- Department of Radiology, Bakirkoy Dr. Sadi Konuk Training and Research Hospital, University of Health Sciences, Bakırkoy, Istanbul, Turkey
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Nalbant MO, Oner O, Akinci O, Hocaoglu E, Inci E. Analysis of Pancreatobiliary and Intestinal Type Periampullary Carcinomas Using Volumetric Apparent Diffusion Coefficient Histograms. Acad Radiol 2023; 30 Suppl 1:S238-S245. [PMID: 37211479 DOI: 10.1016/j.acra.2023.04.031] [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: 04/02/2023] [Revised: 04/21/2023] [Accepted: 04/22/2023] [Indexed: 05/23/2023]
Abstract
RATIONALE AND OBJECTIVES Magnetic resonance imaging plays an important role in the evaluation of patients with known or suspected periampullary masses. The utilization of volumetric apparent diffusion coefficient (ADC) histogram evaluation for the entire lesion eradicates the potential for subjectivity in the region of interest placement, thus guaranteeing the accuracy of computation and repeatability. PURPOSE To investigate the value of volumetric ADC histogram analysis in the differentiation of intestinal-type (IPAC) and pancreatobiliary-type periampullary adenocarcinomas (PPAC). MATERIALS AND METHODS This retrospective study included 69 patients with histopathologically confirmed periampullary adenocarcinoma (54 PPAC and 15 IPAC). Diffusion-weighted imaging was obtained at b values of 1000 mm²/s. The histogram parameters of ADC values, comprising the mean, minimum, maximum, 5th, 10th, 25th, 50th, 75th, 90th, and 95th percentiles, as well as skewness, kurtosis, and variance, were calculated independently by two radiologists. Using the interclass correlation coefficient, the interobserver agreement was evaluated. RESULTS The ADC parameters for the PPAC group were all lower than those of the IPAC group. The PPAC group had higher variance, skewness, and kurtosis than the IPAC group. However, the difference between the kurtosis (P = .003), the 5th (P = .032), 10th (P = .043), and 25th (P = .037) percentiles of ADC values was statistically significant. The area under the curve (AUC) of the kurtosis was the highest (AUC=0.752; cut-off value=-0.235; sensitivity=61.1%; specificity=80.0%). CONCLUSION Volumetric ADC histogram analysis with b values of 1000 mm²/s can discriminate subtypes noninvasively before surgery.
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Affiliation(s)
- Mustafa Orhan Nalbant
- University of Health Sciences, Bakirkoy Dr. Sadi Konuk Training and Research Hospital, Radiology Department, Tevfik Saglam Cad. No: 11, Zuhuratbaba, 34147 Bakırkoy, Istanbul, Turkey.
| | - Ozkan Oner
- University of Health Sciences, Bakirkoy Dr. Sadi Konuk Training and Research Hospital, Radiology Department, Tevfik Saglam Cad. No: 11, Zuhuratbaba, 34147 Bakırkoy, Istanbul, Turkey
| | - Ozlem Akinci
- University of Health Sciences, Bakirkoy Dr. Sadi Konuk Training and Research Hospital, Radiology Department, Tevfik Saglam Cad. No: 11, Zuhuratbaba, 34147 Bakırkoy, Istanbul, Turkey
| | - Elif Hocaoglu
- University of Health Sciences, Bakirkoy Dr. Sadi Konuk Training and Research Hospital, Radiology Department, Tevfik Saglam Cad. No: 11, Zuhuratbaba, 34147 Bakırkoy, Istanbul, Turkey
| | - Ercan Inci
- University of Health Sciences, Bakirkoy Dr. Sadi Konuk Training and Research Hospital, Radiology Department, Tevfik Saglam Cad. No: 11, Zuhuratbaba, 34147 Bakırkoy, Istanbul, Turkey
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Geng Y, Hong R, Cheng Y, Zhang F, Sha Y, Song Y. Whole-tumor histogram analysis of apparent diffusion coefficient maps with machine learning algorithms for predicting histologic grade of sinonasal squamous cell carcinoma: a preliminary study. Eur Arch Otorhinolaryngol 2023; 280:4131-4140. [PMID: 37160465 DOI: 10.1007/s00405-023-07989-9] [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: 01/05/2023] [Accepted: 04/18/2023] [Indexed: 05/11/2023]
Abstract
PURPOSE Accurate histologic grade assessment is helpful for clinical decision making and prognostic assessment of sinonasal squamous cell carcinoma (SNSCC). This research aimed to explore whether whole-tumor histogram analysis of apparent diffusion coefficient (ADC) maps with machine learning algorithms can predict histologic grade of SNSCC. METHODS One hundred and forty-seven patients with pathologically diagnosed SNSCC formed this retrospective study. Sixty-six patients were low-grade (grade I/II) and eighty-one patients were high-grade (grade III). Eighteen histogram features were obtained from quantitative ADC maps. Additionally, the mean ADC value and clinical features were analyzed for comparison with histogram features. Machine learning algorithms were applied to build the best diagnostic model for predicting histological grade. The receiver operating characteristic (ROC) curve was used to evaluate the performance of each model prediction, and the area under the ROC curve (AUC) were analyzed. RESULTS The histogram model based on three features (10th Percentile, Mean, and 90th Percentile) with support vector machine (SVM) classifier demonstrated excellent diagnostic performance, with an AUC of 0.947 on the testing dataset. The AUC of the histogram model was similar to that of the mean ADC value model (0.947 vs 0.957; P = 0.7029). The poor diagnostic performance of the clinical model (AUC = 0.692) was improved by the combined model incorporating histogram features or mean ADC value (P < 0.05). CONCLUSION ADC histogram analysis improved the projection of SNSCC histologic grade, compared with clinical model. The complex histogram model had comparable but not better performance than mean ADC value model.
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Affiliation(s)
- Yue Geng
- Department of Radiology, Eye & ENT Hospital, Fudan University, 83 Fenyang Road, Shanghai, 200031, China
| | - Rujian Hong
- Department of Radiology, Eye & ENT Hospital, Fudan University, 83 Fenyang Road, Shanghai, 200031, China
| | - Yushu Cheng
- Department of Radiology, Eye & ENT Hospital, Fudan University, 83 Fenyang Road, Shanghai, 200031, China
| | - Fang Zhang
- Department of Radiology, Eye & ENT Hospital, Fudan University, 83 Fenyang Road, Shanghai, 200031, China
| | - Yan Sha
- Department of Radiology, Eye & ENT Hospital, Fudan University, 83 Fenyang Road, Shanghai, 200031, China.
| | - Yang Song
- Scientific Marketing, Siemens Healthineers, Shanghai, 200336, China
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Nalbant MO, Inci E, Akinci O, Aygan S, Gulturk U, Boluk Gulsever A. Evaluation of Imaging Findings of Pancreatobiliary and Intestinal Type Periampullary Carcinomas with 3.0T MRI. Acad Radiol 2023; 30:1846-1855. [PMID: 36585328 DOI: 10.1016/j.acra.2022.12.028] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2022] [Revised: 12/13/2022] [Accepted: 12/16/2022] [Indexed: 12/29/2022]
Abstract
RATIONALE AND OBJECTIVES The aim of this study was to differentiate pancreatobiliary and intestinal type periampullary carcinomas using dynamic contrast MRI and MRCP (Magnetic Resonance Cholangiopancreatography) with diffusion-weighted imaging (DWI) MATERIALS AND METHODS: MRI and MRCP images of 70 patients with pathologically proven periampullary adenocarcinoma were included. MRCP image features, extra-ampullary features, enhancement patterns, and apparent diffusion coefficient (ADC) values derived from b-values of 1000 s/mm² were evaluated by two radiologists independently. The interclass correlation coefficient (ICC) or Cohen's kappa statistic was used to evaluate the interobserver agreement. RESULTS 51 patients were diagnosed with pancreatobiliary type carcinomas, and 19 with intestinal type. In the pancreatobiliary subtype, the distal wall of the common bile duct was usually irregular (p = 0.047). Although the progressive enhancement pattern was evident in the pancreatobiliary type, an oval filling defect in the distal common bile duct was found to be more common in the intestinal type (p<0.001). The pancreatic duct cut-off sign (p<0.001), gastroduodenal artery involvement (p <0,001), and lymphadenopathy (p<0.05) were mostly observed in pancreatobiliary carcinomas. The ADCmin, ADCmean, and ADCmax values of the pancreatobiliary type carcinomas were all lower compared to the intestinal type carcinomas (p <0.05). CONCLUSION The oval filling defect seen in MRI and MRCP examinations suggests intestinal type, whereas the progressive contrasting pattern of the masses with irregular narrowing in the distal margin of the common bile duct, the pancreatic duct cut-off sign, gastroduodenal artery involvement, lymphadenopathy, and low ADC values indicate pancreatobiliary type carcinomas.
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Affiliation(s)
- Mustafa Orhan Nalbant
- Radiology Department, University of Health Sciences, Bakirkoy Dr. Sadi Konuk Training and Research Hospital, Istanbul, Turkey.
| | - Ercan Inci
- Radiology Department, University of Health Sciences, Bakirkoy Dr. Sadi Konuk Training and Research Hospital, Istanbul, Turkey
| | - Ozlem Akinci
- Radiology Department, University of Health Sciences, Bakirkoy Dr. Sadi Konuk Training and Research Hospital, Istanbul, Turkey
| | - Sinan Aygan
- Radiology Department, University of Health Sciences, Bakirkoy Dr. Sadi Konuk Training and Research Hospital, Istanbul, Turkey
| | - Ulas Gulturk
- Radiology Department, University of Health Sciences, Bakirkoy Dr. Sadi Konuk Training and Research Hospital, Istanbul, Turkey
| | - Aycan Boluk Gulsever
- Radiology Department, University of Health Sciences, Bakirkoy Dr. Sadi Konuk Training and Research Hospital, Istanbul, Turkey
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Bisgaard ALH, Keesman R, van Lier ALHMW, Coolens C, van Houdt PJ, Tree A, Wetscherek A, Romesser PB, Tyagi N, Lo Russo M, Habrich J, Vesprini D, Lau AZ, Mook S, Chung P, Kerkmeijer LGW, Gouw ZAR, Lorenzen EL, van der Heide UA, Schytte T, Brink C, Mahmood F. Recommendations for improved reproducibility of ADC derivation on behalf of the Elekta MRI-linac consortium image analysis working group. Radiother Oncol 2023; 186:109803. [PMID: 37437609 PMCID: PMC11197850 DOI: 10.1016/j.radonc.2023.109803] [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: 01/19/2023] [Revised: 06/30/2023] [Accepted: 07/06/2023] [Indexed: 07/14/2023]
Abstract
BACKGROUND AND PURPOSE The apparent diffusion coefficient (ADC), a potential imaging biomarker for radiotherapy response, needs to be reproducible before translation into clinical use. The aim of this study was to evaluate the multi-centre delineation- and calculation-related ADC variation and give recommendations to minimize it. MATERIALS AND METHODS Nine centres received identical diffusion-weighted and anatomical magnetic resonance images of different cancerous tumours (adrenal gland, pelvic oligo metastasis, pancreas, and prostate). All centres delineated the gross tumour volume (GTV), clinical target volume (CTV), and viable tumour volume (VTV), and calculated ADCs using both their local calculation methods and each of the following calculation conditions: b-values 0-500 vs. 150-500 s/mm2, region-of-interest (ROI)-based vs. voxel-based calculation, and mean vs. median. ADC variation was assessed using the mean coefficient of variation across delineations (CVD) and calculation methods (CVC). Absolute ADC differences between calculation conditions were evaluated using Friedman's test. Recommendations for ADC calculation were formulated based on observations and discussions within the Elekta MRI-linac consortium image analysis working group. RESULTS The median (range) CVD and CVC were 0.06 (0.02-0.32) and 0.17 (0.08-0.26), respectively. The ADC estimates differed 18% between b-value sets and 4% between ROI/voxel-based calculation (p-values < 0.01). No significant difference was observed between mean and median (p = 0.64). Aligning calculation conditions between centres reduced CVC to 0.04 (0.01-0.16). CVD was comparable between ROI types. CONCLUSION Overall, calculation methods had a larger impact on ADC reproducibility compared to delineation. Based on the results, significant sources of variation were identified, which should be considered when initiating new studies, in particular multi-centre investigations.
