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Guo R, Lu F, Lin J, Fu C, Liu M, Yang S. Multi-b-value DWI to evaluate the synergistic antiproliferation and anti-heterogeneity effects of bufalin plus sorafenib in an orthotopic HCC model. Eur Radiol Exp 2024; 8:43. [PMID: 38467904 PMCID: PMC10928042 DOI: 10.1186/s41747-024-00448-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: 09/22/2023] [Accepted: 02/06/2024] [Indexed: 03/13/2024] Open
Abstract
BACKGROUND Multi-b-value diffusion-weighted imaging (DWI) with different postprocessing models allows for evaluating hepatocellular carcinoma (HCC) proliferation, spatial heterogeneity, and feasibility of treatment strategies. We assessed synergistic effects of bufalin+sorafenib in orthotopic HCC-LM3 xenograft nude mice by using intravoxel incoherent motion (IVIM), diffusion kurtosis imaging (DKI), a stretched exponential model (SEM), and a fractional-order calculus (FROC) model. METHODS Twenty-four orthotopic HCC-LM3 xenograft mice were divided into bufalin+sorafenib, bufalin, sorafenib treatment groups, and a control group. Multi-b-value DWI was performed using a 3-T scanner after 3 weeks' treatment to obtain true diffusion coefficient Dt, pseudo-diffusion coefficient Dp, perfusion fraction f, mean diffusivity (MD), mean kurtosis (MK), distributed diffusion coefficient (DDC), heterogeneity index α, diffusion coefficient D, fractional order parameter β, and microstructural quantity μ. Necrotic fraction (NF), standard deviation (SD) of hematoxylin-eosin staining, and microvessel density (MVD) of anti-CD31 staining were evaluated. Correlations of DWI parameters with histopathological results were analyzed, and measurements were compared among four groups. RESULTS In the final 22 mice, f positively correlated with MVD (r = 0.679, p = 0.001). Significantly good correlations of MK (r = 0.677), α (r = -0.696), and β (r= -0.639) with SD were observed (all p < 0.010). f, MK, MVD, and SD were much lower, while MD, α, β, and NF were higher in bufalin plus sorafenib group than control group (all p < 0.050). CONCLUSION Evaluated by IVIM, DKI, SEM, and FROC, bufalin+sorafenib was found to inhibit tumor proliferation and angiogenesis and reduce spatial heterogeneity in HCC-LM3 models. RELEVANCE STATEMENT Multi-b-value DWI provides potential metrics for evaluating the efficacy of treatment in HCC. KEY POINTS • Bufalin plus sorafenib combination may increase the effectiveness of HCC therapy. • Multi-b-value DWI depicted HCC proliferation, angiogenesis, and spatial heterogeneity. • Multi-b-value DWI may be a noninvasive method to assess HCC therapeutic efficacy.
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Affiliation(s)
- Ran Guo
- Department of Radiology, Shanghai Municipal Hospital of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, 274 Middle Zhi-jiang Road, Shanghai, 200071, People's Republic of China
| | - Fang Lu
- Department of Radiology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, 201203, People's Republic of China
| | - Jiang Lin
- Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, 200032, People's Republic of China
- Shanghai Institute of Medical Imaging, Shanghai, 200032, People's Republic of China
| | - Caixia Fu
- MR Application Development, Siemens Shenzhen Magnetic Resonance Ltd, Shenzhen, 518057, People's Republic of China
| | - Mengxiao Liu
- MR scientific Marketing, Diagnostic Imaging, Siemens Healthineers Ltd, Shanghai, 201318, People's Republic of China
| | - Shuohui Yang
- Department of Radiology, Shanghai Municipal Hospital of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, 274 Middle Zhi-jiang Road, Shanghai, 200071, People's Republic of China.