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Affiliation(s)
- Anne L H Bisgaard
- Laboratory of Radiation Physics, Department of Oncology, Odense University Hospital, Kløvervænget 19, 5000 Odense, Denmark; Department of Clinical Research, University of Southern Denmark, J.B. Winsløws Vej 19.3, 5000 Odense Denmark.
| | - Rick Keesman
- Department of Radiation Oncology, Radboud University Medical Centre, P.O. Box 9101, 6500 HB Nijmegen, The Netherlands.
| | - Astrid L H M W van Lier
- Department of Radiotherapy, University Medical Centre Utrecht, Heidelberglaan 100, 3584 CX,Utrecht, The Netherlands.
| | - Catherine Coolens
- Department of Medical Physics, Princess Margaret Cancer Centre, University Health Network, 610 University Avenue, M5G 2M9 Toronto, ON, Canada.
| | - Petra J van Houdt
- Department of Radiation Oncology, the Netherlands Cancer Institute, Postbus 90203, 1006 BE Amsterdam, The Netherlands.
| | - Alison Tree
- Department of Urology, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, Downs Road, Sutton, Surrey, SM2 5PT London, UK.
| | - Andreas Wetscherek
- Joint Department of Physics, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, SM2 5NG London, UK.
| | - Paul B Romesser
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, Box 22, NY 10065, New York, USA.
| | - Neelam Tyagi
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, 545 E. 73rd street, NY 10021, New York, USA.
| | - Monica Lo Russo
- Department of Radiation Oncology, University Hospital and Medical Faculty, Eberhard Karls University, Hoppe-Seyler-Str. 3, 72076 Tübingen, Germany.
| | - Jonas Habrich
- Section for Biomedical Physics, Department of Radiation Oncology, University of Tübingen, Hoppe-Seyler-Str. 3, 72076 Tübingen, Germany.
| | - Danny Vesprini
- Department of Radiation Oncology, Sunnybrook Odette Cancer Centre, University of Toronto, 2075 Bayview Avenue, M4N 3M5 Toronto, ON, Canada.
| | - Angus Z Lau
- Physical Sciences Platform, Sunnybrook Research Institute. Department of Medical Biophysics, University of Toronto, 2075 Bayview Avenue, M4N 3M5 Toronto, ON, Canada.
| | - Stella Mook
- Department of Radiotherapy, University Medical Centre Utrecht, Heidelberglaan 100, 3584 CX,Utrecht, The Netherlands.
| | - Peter Chung
- Radiation Medicine Program, Princess Margaret Cancer Centre, University Health Network. Department of Radiation Oncology, University of Toronto, 610 University Avenue, M5G 2M9 Toronto, ON, Canada.
| | - Linda G W Kerkmeijer
- Department of Radiation Oncology, Radboud University Medical Centre, P.O. Box 9101, 6500 HB Nijmegen, The Netherlands.
| | - Zeno A R Gouw
- Department of Radiation Oncology, the Netherlands Cancer Institute, Postbus 90203, 1006 BE Amsterdam, The Netherlands.
| | - Ebbe L Lorenzen
- Laboratory of Radiation Physics, Department of Oncology, Odense University Hospital, Kløvervænget 19, 5000 Odense, Denmark.
| | - Uulke A van der Heide
- Department of Radiation Oncology, the Netherlands Cancer Institute, Postbus 90203, 1006 BE Amsterdam, The Netherlands.
| | - Tine Schytte
- Department of Clinical Research, University of Southern Denmark, J.B. Winsløws Vej 19.3, 5000 Odense Denmark; Department of Oncology, Odense University Hospital, Kløvervænget 19, 5000 Odense, Denmark.
| | - Carsten Brink
- Laboratory of Radiation Physics, Department of Oncology, Odense University Hospital, Kløvervænget 19, 5000 Odense, Denmark; Department of Clinical Research, University of Southern Denmark, J.B. Winsløws Vej 19.3, 5000 Odense Denmark.
| | - Faisal Mahmood
- Laboratory of Radiation Physics, Department of Oncology, Odense University Hospital, Kløvervænget 19, 5000 Odense, Denmark; Department of Clinical Research, University of Southern Denmark, J.B. Winsløws Vej 19.3, 5000 Odense Denmark.
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Kamimura K, Kamimura Y, Nakano T, Hasegawa T, Nakajo M, Yamada C, Akune K, Ejima F, Ayukawa T, Ito S, Nagano H, Takumi K, Nakajo M, Uchida H, Tabata K, Iwanaga T, Imai H, Feiweier T, Yoshiura T. Differentiating brain metastasis from glioblastoma by time-dependent diffusion MRI. Cancer Imaging 2023; 23:75. [PMID: 37553578 PMCID: PMC10410879 DOI: 10.1186/s40644-023-00595-2] [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: 05/14/2023] [Accepted: 07/24/2023] [Indexed: 08/10/2023] Open
Abstract
BACKGROUND This study was designed to investigate the use of time-dependent diffusion magnetic resonance imaging (MRI) parameters in distinguishing between glioblastomas and brain metastases. METHODS A retrospective study was conducted involving 65 patients with glioblastomas and 27 patients with metastases using a diffusion-weighted imaging sequence with oscillating gradient spin-echo (OGSE, 50 Hz) and a conventional pulsed gradient spin-echo (PGSE, 0 Hz) sequence. In addition to apparent diffusion coefficient (ADC) maps from two sequences (ADC50Hz and ADC0Hz), we generated maps of the ADC change (cADC): ADC50Hz - ADC0Hz and the relative ADC change (rcADC): (ADC50Hz - ADC0Hz)/ ADC0Hz × 100 (%). RESULTS The mean and the fifth and 95th percentile values of each parameter in enhancing and peritumoral regions were compared between glioblastomas and metastases. The area under the receiver operating characteristic curve (AUC) values of the best discriminating indices were compared. In enhancing regions, none of the indices of ADC0Hz and ADC50Hz showed significant differences between metastases and glioblastomas. The mean cADC and rcADC values of metastases were significantly higher than those of glioblastomas (0.24 ± 0.12 × 10-3mm2/s vs. 0.14 ± 0.03 × 10-3mm2/s and 23.3 ± 9.4% vs. 14.0 ± 4.7%; all p < 0.01). In peritumoral regions, no significant difference in all ADC indices was observed between metastases and glioblastomas. The AUC values for the mean cADC (0.877) and rcADC (0.819) values in enhancing regions were significantly higher than those for ADC0Hz5th (0.595; all p < 0.001). CONCLUSIONS The time-dependent diffusion MRI parameters may be useful for differentiating brain metastases from glioblastomas.
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Affiliation(s)
- Kiyohisa Kamimura
- Department of Advanced Radiological Imaging, Kagoshima University Graduate School of Medical and Dental Sciences, 8-35-1 Sakuragaoka, Kagoshima, 890-8544, Japan.
| | - Yoshiki Kamimura
- Department of Radiology, Kagoshima University Graduate School of Medical and Dental Sciences, 8-35-1 Sakuragaoka, Kagoshima, 890-8544, Japan
| | - Tsubasa Nakano
- Department of Radiology, Kagoshima University Graduate School of Medical and Dental Sciences, 8-35-1 Sakuragaoka, Kagoshima, 890-8544, Japan
| | - Tomohito Hasegawa
- Department of Radiology, Kagoshima University Graduate School of Medical and Dental Sciences, 8-35-1 Sakuragaoka, Kagoshima, 890-8544, Japan
| | - Masanori Nakajo
- Department of Radiology, Kagoshima University Graduate School of Medical and Dental Sciences, 8-35-1 Sakuragaoka, Kagoshima, 890-8544, Japan
| | - Chihiro Yamada
- Department of Radiology, Kagoshima University Graduate School of Medical and Dental Sciences, 8-35-1 Sakuragaoka, Kagoshima, 890-8544, Japan
| | - Kentaro Akune
- Department of Radiology, Kagoshima University Graduate School of Medical and Dental Sciences, 8-35-1 Sakuragaoka, Kagoshima, 890-8544, Japan
| | - Fumitaka Ejima
- Department of Radiology, Kagoshima University Graduate School of Medical and Dental Sciences, 8-35-1 Sakuragaoka, Kagoshima, 890-8544, Japan
| | - Takuro Ayukawa
- Department of Radiology, Kagoshima University Graduate School of Medical and Dental Sciences, 8-35-1 Sakuragaoka, Kagoshima, 890-8544, Japan
| | - Soichiro Ito
- Department of Radiology, Kagoshima University Graduate School of Medical and Dental Sciences, 8-35-1 Sakuragaoka, Kagoshima, 890-8544, Japan
| | - Hiroaki Nagano
- Department of Radiology, Kagoshima University Graduate School of Medical and Dental Sciences, 8-35-1 Sakuragaoka, Kagoshima, 890-8544, Japan
| | - Koji Takumi
- Department of Radiology, Kagoshima University Graduate School of Medical and Dental Sciences, 8-35-1 Sakuragaoka, Kagoshima, 890-8544, Japan
| | - Masatoyo Nakajo
- Department of Radiology, Kagoshima University Graduate School of Medical and Dental Sciences, 8-35-1 Sakuragaoka, Kagoshima, 890-8544, Japan
| | - Hiroyuki Uchida
- Department of Neurosurgery, Kagoshima University Graduate School of Medical and Dental Sciences, 8-35-1 Sakuragaoka, Kagoshima, 890-8544, Japan
| | - Kazuhiro Tabata
- Department of Pathology, Kagoshima University Graduate School of Medical and Dental Sciences, 8-35-1 Sakuragaoka, Kagoshima, 890-8544, Japan
| | - Takashi Iwanaga
- Department of Radiological Technology, Kagoshima University Hospital, 8-35-1 Sakuragaoka, Kagoshima, 890-8544, Japan
| | - Hiroshi Imai
- Siemens Healthcare K.K., Gate City Osaki West Tower, 1-11-1 Osaki, Shinagawa-Ku, Tokyo, 141-8644, Japan
| | | | - Takashi Yoshiura
- Department of Advanced Radiological Imaging, Kagoshima University Graduate School of Medical and Dental Sciences, 8-35-1 Sakuragaoka, Kagoshima, 890-8544, Japan
- Department of Radiology, Kagoshima University Graduate School of Medical and Dental Sciences, 8-35-1 Sakuragaoka, Kagoshima, 890-8544, Japan
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Vallée R, Vallée JN, Guillevin C, Lallouette A, Thomas C, Rittano G, Wager M, Guillevin R, Vallée A. Machine learning decision tree models for multiclass classification of common malignant brain tumors using perfusion and spectroscopy MRI data. Front Oncol 2023; 13:1089998. [PMID: 37614505 PMCID: PMC10442801 DOI: 10.3389/fonc.2023.1089998] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Accepted: 07/17/2023] [Indexed: 08/25/2023] Open
Abstract
Background To investigate the contribution of machine learning decision tree models applied to perfusion and spectroscopy MRI for multiclass classification of lymphomas, glioblastomas, and metastases, and then to bring out the underlying key pathophysiological processes involved in the hierarchization of the decision-making algorithms of the models. Methods From 2013 to 2020, 180 consecutive patients with histopathologically proved lymphomas (n = 77), glioblastomas (n = 45), and metastases (n = 58) were included in machine learning analysis after undergoing MRI. The perfusion parameters (rCBVmax, PSRmax) and spectroscopic concentration ratios (lac/Cr, Cho/NAA, Cho/Cr, and lip/Cr) were applied to construct Classification and Regression Tree (CART) models for multiclass classification of these brain tumors. A 5-fold random cross validation was performed on the dataset. Results The decision tree model thus constructed successfully classified all 3 tumor types with a performance (AUC) of 0.98 for PCNSLs, 0.98 for GBM and 1.00 for METs. The model accuracy was 0.96 with a RSquare of 0.887. Five rules of classifier combinations were extracted with a predicted probability from 0.907 to 0.989 for that end nodes of the decision tree for tumor multiclass classification. In hierarchical order of importance, the root node (Cho/NAA) in the decision tree algorithm was primarily based on the proliferative, infiltrative, and neuronal destructive characteristics of the tumor, the internal node (PSRmax), on tumor tissue capillary permeability characteristics, and the end node (Lac/Cr or Cho/Cr), on tumor energy glycolytic (Warburg effect), or on membrane lipid tumor metabolism. Conclusion Our study shows potential implementation of machine learning decision tree model algorithms based on a hierarchical, convenient, and personalized use of perfusion and spectroscopy MRI data for multiclass classification of these brain tumors.