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Wen D, Peng P, Yue X, Xu C, Pu Q, Ming Y, Yang H, Zhang M, Ren Y, Sun J. Comparative study of stretched-exponential and kurtosis models of diffusion-weighted imaging in renal assessment to distinguish patients with primary aldosteronism from healthy controls. PLoS One 2024; 19:e0298207. [PMID: 38330049 PMCID: PMC10852313 DOI: 10.1371/journal.pone.0298207] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Accepted: 01/20/2024] [Indexed: 02/10/2024] Open
Abstract
PURPOSE To compare the ability of diffusion parameters obtained by stretched-exponential and kurtosis models of diffusion-weighted imaging (DWI) to distinguish between patients with primary aldosteronism (PA) and healthy controls (HCs) in renal assessment. MATERIALS AND METHODS A total of 44 participants (22 patients and 22 HCs) underwent renal MRI with an 11 b-value DWI sequence and a 3 b-value diffusion kurtosis imaging (DKI) sequence from June 2021 to April 2022. Binary logistic regression was used to construct regression models combining different diffusion parameters. Receiver-operating characteristic (ROC) curve analysis and comparisons were used to evaluate the ability of single diffusion parameters and combined diffusion models to distinguish between the two groups. RESULTS A total of six diffusion parameters (including the cortical anomalous exponent term [α_Cortex], medullary fractional anisotropy [FA_Medulla], cortical FA [FA_Cortex], cortical axial diffusivity [Da_Cortex], medullary mean diffusivity [MD_Medulla] and medullary radial diffusivity [Dr_Medulla]) were included, and 10 regression models were studied. The area under the curve (AUC) of Dr_Medulla was 0.855, comparable to that of FA_Cortex and FA_Medulla and significantly higher than that of α_Cortex, Da_Cortex and MD_Medulla. The AUC of the Model_all parameters was 0.967, comparable to that of Model_FA (0.946) and Model_DKI (0.966) and significantly higher than that of the other models. The sensitivity and specificity of Model_all parameters were 87.2% and 95%, respectively. CONCLUSION The Model_all parameters, Model_FA and Model_DKI were valid for differentiating between PA patients and HCs with similar differentiation efficacy and were superior to single diffusion parameters and other models.
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Affiliation(s)
- Deying Wen
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
| | - Pengfei Peng
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
| | - Xun Yue
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
- Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, China
| | - Chenxiao Xu
- Department of Endocrinology and Metabolism, West China Hospital, Sichuan University, Chengdu, China
| | - Qian Pu
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
| | - Yue Ming
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
| | - Huiyi Yang
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
| | | | - Yan Ren
- Department of Endocrinology and Metabolism, West China Hospital, Sichuan University, Chengdu, China
| | - Jiayu Sun
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
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Gao Y, Wang Y, Zhang H, Li X, Han L. The outstanding diagnostic value of DKI in multimodal magnetic resonance imaging for benign and malignant breast tumors: A diagnostic accuracy study. Medicine (Baltimore) 2023; 102:e35337. [PMID: 37800758 PMCID: PMC10553060 DOI: 10.1097/md.0000000000035337] [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: 06/14/2023] [Accepted: 08/31/2023] [Indexed: 10/07/2023] Open
Abstract
To explore the value of applying different magnetic resonance imaging MRI sequences in the differential diagnosis of benign and malignant breast tumors. Routine breast magnetic resonance scans (T1-weighted image, T1WI; T2-weighted image, T2WI), dynamically enhanced scans, diffusion-weighted Imaging, and diffusion kurtosis imaging (DKI) scans were performed on 63 female patients with breast-occupying lesions. The benign and malignant lesions were confirmed by biopsy, excision-histopathology reports. There are 70 lesions, of which 46 are benign and 24 are malignant. Analyze the primary conditions, such as the shape, size, and boundary of the lesion, and determine the apparent diffusion coefficient (ADC), mean kurtosis (MK), and mean diffusion (MD) values. The receiver operating characteristic curve was used to evaluate the value and difference in differentiating benign and malignant lesions. In this study, the results of the 2 testers both showed that the MK of malignant lesions was significantly higher than that of benign lesions (P < .001), and the MD of benign lesions was higher than that of malignant lesions (P < .05). The ADC of benign lesions was higher than that of malignant lesions (P < .05). For MK, the area under the curve of the 2 testers was 0.855/0.869, respectively. When the best cutoff value of MK for tester 1 was 0.515, the sensitivity and specificity of MK for diagnosing malignant tumors were 83.3%/87.0%, respectively. For the 2 testers MD, and ADC, the area under the curve was < 0.5, and the diagnostic value was low. The MK value obtained by DKI has a specific value in the differential diagnosis of benign and malignant breast lesions. DKI is helpful in the identification of benign and malignant breast tumors. The diagnostic value is outstanding, and its importance to the changes in the microstructure of the organization needs to be further explored.