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Affiliation(s)
- Rodolphe Vallée
- Interdisciplinary Laboratory in Neurosciences, Physiology and Psychology (LINP2), Université Paris Lumière (UPL), Paris Nanterre University, Nanterre, France
- Laboratory of Mathematics and Applications (LMA) Centre National de la Recherche Scientifique - Unité Mixte de Recherche (CNRS UMR)7348, i3M-DACTIM-MIH (Data Analysis and Computations Through Imaging Modeling - Mathematics, Image, Health), Poitiers University, Poitiers, France
- Glaucoma Research Center, Swiss Visio Network, Lausanne, Switzerland
| | - Jean-Noël Vallée
- Laboratory of Mathematics and Applications (LMA) Centre National de la Recherche Scientifique - Unité Mixte de Recherche (CNRS UMR)7348, i3M-DACTIM-MIH (Data Analysis and Computations Through Imaging Modeling - Mathematics, Image, Health), Poitiers University, Poitiers, France
- Diagnostic and Functional Neuroradiology and Brain stimulation Department, 15-20 National Vision Hospital of Paris - Paris University Hospital Center, University of PARIS-SACLAY - UVSQ, Paris, France
| | - Carole Guillevin
- Laboratory of Mathematics and Applications (LMA) Centre National de la Recherche Scientifique - Unité Mixte de Recherche (CNRS UMR)7348, i3M-DACTIM-MIH (Data Analysis and Computations Through Imaging Modeling - Mathematics, Image, Health), Poitiers University, Poitiers, France
- Radiology Department, Poitiers University Hospital, Poitiers University, Poitiers, France
| | | | - Clément Thomas
- Laboratory of Mathematics and Applications (LMA) Centre National de la Recherche Scientifique - Unité Mixte de Recherche (CNRS UMR)7348, i3M-DACTIM-MIH (Data Analysis and Computations Through Imaging Modeling - Mathematics, Image, Health), Poitiers University, Poitiers, France
- Diagnostic and Functional Neuroradiology and Brain stimulation Department, 15-20 National Vision Hospital of Paris - Paris University Hospital Center, University of PARIS-SACLAY - UVSQ, Paris, France
| | | | - Michel Wager
- Neurosurgery Department, Poitiers University Hospital, Poitiers University, Poitiers, France
| | - Rémy Guillevin
- Laboratory of Mathematics and Applications (LMA) Centre National de la Recherche Scientifique - Unité Mixte de Recherche (CNRS UMR)7348, i3M-DACTIM-MIH (Data Analysis and Computations Through Imaging Modeling - Mathematics, Image, Health), Poitiers University, Poitiers, France
- Radiology Department, Poitiers University Hospital, Poitiers University, Poitiers, France
| | - Alexandre Vallée
- Department of Epidemiology and Public Health, Foch Hospital, Suresnes, France
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Mui AW, Lee AW, Ng WT, Lee VH, Vardhanabhuti V, Man SY, Chua DT, Guan XY. Optimal time for early therapeutic response prediction in nasopharyngeal carcinoma with functional magnetic resonance imaging. Phys Imaging Radiat Oncol 2023; 27:100458. [PMID: 37457666 PMCID: PMC10339040 DOI: 10.1016/j.phro.2023.100458] [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: 02/16/2023] [Revised: 05/26/2023] [Accepted: 06/12/2023] [Indexed: 07/18/2023] Open
Abstract
Background and Purpose Physiological changes in tumour occur much earlier than morphological changes. They can potentially be used as biomarkers for therapeutic response prediction. This study aimed to investigate the optimal time for early therapeutic response prediction with multi-parametric magnetic resonance imaging (MRI) in patients with nasopharyngeal carcinoma (NPC) receiving concurrent chemo-radiotherapy (CCRT). Material and Methods Twenty-seven NPC patients were divided into the responder (N = 23) and the poor-responder (N = 4) groups by their primary tumour post-treatment shrinkages. Single-voxel proton MR spectroscopy (1H-MRS), diffusion-weighted (DW) and dynamic contrast-enhanced (DCE) MRI were scanned at baseline, weekly during CCRT and post-CCRT. The median choline peak in 1H-MRS, the median apparent diffusion coefficient (ADC) in DW-MRI, the median influx rate constant (Ktrans), reflux rate constant (Kep), volume of extravascular-extracellular space per unit volume (Ve), and initial area under the time-intensity curve for the first 60 s (iAUC60) in DCE-MRI were compared between the two groups with the Mann-Whitney tests for any significant difference at different time points. Results In DW-MRI, the percentage increase in ADC from baseline to week-1 for the responders (median = 11.39%, IQR = 18.13%) was higher than the poor-responders (median = 4.91%, IQR = 7.86%) (p = 0.027). In DCE-MRI, the iAUC60 on week-2 was found significantly higher in the poor-responders (median = 0.398, IQR = 0.051) than the responders (median = 0.192, IQR = 0.111) (p = 0.012). No significant difference was found in median choline peaks in 1H-MRS at all time points. Conclusion Early perfusion and diffusion changes occurred in primary tumours of NPC patients treated with CCRT. The DW-MRI on week-1 and the DCE-MRI on week-2 were the optimal time points for early therapeutic response prediction.
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Affiliation(s)
- Alan W.L. Mui
- Department of Radiotherapy, Hong Kong Sanatorium and Hospital, Hong Kong, China
- Department of Clinical Oncology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Anne W.M. Lee
- Department of Clinical Oncology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Wai-Tong Ng
- Department of Clinical Oncology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Victor H.F. Lee
- Department of Clinical Oncology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Varut Vardhanabhuti
- Department of Diagnostic Radiology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Shei-Yee Man
- Department of Radiotherapy, Hong Kong Sanatorium and Hospital, Hong Kong, China
| | - Daniel T.T. Chua
- Department of Medicine, Hong Kong Sanatorium and Hospital, Hong Kong, China
| | - Xin-Yuan Guan
- Department of Clinical Oncology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
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Brabec J, Englund E, Bengzon J, Szczepankiewicz F, van Westen D, Sundgren PC, Nilsson M. Coregistered histology sections with diffusion tensor imaging data at 200 µm resolution in meningioma tumors. Data Brief 2023; 48:109261. [PMID: 37383742 PMCID: PMC10294079 DOI: 10.1016/j.dib.2023.109261] [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: 03/06/2023] [Revised: 05/08/2023] [Accepted: 05/17/2023] [Indexed: 06/30/2023] Open
Abstract
A significant problem in diffusion MRI (dMRI) is the lack of understanding regarding which microstructural features account for the variability in the diffusion tensor imaging (DTI) parameters observed in meningioma tumors. A common assumption is that mean diffusivity (MD) and fractional anisotropy (FA) from DTI are inversely proportional to cell density and proportional to tissue anisotropy, respectively. Although these associations have been established across a wide range of tumors, they have been challenged for interpreting within-tumor variations where several additional microstructural features have been suggested as contributing to MD and FA. To facilitate the investigation of the biological underpinnings of DTI parameters, we performed ex-vivo DTI at 200 µm isotropic resolution on sixteen excised meningioma tumor samples. The samples exhibit a variety of microstructural features because the dataset includes meningiomas of six different meningioma types and two different grades. Diffusion-weighted signal (DWI) maps, DWI maps averaged over all directions for given b-value, signal intensities without diffusion encoding (S0) as well as DTI parameters: MD, FA, in-plane FA (FAIP), axial diffusivity (AD) and radial diffusivity (RD), were coregistered to Hematoxylin & Eosin- (H&E) and Elastica van Gieson-stained (EVG) histological sections by a non-linear landmark-based approach. Here, we provide DWI signal and DTI maps coregistered to histology sections and describe the pipeline for processing the raw DTI data and the coregistration. The raw, processed, and coregistered data are hosted by Analytic Imaging Diagnostics Arena (AIDA) data hub registry, and software tools for processing are provided via GitHub. We hope that data can be used in research and education concerning the link between the meningioma microstructure and parameters obtained by DTI.
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Affiliation(s)
- Jan Brabec
- Medical Radiation Physics, Clinical Sciences Lund, Lund University, Lund, Sweden
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | | | - Johan Bengzon
- Division of Neurosurgery, Skane University Hospital, Lund, Sweden
- Stem Cell Center, Department of Clinical Sciences, Lund, Sweden
| | | | | | - Pia C. Sundgren
- Diagnostic Radiology, Clinical Sciences Lund, Lund University, Lund, Sweden
- Lund University Bioimaging Centre, Lund University, Lund, Sweden
- Department of Medical Imaging and Physiology, Skåne University Hospital, Lund University, Lund, Sweden
| | - Markus Nilsson
- Medical Radiation Physics, Clinical Sciences Lund, Lund University, Lund, Sweden
- Diagnostic Radiology, Clinical Sciences Lund, Lund University, Lund, Sweden
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Baratto L, Nyalakonda R, Theruvath AJ, Sarrami AH, Hawk KE, Rashidi A, Shen S, States L, Aboian M, Jeng M, Daldrup-Link HE. Comparison of whole-body DW-MRI with 2-[ 18F]FDG PET for staging and treatment monitoring of children with Langerhans cell histiocytosis. Eur J Nucl Med Mol Imaging 2023; 50:1689-1698. [PMID: 36717409 PMCID: PMC10121877 DOI: 10.1007/s00259-023-06122-6] [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: 10/11/2022] [Accepted: 01/22/2023] [Indexed: 02/01/2023]
Abstract
PURPOSE To assess and compare the diagnostic accuracy of whole-body (WB) DW-MRI with 2-[18F]FDG PET for staging and treatment monitoring of children with Langerhans cell histiocytosis (LCH). METHODS Twenty-three children with LCH underwent 2-[18F]FDG PET and WB DW-MRI at baseline. Two nuclear medicine physicians and two radiologists independently assessed presence/absence of tumors in 8 anatomical areas. Sixteen children also performed 2-[18F]FDG PET and WB DW-MRI at follow-up. One radiologist and one nuclear medicine physician revised follow-up scans and collected changes in tumor apparent diffusion (ADC) and standardized uptake values (SUV) before and after therapy in all detectable lesions. 2-[18F]FDG PET results were considered the standard of reference for tumor detection and evaluation of treatment response according to Lugano criteria. Sensitivity, specificity, positive and negative predictive values, and diagnostic accuracy of WB DW-MRI at baseline were calculated, and the 95% confidence intervals were estimated by using the Clopper-Pearson (exact) method; changes in tumor SUVs and ADC were compared using a Mann-Whitney U test. Agreement between reviewers was assessed with a Cohen's weighted kappa coefficient. Analyses were conducted using SAS software version 9.4. RESULTS Agreement between reviewers was perfect (kappa coefficient = 1) for all analyzed regions but spine and neck (kappa coefficient = 0.89 and 0.83, respectively) for 2-[18F]FDG PET images, and abdomen and pelvis (kappa coefficient = 0.65 and 0.88, respectively) for WB DW-MRI. Sensitivity and specificity were 95.5% and 100% for WB DW-MRI compared to 2-[18F]FDG PET. Pre to post-treatment changes in SUVratio and ADCmean were inversely correlated for all lesions (r: -0.27, p = 0·06) and significantly different between responders and non-responders to chemotherapy (p = 0.0006 and p = 0·003 for SUVratio and ADCmean, respectively). CONCLUSION Our study showed that WB DW-MRI has similar accuracy to 2-[18F]FDG PET for staging and treatment monitoring of LCH in children. While 2-[18F]FDG PET remains an approved radiological examination for assessing metabolically active disease, WB DW-MRI could be considered as an alternative approach without radiation exposure. The combination of both modalities might have advantages over either approach alone.
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Affiliation(s)
- Lucia Baratto
- Department of Radiology, Division of Pediatric Radiology, Lucile Packard Children's Hospital, Stanford University, CA. 1201 Welch Rd, Stanford, CA, 94305, USA.
| | - Ramyashree Nyalakonda
- University of North Texas Health Science Center, Texas College of Osteopathic Medicine, TX, 3500 Camp Bowie Boulevard, Fort Worth, TX, 76107-2699, USA
| | - Ashok J Theruvath
- Edward B. Singleton, Department of Radiology, Texas Children's Hospital, 6701 Fannin Street, Suite 470, Houston, TX, 77030, USA
- Department of Radiology, Baylor College of Medicine, Houston, TX, USA
| | - Amir Hossein Sarrami
- Department of Radiology, Division of Pediatric Radiology, Lucile Packard Children's Hospital, Stanford University, CA. 1201 Welch Rd, Stanford, CA, 94305, USA
| | - Kristina Elizabeth Hawk
- Department of Radiology, Division of Pediatric Radiology, Lucile Packard Children's Hospital, Stanford University, CA. 1201 Welch Rd, Stanford, CA, 94305, USA
| | - Ali Rashidi
- Department of Radiology, Division of Pediatric Radiology, Lucile Packard Children's Hospital, Stanford University, CA. 1201 Welch Rd, Stanford, CA, 94305, USA
| | - Sa Shen
- Quantitative Sciences Unit, Department of Medicine, Stanford University, CA. 1070 Arastradero Road, Palo Alto, CA, 94305, USA
| | - Lisa States
- Department of Radiology, Division of Body Imaging, The Children's Hospital of Philadelphia, University of Pennsylvania, PA. 401 Civic Center Blvd, Philadelphia, PA, 19104, USA
| | - Mariam Aboian
- Department of Radiology, Division of Neuroradiology and Nuclear Medicine, Yale School of Medicine, CT. 333 Cedar St, New Haven, CT, 06510, USA
| | - Michael Jeng
- Department of Pediatrics, Pediatric Hematology/Oncology, Lucile Packard Children's Hospital, Stanford University, CA. 725 Welch Road, Stanford, CA, 94305, USA
| | - Heike E Daldrup-Link
- Department of Radiology, Division of Pediatric Radiology, Lucile Packard Children's Hospital, Stanford University, CA. 1201 Welch Rd, Stanford, CA, 94305, USA
- Department of Pediatrics, Pediatric Hematology/Oncology, Lucile Packard Children's Hospital, Stanford University, CA. 725 Welch Road, Stanford, CA, 94305, USA
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Yuan L, Lin X, Zhao P, Ma H, Duan S, Sun S. Correlations between DKI and DWI with Ki-67 in gastric adenocarcinoma. Acta Radiol 2023; 64:1792-1798. [PMID: 36740857 DOI: 10.1177/02841851231153035] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
BACKGROUND Diffusion kurtosis imaging (DKI) has been applied for gastric adenocarcinoma. Correlations between its parameters and Ki-67 are unclear. PURPOSE To investigate the correlation between DKI and diffusion-weighted imaging (DWI) parameters with the Ki-67 index in gastric adenocarcinoma. MATERIAL AND METHODS A total of 54 patients with gastric adenocarcinoma were enrolled in the study and underwent DWI and DKI at 3.0-T MRI before surgery. Based on the settings of the regions of interest, the DWI and DKI parameters (including apparent diffusion coefficient [ADC], diffusion kurtosis [K], and diffusion coefficient [DK]) of each patient's gastric adenocarcinoma were measured and calculated. The participants were divided into two groups (low Ki-67 group and high Ki-67 groups). The intraclass correlation coefficient (ICC) and independent-sample t-test were used to compare differences in each parameter between two groups. Spearman's correlation coefficient was calculated to determine the correlation between Ki-67 and the parameters. Each parameter was compared using the area under the receiver operating characteristic curve. All parameters were included in the multivariate logistic regression analysis to explore the relationship between each parameter and high Ki-67 index. RESULTS ADC and DK were negatively relevant with Ki-67 and K was positively relevant with Ki-67 in gastric adenocarcinoma. ADC, DK, and K had diagnostic efficiency in differentiating the low Ki-67 group from the high Ki-67 group. A higher K value independently predicted a high Ki-67 status. CONCLUSION DWI and DKI reflected the proliferative characteristics of gastric adenocarcinoma. K was the strongest independent factor for predicting high Ki-67 status.
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Affiliation(s)
- Letian Yuan
- Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, PR China
| | - Xiangtao Lin
- Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, PR China
| | - Peng Zhao
- Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, PR China
| | - Hui Ma
- Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, PR China
| | - Shuai Duan
- Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, PR China
| | - Shanshan Sun
- Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, PR China
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Mehta R, Bu Y, Zhong Z, Dan G, Zhong PS, Zhou C, Hu W, Zhou XJ, Xu M, Wang S, Karaman MM. Characterization of breast lesions using multi-parametric diffusion MRI and machine learning. Phys Med Biol 2023; 68:085006. [PMID: 36808921 DOI: 10.1088/1361-6560/acbde0] [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: 10/13/2022] [Accepted: 02/21/2023] [Indexed: 02/23/2023]
Abstract
Objective. To investigate quantitative imaging markers based on parameters from two diffusion-weighted imaging (DWI) models, continuous-time random-walk (CTRW) and intravoxel incoherent motion (IVIM) models, for characterizing malignant and benign breast lesions by using a machine learning algorithm.Approach. With IRB approval, 40 women with histologically confirmed breast lesions (16 benign, 24 malignant) underwent DWI with 11b-values (50 to 3000 s/mm2) at 3T. Three CTRW parameters,Dm,α, andβand three IVIM parametersDdiff,Dperf, andfwere estimated from the lesions. A histogram was generated and histogram features of skewness, variance, mean, median, interquartile range; and the value of the 10%, 25% and 75% quantiles were extracted for each parameter from the regions-of-interest. Iterative feature selection was performed using the Boruta algorithm that uses the Benjamin Hochberg False Discover Rate to first determine significant features and then to apply the Bonferroni correction to further control for false positives across multiple comparisons during the iterative procedure. Predictive performance of the significant features was evaluated using Support Vector Machine, Random Forest, Naïve Bayes, Gradient Boosted Classifier (GB), Decision Trees, AdaBoost and Gaussian Process machine learning classifiers.Main Results. The 75% quantile, and median ofDm; 75% quantile off;mean, median, and skewness ofβ;kurtosis ofDperf; and 75% quantile ofDdiffwere the most significant features. The GB differentiated malignant and benign lesions with an accuracy of 0.833, an area-under-the-curve of 0.942, and an F1 score of 0.87 providing the best statistical performance (p-value < 0.05) compared to the other classifiers.Significance. Our study has demonstrated that GB with a set of histogram features from the CTRW and IVIM model parameters can effectively differentiate malignant and benign breast lesions.
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Affiliation(s)
- Rahul Mehta
- Center for Magnetic Resonance Research, University of Illinois at Chicago, Chicago, IL, United States of America
- Department of Biomedical Engineering, University of Illinois at Chicago, Chicago, IL, United States of America
| | - Yangyang Bu
- The First School of Clinical Medicine of Zhejiang Chinese Medical University, Hangzhou, People's Republic of China
- Department of Radiology, The First Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, People's Republic of China
| | - Zheng Zhong
- Center for Magnetic Resonance Research, University of Illinois at Chicago, Chicago, IL, United States of America
- Department of Biomedical Engineering, University of Illinois at Chicago, Chicago, IL, United States of America
| | - Guangyu Dan
- Center for Magnetic Resonance Research, University of Illinois at Chicago, Chicago, IL, United States of America
- Department of Biomedical Engineering, University of Illinois at Chicago, Chicago, IL, United States of America
| | - Ping-Shou Zhong
- Department of Mathematics, Statistics, and Computer Science, University of Illinois at Chicago, Chicago, IL, United States of America
| | - Changyu Zhou
- The First School of Clinical Medicine of Zhejiang Chinese Medical University, Hangzhou, People's Republic of China
- Department of Radiology, The First Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, People's Republic of China
| | - Weihong Hu
- The First School of Clinical Medicine of Zhejiang Chinese Medical University, Hangzhou, People's Republic of China
- Department of Radiology, The First Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, People's Republic of China
| | - Xiaohong Joe Zhou
- Departments of Radiology and Neurosurgery, University of Illinois at Chicago, Chicago, IL, United States of America
| | - Maosheng Xu
- The First School of Clinical Medicine of Zhejiang Chinese Medical University, Hangzhou, People's Republic of China
- Department of Radiology, The First Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, People's Republic of China
| | - Shiwei Wang
- The First School of Clinical Medicine of Zhejiang Chinese Medical University, Hangzhou, People's Republic of China
- Department of Radiology, The First Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, People's Republic of China
| | - M Muge Karaman
- Center for Magnetic Resonance Research, University of Illinois at Chicago, Chicago, IL, United States of America
- Department of Biomedical Engineering, University of Illinois at Chicago, Chicago, IL, United States of America
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Abele N, Langner S, Felbor U, Lode H, Hosten N. Quantitative Diffusion-Weighted MRI of Neuroblastoma. Cancers (Basel) 2023; 15:cancers15071940. [PMID: 37046600 PMCID: PMC10092990 DOI: 10.3390/cancers15071940] [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: 01/26/2023] [Revised: 03/06/2023] [Accepted: 03/08/2023] [Indexed: 04/14/2023] Open
Abstract
Neuroblastoma is the most common extracranial, malignant, solid tumor found in children. In more than one-third of cases, the tumor is in an advanced stage, with limited resectability. The treatment options include resection, with or without (neo-/) adjuvant therapy, and conservative therapy, the latter even with curative intent. Contrast-enhanced MRI is used for staging and therapy monitoring. Diffusion-weighted imaging (DWI) is often included. DWI allows for a calculation of the apparent diffusion coefficient (ADC) for quantitative assessment. Histological tumor characteristics can be derived from ADC maps. Monitoring the response to treatment is possible using ADC maps, with an increase in ADC values in cases of a response to therapy. Changes in the ADC value precede volume reduction. The usual criteria for determining the response to therapy can therefore be supplemented by ADC values. While these changes have been observed in neuroblastoma, early changes in the ADC value in response to therapy are less well described. In this study, we evaluated whether there is an early change in the ADC values in neuroblastoma under therapy; if this change depends on the form of therapy; and whether this change may serve as a prognostic marker. We retrospectively evaluated neuroblastoma cases treated in our institution between June 2007 and August 2014. The examinations were grouped as 'prestaging'; 'intermediate staging'; 'final staging'; and 'follow-up'. A classification of "progress", "stable disease", or "regress" was made. For the determination of ADC values, regions of interest were drawn along the borders of all tumor manifestations. To calculate ADC changes (∆ADC), the respective MRI of the prestaging was used as a reference point or, in the case of therapies that took place directly after previous therapies, the associated previous staging. In the follow-up examinations, the previous examination was used as a reference point. The ∆ADC were grouped into ∆ADCregress for regressive disease, ∆ADCstable for stable disease, and ∆ADC for progressive disease. In addition, examinations at 60 to 120 days from the baseline were grouped as er∆ADCregress, er∆ADCstable, and er∆ADCprogress. Any differences were tested for significance using the Mann-Whitney test (level of significance: p < 0.05). In total, 34 patients with 40 evaluable tumor manifestations and 121 diffusion-weighted MRI examinations were finally included. Twenty-seven patients had INSS stage IV neuroblastoma, and seven had INSS stage III neuroblastoma. A positive N-Myc expression was found in 11 tumor diseases, and 17 patients tested negative for N-Myc (with six cases having no information). 26 patients were assigned to the high-risk group according to INRG and eight patients to the intermediate-risk group. There was a significant difference in mean ADC values from the high-risk group compared to those from the intermediate-risk group, according to INRG. The differences between the mean ∆ADC values (absolute and percentage) according to the course of the disease were significant: between ∆ADCregress and ∆ADCstable, between ∆ADCprogress and ∆ADCstable, as well as between ∆ADCregress and ∆ADCprogress. The differences between the mean er∆ADC values (absolute and percentage) according to the course of the disease were significant: between er∆ADCregress and er∆ADCstable, as well as between er∆ADCregress and er∆ADCprogress. Forms of therapy, N-Myc status, and risk groups showed no further significant differences in mean ADC values and ∆ADC/er∆ADC. A clear connection between the ADC changes and the response to therapy could be demonstrated. This held true even within the first 120 days after the start of therapy: an increase in the ADC value corresponds to a probable response to therapy, while a decrease predicts progression. Minimal or no changes were seen in cases of stable disease.
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Affiliation(s)
- Niklas Abele
- Department of Radiology, Germany University of Greifswald, 17475 Greifswald, Germany
- Institute of Pathology, University of Erlangen, 91054 Erlangen, Germany
| | - Soenke Langner
- Department of Radiology, Germany University of Greifswald, 17475 Greifswald, Germany
- Department of Radiology, University of Rostock, 18057 Rostock, Germany
| | - Ute Felbor
- Department of Human Genetics, University of Greifswald, 17475 Greifswald, Germany
- Interfaculty Institute of Genetics and Functional Genetics, University of Greifswald, 17475 Greifswald, Germany
| | - Holger Lode
- Department of Pediatric Hematology and Oncology, University of Greifswald, 17475 Greifswald, Germany
| | - Norbert Hosten
- Department of Radiology, Germany University of Greifswald, 17475 Greifswald, Germany
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Wongsa P, Nantasuk M, Singhnoi S, Pawano P, Jantarato A, Siripongsatian D, Lerdsirisuk P, Phonlakrai M. Assessing the variability and correlation between SUV and ADC parameters of head and neck cancers derived from simultaneous PET/MRI: A single-center study. J Appl Clin Med Phys 2023; 24:e13928. [PMID: 36763489 PMCID: PMC10161023 DOI: 10.1002/acm2.13928] [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: 08/06/2022] [Revised: 01/21/2023] [Accepted: 01/26/2023] [Indexed: 02/11/2023] Open
Abstract
OBJECTIVE Intratumoral heterogeneity is associated with poor outcomes in head and neck cancer (HNC) patients owing to chemoradiotherapy resistance. [18 F]-FDG positron emission tomography (PET) / Magnetic Resonance Imaging (MRI) provides spatial information about tumor mass, allowing intratumor heterogeneity assessment through histogram analysis. However, variability in quantitative PET/MRI parameter measurements could influence their reliability in assessing patient prognosis. Therefore, to use standardized uptake value (SUV) and apparent diffusion coefficient (ADC) parameters for assessing tumor response, this study aimed to measure SUV and ADC's variability and assess their relationship in HNC. METHODS First, ADC variability was measured in an in-house diffusion phantom and in five healthy volunteers. The SUV variability was only measured with the NEMA phantom using a clinical imaging protocol. Furthermore, simultaneous PET/MRI data of 11 HNC patients were retrospectively collected from the National Cyclotron and PET center in Chulabhorn Hospital. Tumor contours were manually drawn from PET images by an experienced nuclear medicine radiologist before tumor volume segmentation. Next, SUV and ADC's histogram were used to extract statistic variables of ADC and SUV: mean, median, min, max, skewness, kurtosis, and 5th , 10th , 25th , 50th , 75th , 90th , and 95th percentiles. Finally, the correlation between the statistic variables of ADC and SUV, as well as Metabolic Tumor volume and Total Lesion Glycolysis parameters was assessed using Pearson's correlation. RESULTS This pilot study showed that both parameters' maximum coefficient of variation was 13.9% and 9.8% in the phantom and in vivo, respectively. Furthermore, we found a strong and negative correlation between SUVmax and ADVmed (r = -0.75, P = 0.01). CONCLUSION The SUV and ADC obtained by simultaneous PET/MRI can be potentially used as an imaging biomarker for assessing intratumoral heterogeneity in patients with HNC. The low variability and relationship between SUV and ADC could allow multimodal prediction of tumor response in future studies.
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Affiliation(s)
- Paramest Wongsa
- School of Radiological Technology, Faculty of Health Science Technology, HRH Princess Chulabhorn College of Medical Sciences, Chulabhorn Royal Academy, Bangkok, Thailand
| | - Mayurachat Nantasuk
- School of Radiological Technology, Faculty of Health Science Technology, HRH Princess Chulabhorn College of Medical Sciences, Chulabhorn Royal Academy, Bangkok, Thailand
| | - Sinirun Singhnoi
- School of Radiological Technology, Faculty of Health Science Technology, HRH Princess Chulabhorn College of Medical Sciences, Chulabhorn Royal Academy, Bangkok, Thailand
| | - Phattarasaya Pawano
- School of Radiological Technology, Faculty of Health Science Technology, HRH Princess Chulabhorn College of Medical Sciences, Chulabhorn Royal Academy, Bangkok, Thailand
| | - Attapon Jantarato
- National Cyclotron and PET Centre, Chulabhorn Hospital, Chulabhorn Royal Academy, Bangkok, Thailand
| | | | - Pradith Lerdsirisuk
- National Cyclotron and PET Centre, Chulabhorn Hospital, Chulabhorn Royal Academy, Bangkok, Thailand
| | - Monchai Phonlakrai
- School of Radiological Technology, Faculty of Health Science Technology, HRH Princess Chulabhorn College of Medical Sciences, Chulabhorn Royal Academy, Bangkok, Thailand
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Wakle DU, Choudhury S, Chakraborty S, Ganguly A, Pal DK. Evaluation of renal space occupying lesions with multiparametric MRI and its correlation with histopathology findings- an observational study. Urologia 2023; 90:42-50. [PMID: 36314948 DOI: 10.1177/03915603221131733] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/05/2023]
Abstract
The term multiparametric MRI, is a useful tool in reference to an approach that takes advantage of the added value of different MR imaging acquisitions to yield anatomic and pathophysiologic information about renal space occupying lesions and to evaluate patients with different tumors, including genitourinary malignancies. The role of multiparametric MRI is continuously growing because of its ability to detect and characterize renal space occupying lesions as well as to assess response to treatment. An observational study was carried out in 50 patients who presented with renal mass, based on clinical suspicion and prior imaging diagnosis of neoplastic renal space occupying lesion. Total renal space occupying lesions were 50, of which, 38 were males & 12 were females. The age range of the study population was 30-80 years. In our study, Agreement analysis between mpMRI diagnosis and HPE diagnosis of different RCC subtypes was statistically significant. So, multiparametric MRI had a role in differentiating the subtypes of RCC which had fair agreement with HPE. The present study results state that the renal mass lesions has different ADC values for different lesions because of the change in tissue contents and there was a statistically significant difference in ADC values between low and high-stage RCCs. Histologic and radiologic profiles of renal space occupying lesions and diverse subtypes of RCC can be used as biologic indicators of clinical behavior, response to treatment, and prognosis.
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Speckter H, Palque-Santos S, Mota-Gonzalez R, Bido J, Hernandez G, Rivera D, Suazo L, Valenzuela S, Gonzalez-Curi M, Stoeter P. Can Apparent Diffusion Coefficient (ADC) maps replace Diffusion Tensor Imaging (DTI) maps to predict the volumetric response of meningiomas to Gamma Knife Radiosurgery? J Neurooncol 2023; 161:547-554. [PMID: 36745271 DOI: 10.1007/s11060-023-04243-4] [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: 12/22/2022] [Accepted: 01/17/2023] [Indexed: 02/07/2023]
Abstract
PURPOSE Noninvasive methods are desired to predict the treatment response to Stereotactic Radiosurgery (SRS) to improve individual tumor management. In a previous study, we demonstrated that Diffusion Tensor Imaging (DTI)-derived parameter maps significantly correlate to SRS response. This study aimed to analyze and compare the predictive value of intratumoral ADC and DTI parameters in patients with meningiomas undergoing radiosurgery. METHODS MR images of 70 patients treated with Gamma Knife SRS for WHO grade I meningiomas were retrospectively reviewed. MR acquisition included pre- and post-treatment DWI and DTI sequences, and subtractions were calculated to assess for radiation-induced changes in the parameter values. RESULTS After a mean follow-up period (FUP) of 52.7 months, 69 of 70 meningiomas were controlled, with a mean volume reduction of 34.9%. Whereas fractional anisotropy (FA) values of the initial exam showed the highest correlation to tumor volume change at the last FU (CC = - 0.607), followed by the differences between first and second FU values of FA (CC = - 0.404) and the first longitudinal diffusivity (LD) value (CC = - 0.375), the correlation coefficients of all ADC values were comparably low. Nevertheless, all these correlations, except for ADC measured at the first follow-up, reached significance. CONCLUSION For the first time, the prognostic value of ADC maps measured in meningiomas before and at first follow-up after Gamma Knife SRS, was compared to simultaneously acquired DTI parameter maps. Quantities assessed from ADC maps present significant correlations to the volumetric meningioma response but are less effective than correlations with DTI parameters.
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Affiliation(s)
- Herwin Speckter
- Centro Gamma Knife Dominicano, CEDIMAT, Plaza de la Salud, Santo Domingo, Dominican Republic. .,Department of Radiology, CEDIMAT, Plaza de la Salud, Santo Domingo, Dominican Republic.
| | - Sarai Palque-Santos
- Centro Gamma Knife Dominicano, CEDIMAT, Plaza de la Salud, Santo Domingo, Dominican Republic
| | - Ruben Mota-Gonzalez
- Centro Gamma Knife Dominicano, CEDIMAT, Plaza de la Salud, Santo Domingo, Dominican Republic
| | - Jose Bido
- Centro Gamma Knife Dominicano, CEDIMAT, Plaza de la Salud, Santo Domingo, Dominican Republic
| | - Giancarlo Hernandez
- Centro Gamma Knife Dominicano, CEDIMAT, Plaza de la Salud, Santo Domingo, Dominican Republic
| | - Diones Rivera
- Centro Gamma Knife Dominicano, CEDIMAT, Plaza de la Salud, Santo Domingo, Dominican Republic
| | - Luis Suazo
- Centro Gamma Knife Dominicano, CEDIMAT, Plaza de la Salud, Santo Domingo, Dominican Republic
| | - Santiago Valenzuela
- Centro Gamma Knife Dominicano, CEDIMAT, Plaza de la Salud, Santo Domingo, Dominican Republic
| | - Maria Gonzalez-Curi
- Department of Radiology, CEDIMAT, Plaza de la Salud, Santo Domingo, Dominican Republic
| | - Peter Stoeter
- Centro Gamma Knife Dominicano, CEDIMAT, Plaza de la Salud, Santo Domingo, Dominican Republic.,Department of Radiology, CEDIMAT, Plaza de la Salud, Santo Domingo, Dominican Republic
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Ng J, Gregucci F, Pennell RT, Nagar H, Golden EB, Knisely JPS, Sanfilippo NJ, Formenti SC. MRI-LINAC: A transformative technology in radiation oncology. Front Oncol 2023; 13:1117874. [PMID: 36776309 PMCID: PMC9911688 DOI: 10.3389/fonc.2023.1117874] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2022] [Accepted: 01/16/2023] [Indexed: 01/28/2023] Open
Abstract
Advances in radiotherapy technologies have enabled more precise target guidance, improved treatment verification, and greater control and versatility in radiation delivery. Amongst the recent novel technologies, Magnetic Resonance Imaging (MRI) guided radiotherapy (MRgRT) may hold the greatest potential to improve the therapeutic gains of image-guided delivery of radiation dose. The ability of the MRI linear accelerator (LINAC) to image tumors and organs with on-table MRI, to manage organ motion and dose delivery in real-time, and to adapt the radiotherapy plan on the day of treatment while the patient is on the table are major advances relative to current conventional radiation treatments. These advanced techniques demand efficient coordination and communication between members of the treatment team. MRgRT could fundamentally transform the radiotherapy delivery process within radiation oncology centers through the reorganization of the patient and treatment team workflow process. However, the MRgRT technology currently is limited by accessibility due to the cost of capital investment and the time and personnel allocation needed for each fractional treatment and the unclear clinical benefit compared to conventional radiotherapy platforms. As the technology evolves and becomes more widely available, we present the case that MRgRT has the potential to become a widely utilized treatment platform and transform the radiation oncology treatment process just as earlier disruptive radiation therapy technologies have done.
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Affiliation(s)
- John Ng
- Department of Radiation Oncology, Weill Cornell Medicine, New York, NY, United States,*Correspondence: John Ng,
| | - Fabiana Gregucci
- Department of Radiation Oncology, Weill Cornell Medicine, New York, NY, United States,Department of Radiation Oncology, Miulli General Regional Hospital, Acquaviva delle Fonti, Bari, Italy
| | - Ryan T. Pennell
- Department of Radiation Oncology, Weill Cornell Medicine, New York, NY, United States
| | - Himanshu Nagar
- Department of Radiation Oncology, Weill Cornell Medicine, New York, NY, United States
| | - Encouse B. Golden
- Department of Radiation Oncology, Weill Cornell Medicine, New York, NY, United States
| | | | | | - Silvia C. Formenti
- Department of Radiation Oncology, Weill Cornell Medicine, New York, NY, United States
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Meaney C, Das S, Colak E, Kohandel M. Deep learning characterization of brain tumours with diffusion weighted imaging. J Theor Biol 2023; 557:111342. [PMID: 36368560 DOI: 10.1016/j.jtbi.2022.111342] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2022] [Revised: 10/19/2022] [Accepted: 10/30/2022] [Indexed: 11/09/2022]
Abstract
Glioblastoma multiforme (GBM) is one of the most deadly forms of cancer. Methods of characterizing these tumours are valuable for improving predictions of their progression and response to treatment. A mathematical model called the proliferation-invasion (PI) model has been used extensively in the literature to model the growth of these tumours, though it relies on known values of two key parameters: the tumour cell diffusivity and proliferation rate. Unfortunately, these parameters are difficult to estimate in a patient-specific manner, making personalized tumour forecasting challenging. In this paper, we develop and apply a deep learning model capable of making accurate estimates of these key GBM-characterizing parameters while simultaneously producing a full prediction of the tumour progression curve. Our method uses two sets of multi sequence MRI in order to produce estimations and relies on a preprocessing pipeline which includes brain tumour segmentation and conversion to tumour cellularity. We first apply our deep learning model to synthetic tumours to showcase the model's capabilities and identify situations where prediction errors are likely to occur. We then apply our model to a clinical dataset consisting of five patients diagnosed with GBM. For all patients, we derive evidence-based estimates for each of the PI model parameters and predictions for the future progression of the tumour, along with estimates of the parameter uncertainties. Our work provides a new, easily generalizable method for the estimation of patient-specific tumour parameters, which can be built upon to aid physicians in designing personalized treatments.
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Affiliation(s)
- Cameron Meaney
- Department of Applied Mathematics, University of Waterloo, Waterloo, Canada.
| | - Sunit Das
- Division of Neurosurgery, Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, Canada; Faculty of Medicine, University of Toronto, Toronto, Canada
| | - Errol Colak
- Faculty of Medicine, University of Toronto, Toronto, Canada; Department of Medical Imaging and Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, Canada; Odette Professorship in Artificial Intelligence for Medical Imaging, St. Michael's Hospital, Toronto, Canada
| | - Mohammad Kohandel
- Department of Applied Mathematics, University of Waterloo, Waterloo, Canada
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Brabec J, Friedjungová M, Vašata D, Englund E, Bengzon J, Knutsson L, Szczepankiewicz F, van Westen D, Sundgren PC, Nilsson M. Meningioma microstructure assessed by diffusion MRI: An investigation of the source of mean diffusivity and fractional anisotropy by quantitative histology. Neuroimage Clin 2023; 37:103365. [PMID: 36898293 PMCID: PMC10020119 DOI: 10.1016/j.nicl.2023.103365] [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: 11/25/2022] [Revised: 02/08/2023] [Accepted: 02/25/2023] [Indexed: 03/06/2023]
Abstract
BACKGROUND Mean diffusivity (MD) and fractional anisotropy (FA) from diffusion MRI (dMRI) have been associated with cell density and tissue anisotropy across tumors, but it is unknown whether these associations persist at the microscopic level. PURPOSE To quantify the degree to which cell density and anisotropy, as determined from histology, account for the intra-tumor variability of MD and FA in meningioma tumors. Furthermore, to clarify whether other histological features account for additional intra-tumor variability of dMRI parameters. MATERIALS AND METHODS We performed ex-vivo dMRI at 200 μm isotropic resolution and histological imaging of 16 excised meningioma tumor samples. Diffusion tensor imaging (DTI) was used to map MD and FA, as well as the in-plane FA (FAIP). Histology images were analyzed in terms of cell nuclei density (CD) and structure anisotropy (SA; obtained from structure tensor analysis) and were used separately in a regression analysis to predict MD and FAIP, respectively. A convolutional neural network (CNN) was also trained to predict the dMRI parameters from histology patches. The association between MRI and histology was analyzed in terms of out-of-sample (R2OS) on the intra-tumor level and within-sample R2 across tumors. Regions where the dMRI parameters were poorly predicted from histology were analyzed to identify features apart from CD and SA that could influence MD and FAIP, respectively. RESULTS Cell density assessed by histology poorly explained intra-tumor variability of MD at the mesoscopic level (200 μm), as median R2OS = 0.04 (interquartile range 0.01-0.26). Structure anisotropy explained more of the variation in FAIP (median R2OS = 0.31, 0.20-0.42). Samples with low R2OS for FAIP exhibited low variations throughout the samples and thus low explainable variability, however, this was not the case for MD. Across tumors, CD and SA were clearly associated with MD (R2 = 0.60) and FAIP (R2 = 0.81), respectively. In 37% of the samples (6 out of 16), cell density did not explain intra-tumor variability of MD when compared to the degree explained by the CNN. Tumor vascularization, psammoma bodies, microcysts, and tissue cohesivity were associated with bias in MD prediction based solely on CD. Our results support that FAIP is high in the presence of elongated and aligned cell structures, but low otherwise. CONCLUSION Cell density and structure anisotropy account for variability in MD and FAIP across tumors but cell density does not explain MD variations within the tumor, which means that low or high values of MD locally may not always reflect high or low tumor cell density. Features beyond cell density need to be considered when interpreting MD.
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Affiliation(s)
- Jan Brabec
- Medical Radiation Physics, Clinical Sciences, Lund University, Lund, Sweden; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA; Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
| | - Magda Friedjungová
- Faculty of Information Technology, Czech Technical University in Prague, Prague, Czech Republic
| | - Daniel Vašata
- Faculty of Information Technology, Czech Technical University in Prague, Prague, Czech Republic
| | | | - Johan Bengzon
- Neurosurgery, Clinical Sciences, Lund University, Lund, Sweden
| | - Linda Knutsson
- Medical Radiation Physics, Clinical Sciences, Lund University, Lund, Sweden; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA; Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | | | | | - Pia C Sundgren
- Diagnostic Radiology, Clinical Sciences, Lund University, Lund, Sweden; Lund University Bioimaging Centre, Lund University, Lund, Sweden; Department of Medical Imaging and Physiology, Skåne University Hospital, Lund University, Lund, Sweden
| | - Markus Nilsson
- Medical Radiation Physics, Clinical Sciences, Lund University, Lund, Sweden; Diagnostic Radiology, Clinical Sciences, Lund University, Lund, Sweden
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Bengtsson J, Thimansson E, Baubeta E, Zackrisson S, Sundgren PC, Bjartell A, Flondell-Sité D. Correlation between ADC, ADC ratio, and Gleason Grade group in prostate cancer patients undergoing radical prostatectomy: Retrospective multicenter study with different MRI scanners. Front Oncol 2023; 13:1079040. [PMID: 36890837 PMCID: PMC9986526 DOI: 10.3389/fonc.2023.1079040] [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: 10/24/2022] [Accepted: 02/03/2023] [Indexed: 02/22/2023] Open
Abstract
Background MRI is an important tool in the prostate cancer work-up, with special emphasis on the ADC sequence. This study aimed to investigate the correlation between ADC and ADC ratio compared to tumor aggressiveness determined by a histopathological examination after radical prostatectomy. Methods Ninety-eight patients with prostate cancer underwent MRI at five different hospitals prior to radical prostatectomy. Images were retrospectively analyzed individually by two radiologists. The ADC of the index lesion and reference tissues (contralateral normal prostatic, normal peripheral zone, and urine) was recorded. Absolute ADC and different ADC ratios were compared to tumor aggressivity according to the ISUP Gleason Grade Groups extracted from the pathology report using Spearman's rank correlation coefficient (ρ). ROC curves were used to evaluate the ability to discriminate between ISUP 1-2 and ISUP 3-5 and intra class correlation and Bland-Altman plots for interrater reliability. Results All patients had prostate cancer classified as ISUP grade ≥ 2. No correlation was found between ADC and ISUP grade. We found no benefit of using the ADC ratio over absolute ADC. The AUC for all metrics was close to 0.5, and no threshold could be extracted for prediction of tumor aggressivity. The interrater reliability was substantial to almost perfect for all variables analyzed. Conclusions ADC and ADC ratio did not correlate with tumor aggressiveness defined by ISUP grade in this multicenter MRI study. The result of this study is opposite to previous research in the field.
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Affiliation(s)
- Johan Bengtsson
- Department of Clinical Sciences, Radiology, Lund, Lund University, Lund, Sweden.,Department of Medical Imaging and Physiology, Skåne University Hospital, Lund, Sweden
| | - Erik Thimansson
- Department of Translational Medicine, Lund University, Malmö, Sweden.,Department of Radiology, Helsingborg Hospital, Helsingborg, Sweden
| | - Erik Baubeta
- Department of Medical Imaging and Physiology, Skåne University Hospital, Lund, Sweden.,Department of Translational Medicine, Lund University, Malmö, Sweden
| | - Sophia Zackrisson
- Department of Translational Medicine, Lund University, Malmö, Sweden.,Department of Medical Imaging and Physiology, Skåne University Hospital, Malmö, Sweden
| | - Pia Charlotte Sundgren
- Department of Clinical Sciences, Radiology, Lund, Lund University, Lund, Sweden.,Department of Medical Imaging and Physiology, Skåne University Hospital, Lund, Sweden.,Lund Bioimaging Center (LBIC), Lund University, Lund, Sweden
| | - Anders Bjartell
- Department of Translational Medicine, Lund University, Malmö, Sweden.,Department of Urology, Skåne University Hospital, Malmö, Sweden
| | - Despina Flondell-Sité
- Department of Translational Medicine, Lund University, Malmö, Sweden.,Department of Urology, Skåne University Hospital, Malmö, Sweden
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Quantitative Diffusion-Weighted Imaging Analyses to Predict Response to Neoadjuvant Immunotherapy in Patients with Locally Advanced Head and Neck Carcinoma. Cancers (Basel) 2022; 14:cancers14246235. [PMID: 36551718 PMCID: PMC9776484 DOI: 10.3390/cancers14246235] [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: 10/14/2022] [Revised: 12/09/2022] [Accepted: 12/13/2022] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND Neoadjuvant immune checkpoint blockade (ICB) prior to surgery may induce early pathological responses in head and neck squamous cell carcinoma (HNSCC) patients. Routine imaging parameters fail to diagnose these responses early on. Magnetic resonance (MR) diffusion-weighted imaging (DWI) has proven to be useful for detecting HNSCC tumor mass after (chemo)radiation therapy. METHODS 32 patients with stage II-IV, resectable HNSCC, treated at a phase Ib/IIa IMCISION trial (NCT03003637), were retrospectively analyzed using MR-imaging before and after two doses of single agent nivolumab (anti-PD-1) (n = 6) or nivolumab with ipilimumab (anti-CTLA-4) ICB (n = 26). The primary tumors were delineated pre- and post-treatment. A total of 32 features were derived from the delineation and correlated with the tumor regression percentage in the surgical specimen. RESULTS MR-DWI data was available for 24 of 32 patients. Smaller baseline tumor diameter (p = 0.01-0.04) and higher sphericity (p = 0.03) were predictive of having a good pathological response to ICB. Post-treatment skewness and the change in skewness between MRIs were negatively correlated with the tumor's regression (p = 0.04, p = 0.02). CONCLUSION Pre-treatment DWI tumor diameter and sphericity may be quantitative biomarkers for the prediction of an early pathological response to ICB. Furthermore, our data indicate that ADC skewness could be a marker for individual response evaluation.
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Evaluation of pretreatment ADC values as predictors of treatment response to neoadjuvant chemotherapy in patients with breast cancer - a multicenter study. Cancer Imaging 2022; 22:68. [PMID: 36494872 PMCID: PMC9733082 DOI: 10.1186/s40644-022-00501-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2022] [Accepted: 10/25/2022] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND Magnetic resonance imaging (MRI) can be used to diagnose breast cancer. Diffusion weighted imaging (DWI) and the apparent diffusion coefficient (ADC) can reflect tumor microstructure in a non-invasive manner. The correct prediction of response of neoadjuvant chemotherapy (NAC) is crucial for clinical routine. Our aim was to compare ADC values between patients with pathological complete response (pCR) and non-responders based upon a multi-center design to improve the correct patient selection, which patient would more benefit from NAC and which patient would not. METHODS For this study, data from 4 centers (from Japan, Brazil, Spain and United Kingdom) were retrospectively acquired. The time period was overall 2003-2019. The patient sample comprises 250 patients (all female; median age, 50.5). In every case, pretreatment breast MRI with DWI was performed. pCR was assessed by experienced pathologists in every center using the surgical specimen in the clinical routine work up. pCR was defined as no residual invasive disease in either breast or axillary lymph nodes after NAC. ADC values between the group with pCR and those with no pCR were compared using the Mann-Whitney U test (two-group comparisons). Univariable and multivariabe logistic regression analysis was performed to predict pCR status. RESULTS Overall, 83 patients (33.2%) achieved pCR. The ADC values of the patient group with pCR were lower compared with patients without pCR (0.98 ± 0.23 × 10- 3 mm2/s versus 1.07 ± 0.24 × 10- 3 mm2/s, p = 0.02). The ADC value achieved an odds ratio of 4.65 (95% CI 1.40-15.49) in univariable analysis and of 3.0 (95% CI 0.85-10.63) in multivariable analysis (overall sample) to be associated with pCR status. The odds ratios differed in the subgroup analyses in accordance with the molecular subtype. CONCLUSIONS The pretreatment ADC-value is associated with pathological complete response after NAC in breast cancer patients. This could aid in clinical routine to reduce treatment toxicity for patients, who would not benefit from NAC. However, this must be tested in further studies, as the overlap of the ADC values in both groups is too high for clinical prediction.
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Karabay N, Bülbül HM, Doğan E, İkiz AÖ, Bülbül G, Sarıoğlu S. The correlations between dynamic contrast enhanced magnetic resonance imaging and immunohistochemical data in head and neck squamous cell carcinomas. Turk J Med Sci 2022; 52:1950-1957. [PMID: 36945990 PMCID: PMC10390131 DOI: 10.55730/1300-0144.5543] [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: 03/19/2022] [Accepted: 09/21/2022] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND Dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) can in vivo characterize tumor microvascular environment. The aim of the present study was to reveal the DCE-MRI findings and to determine the correlation between these findings and immunohistochemical data in head and neck squamous cell carcinoma (HNSCC). METHODS Thirty-three patients diagnosed with primary HNSCC were evaluated retrospectively. DCE-MRI was conducted in all cases. CD34, CD105, and ki-67 expressions were analyzed with immunohistochemistry in tissue sections to determine micro-vessel density and proliferative activity. RESULTS The DCE-MRI is a successful technique in distinguishing tumor tissue from normal tissue. It was determined that Ve, Ktrans, and ki-67 values were significantly higher in high-stage tumors and there were positive correlations between the Ktrans value (by standard ROI) and CD34 MVDmax and CD34 MVDmean values. No statistically significant correlation was determined between other parameters in DCE-MRI and immunohistochemical data, and T stage. DISCUSSION DCE-MRI could successfully differentiate tumor tissue in HNSCC. Furthermore, it was observed that DCE-MRI had the potential to reveal certain immunohistochemical information in vivo.
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Affiliation(s)
- Nuri Karabay
- Department of Radiology, School of Medicine, Dokuz Eylül University, İzmir, Turkey
| | - Hande Melike Bülbül
- Department of Radiology, School of Medicine, Dokuz Eylül University, İzmir, Turkey
| | - Ersoy Doğan
- Department of Otorhinolaryngology, School of Medicine, Dokuz Eylül University, İzmir, Turkey
| | - Ahmet Ömer İkiz
- Department of Otorhinolaryngology, School of Medicine, Dokuz Eylül University, İzmir, Turkey
| | - Göksenil Bülbül
- Department of Pathology, School of Medicine, Dokuz Eylül University, İzmir, Turkey
| | - Sülen Sarıoğlu
- Department of Pathology, School of Medicine, Dokuz Eylül University, İzmir, Turkey
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Capturing cognitive changes in multiple sclerosis by performance-based functional and virtual reality assessments. Ann Phys Rehabil Med 2022; 66:101677. [PMID: 35667625 DOI: 10.1016/j.rehab.2022.101677] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2021] [Revised: 04/25/2022] [Accepted: 05/07/2022] [Indexed: 12/03/2022]
Abstract
Cognitive impairment (CI) has been recognized as one of the core multiple sclerosis (MS) symptoms that profoundly impact lives of people with MS (PwMS). Clinical trials have begun to focus on cognition as a primary or secondary outcome, but translating improvements in cognitive testing scores to functioning in the real world is difficult. Performance-based functional assessments and virtual reality (VR) assessments, which incorporate real-world challenges, have been proposed as a way to better assess functional cognition (i.e., cognitive performance and its impact on real-life cognitive functioning of PwMS) and could address the difficulty in evaluating the impact of a treatment on real-world functioning. In this narrative review, we identify and summarize some of the promising recent research applications of performance-based functional assessments and VR tools to assess functional cognition in MS. Overall, most of the studies suggest that functional and VR assessments can detect cognitive differences between people with and without MS and between PwMS with and without CI. Furthermore, performance on some of the functional and VR assessments was associated with performance on standard cognitive assessments. However, developing any guidelines on how to implement these assessments in clinical practice is difficult because of the relatively small sample size across these studies. Performance-based functional and VR assessments represent an innovative approach to increasing sensitivity of how cognitive impairments/abilities present in the daily life of PwMS. More studies, with a larger sample size, robust research methods, and pre- and post-treatment assessments, are warranted to validate relevant, accessible functional and VR assessments before implementing these assessment approaches in clinical practice.
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Husby T, Johansen H, Bogsrud TV, Hustad KV, Evensen BV, Boellaard R, Giskeødegård GF, Fagerli UM, Eikenes L. Prognostic value of combined MTV and ADC derived from baseline FDG PET/MRI in aggressive non-Hodgkins lymphoma. BMC Cancer 2022; 22:1117. [PMID: 36319985 PMCID: PMC9623965 DOI: 10.1186/s12885-022-10194-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2022] [Accepted: 10/18/2022] [Indexed: 01/24/2023] Open
Abstract
PURPOSE The aim of this prospective study was to investigate the prognostic value of metabolic tumor volume (MTV) and apparent diffusion coefficient (ADC) from baseline FDG PET/MRI compared to established clinical risk factors in terms of progression free survival (PFS) at 2 years in a cohort of diffuse large B-cell Lymphoma (DLBCL) and high-grade-B-cell lymphoma (HGBCL). METHODS Thirty-three patients and their baseline PET/MRI examinations were included. Images were read by two pairs of nuclear medicine physicians and radiologists for defining lymphoma lesions. MTV was computed on PET, and up to six lymphoma target lesions with restricted diffusion was defined for each PET/MRI examination. Minimum ADC (ADCmin) and the corresponding mean ADC (ADCmean) from the target lesion with the lowest ADCmin were included in the analyses. For the combined PET/MRI parameters, the ratio between MTV and the target lesion with the lowest ADCmin (MTV/ADCmin) and the corresponding ADCmean (MTV/ADCmean) was calculated for each patient. Clinical, histological, and PET/MRI parameters were compared between the treatment failure and treatment response group, while survival analyses for each variable was performed by using univariate Cox regression. In case of significant variables in the Cox regression analyses, Kaplan-Meier survival analyses with log-rank test was used to study the effect of the variables on PFS. RESULTS ECOC PS scale ≥2 (p = 0.05) and ADCmean (p = 0.05) were significantly different between the treatment failure group (n = 6) and those with treatment response (n = 27). Survival analyses showed that ADCmean was associated with PFS (p = 0.02, [HR 2.3 for 1 SD increase]), while combining MTV and ADC did not predict outcome. In addition, ECOG PS ≥2 (p = 0.01, [HR 13.3]) and histology of HGBCL (p = 0.02 [HR 7.6]) was significantly associated with PFS. CONCLUSIONS ADCmean derived from baseline MRI could be a prognostic imaging biomarker for DLBCL and HGBCL. Baseline staging with PET/MRI could therefore give supplementary prognostic information compared to today's standard PET/CT.
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Affiliation(s)
- Trine Husby
- grid.5947.f0000 0001 1516 2393Department of Circulation and Medical Imaging, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Postboks, 8905 Trondheim, Norway ,grid.52522.320000 0004 0627 3560Department of Oncology, St. Olavs hospital, Trondheim University Hospital, Trondheim, Norway
| | - Håkon Johansen
- grid.52522.320000 0004 0627 3560Department of Radiology and Nuclear Medicine, St. Olavs hospital, Trondheim University Hospital, Trondheim, Norway
| | - Trond Velde Bogsrud
- grid.412244.50000 0004 4689 5540PET-Centre, University Hospital of North Norway, Tromsø, Norway ,grid.154185.c0000 0004 0512 597XPET-Centre, Aarhus University Hospital, Aarhus, Denmark
| | - Kari Vekseth Hustad
- grid.52522.320000 0004 0627 3560Department of Radiology and Nuclear Medicine, St. Olavs hospital, Trondheim University Hospital, Trondheim, Norway
| | - Birte Veslemøy Evensen
- grid.52522.320000 0004 0627 3560Department of Radiology and Nuclear Medicine, St. Olavs hospital, Trondheim University Hospital, Trondheim, Norway
| | - Ronald Boellaard
- grid.4494.d0000 0000 9558 4598Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, Groningen, The Netherlands ,grid.16872.3a0000 0004 0435 165XDepartment of Radiology and Nuclear Medicine, Cancer Center Amsterdam, University Medical Centers Amsterdam, VUMC, Amsterdam, The Netherlands
| | - Guro F. Giskeødegård
- grid.5947.f0000 0001 1516 2393Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
| | - Unn-Merete Fagerli
- grid.52522.320000 0004 0627 3560Department of Oncology, St. Olavs hospital, Trondheim University Hospital, Trondheim, Norway ,grid.5947.f0000 0001 1516 2393Department of Clinical and Molecular Medicine, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
| | - Live Eikenes
- grid.5947.f0000 0001 1516 2393Department of Circulation and Medical Imaging, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Postboks, 8905 Trondheim, Norway
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Thormann M, Surov A, Pech M, March C, Hass P, Damm R, Omari J. Local ablation of hepatocellular carcinoma by interstitial brachytherapy: prediction of outcome by diffusion-weighted imaging. Acta Radiol 2022; 64:1331-1340. [PMID: 36262039 DOI: 10.1177/02841851221129714] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND Interstitial brachytherapy (iBT) has become a viable treatment option in the therapy of early and intermediate stage hepatocellular carcinoma (HCC). Prognostic imaging tools to predict patient outcome are missing. PURPOSE To assess the predictive value of baseline diffusion-weighted imaging in HCC before iBT with regard to local tumor control and overall survival (OS). MATERIAL AND METHODS We retrospectively identified 107 patients who underwent iBT for HCC from 2011 to 2018 from our database. Apparent diffusion coefficient (ADC) values for each treated lesion were analyzed in region of interest measurements. Additionally, explorative combined ratios adjusting total measured lesion area and mean measured lesion area per patient by ADC values were calculated. Measurements underwent a univariate and multivariate Cox regression analysis. The log rank test was then used to verify prognostic cutoff levels for median survival time. RESULTS A total of 189 lesions in 81 patients were measured. Median survival of patients was 46.0 months. Neither ADC parameter was indicative of local tumor control. Lesion size >5 cm was associated with lower local tumor control (hazard ratio [HR]=4.292, 95% confidence interval [CI]=1.285-14.331; P = 0.018). Average measured lesion area divided by ADCmin (ADCarea mean, min) was identified to independently predict OS (HR=1.994, 95% CI=1.172-3.392; P = 0.011). A cutoff based on the variable's median (0.29 × 10-4 AU) identified patients with poor outcome (OS 36 vs. 61 months) for lower ADCarea mean, min values as verified by the log-rank test (P = 0.040). CONCLUSION Pre-treatment ADCarea mean, min may serve as an independent predictor of OS in patients with HCC undergoing iBT.
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Affiliation(s)
- Maximilian Thormann
- Clinic for Radiology and Nuclear Medicine, 39067University Hospital Magdeburg, Magdeburg, Germany
| | - Alexey Surov
- Clinic for Radiology and Nuclear Medicine, 39067University Hospital Magdeburg, Magdeburg, Germany
| | - Maciej Pech
- Clinic for Radiology and Nuclear Medicine, 39067University Hospital Magdeburg, Magdeburg, Germany
| | - Christine March
- Clinic for Radiology and Nuclear Medicine, 39067University Hospital Magdeburg, Magdeburg, Germany
| | - Peter Hass
- Clinic for Radiation Oncology, 39067University Hospital Magdeburg, Magdeburg, Germany
| | - Robert Damm
- Clinic for Radiology and Nuclear Medicine, 39067University Hospital Magdeburg, Magdeburg, Germany
| | - Jazan Omari
- Clinic for Radiology and Nuclear Medicine, 39067University Hospital Magdeburg, Magdeburg, Germany
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Brancato V, Cavaliere C, Garbino N, Isgrò F, Salvatore M, Aiello M. The relationship between radiomics and pathomics in Glioblastoma patients: Preliminary results from a cross-scale association study. Front Oncol 2022; 12:1005805. [PMID: 36276163 PMCID: PMC9582951 DOI: 10.3389/fonc.2022.1005805] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2022] [Accepted: 09/21/2022] [Indexed: 12/01/2022] Open
Abstract
Glioblastoma multiforme (GBM) typically exhibits substantial intratumoral heterogeneity at both microscopic and radiological resolution scales. Diffusion Weighted Imaging (DWI) and dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) are two functional MRI techniques that are commonly employed in clinic for the assessment of GBM tumor characteristics. This work presents initial results aiming at determining if radiomics features extracted from preoperative ADC maps and post-contrast T1 (T1C) images are associated with pathomic features arising from H&E digitized pathology images. 48 patients from the public available CPTAC-GBM database, for which both radiology and pathology images were available, were involved in the study. 91 radiomics features were extracted from ADC maps and post-contrast T1 images using PyRadiomics. 65 pathomic features were extracted from cell detection measurements from H&E images. Moreover, 91 features were extracted from cell density maps of H&E images at four different resolutions. Radiopathomic associations were evaluated by means of Spearman's correlation (ρ) and factor analysis. p values were adjusted for multiple correlations by using a false discovery rate adjustment. Significant cross-scale associations were identified between pathomics and ADC, both considering features (n = 186, 0.45 < ρ < 0.74 in absolute value) and factors (n = 5, 0.48 < ρ < 0.54 in absolute value). Significant but fewer ρ values were found concerning the association between pathomics and radiomics features (n = 53, 0.5 < ρ < 0.65 in absolute value) and factors (n = 2, ρ = 0.63 and ρ = 0.53 in absolute value). The results of this study suggest that cross-scale associations may exist between digital pathology and ADC and T1C imaging. This can be useful not only to improve the knowledge concerning GBM intratumoral heterogeneity, but also to strengthen the role of radiomics approach and its validation in clinical practice as "virtual biopsy", introducing new insights for omics integration toward a personalized medicine approach.
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Affiliation(s)
| | | | | | - Francesco Isgrò
- Department of Electrical Engineering and Information Technologies, University of Napoli Federico II, Napoli, Italy
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