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Affiliation(s)
- Yufei Gao
- Department of Radiology, The First Hospital of Hebei Medical University, Shijiazhuang, China
| | - Yong Wang
- Department of Radiology, The First Hospital of Hebei Medical University, Shijiazhuang, China
| | - Hui Zhang
- Department of Radiology, Hebei General Hospital, Shijiazhuang, China
| | - Xiaolei Li
- Hebei Provincial Center for Disease Control and Prevention, Shijiazhuang, China
| | - Lina Han
- Department of Neurology, Hebei General Hospital, Shijiazhuang, China
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Wang Y, Yuan D, Sun H, Pan X, Lu F, Li H, Huang Y, Tang S. Non-invasive preoperative prediction of Edmondson-Steiner grade of hepatocellular carcinoma based on contrast-enhanced ultrasound using ensemble learning. Front Oncol 2023; 13:1116129. [PMID: 37476377 PMCID: PMC10354515 DOI: 10.3389/fonc.2023.1116129] [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: 12/05/2022] [Accepted: 05/15/2023] [Indexed: 07/22/2023] Open
Abstract
Purpose This study aimed to explore the clinical value of non-invasive preoperative Edmondson-Steiner grade of hepatocellular carcinoma (HCC) using contrast-enhanced ultrasound (CEUS). Methods 212 cases of HCCs were retrospectively included, including 83 cases of high-grade HCCs and 129 cases of low-grade HCCs. Three representative CEUS images were selected from the arterial phase, portal vein phase, and delayed phase and stored in a 3-dimensional array. ITK-SNAP was used to segment the tumor lesions manually. The Radiomics method was conducted to extract high-dimensional features on these contrast-enhanced ultrasound images. Then the independent sample T-test and the Least Absolute Shrinkage and Selection Operator (LASSO) were employed to reduce the feature dimensions. The optimized features were modeled by a classifier based on ensemble learning, and the Edmondson Steiner grading was predicted in an independent testing set using this model. Results A total of 1338 features were extracted from the 3D images. After the dimension reduction, 10 features were finally selected to establish the model. In the independent testing set, the integrated model performed best, with an AUC of 0.931. Conclusion This study proposed an Edmondson-Steiner grading method for HCC with CEUS. The method has good classification performance on independent testing sets, which can provide quantitative analysis support for clinical decision-making.
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Affiliation(s)
- Yao Wang
- Department of Ultrasound, Shengjing Hospital of China Medical University, Shenyang, Liaoning, China
| | - Dongbo Yuan
- College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, China
| | - Hang Sun
- School of Information Science and Engineering, Shenyang Ligong University, Shenyang, China
| | - Xiaoguang Pan
- Computer Science and Technology, School of Information and Control Engineering, Liaoning Petrochemical University, Fushun, China
| | - Fangnan Lu
- College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, China
| | - Hong Li
- College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, China
| | - Ying Huang
- Department of Ultrasound, Shengjing Hospital of China Medical University, Shenyang, Liaoning, China
| | - Shaoshan Tang
- Department of Ultrasound, Shengjing Hospital of China Medical University, Shenyang, Liaoning, China
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Barham M, Kuroda M, Yoshimura Y, Hamada K, Khasawneh A, Sugimoto K, Konishi K, Tekiki N, Sugianto I, Bamgbose BO, Ishizaka H, Shimizu Y, Nakamitsu Y, Al-Hammad WE, Kamizaki R, Kurozumi A, Matsushita T, Ohno S, Asaumi J. Evaluation of calculation processes of apparent diffusion coefficient subtraction method (ASM) imaging. PLoS One 2023; 18:e0282462. [PMID: 36848353 PMCID: PMC9970062 DOI: 10.1371/journal.pone.0282462] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2021] [Accepted: 02/16/2023] [Indexed: 03/01/2023] Open
Abstract
A number of restricted diffusion (RD) imaging techniques, such as diffusion kurtosis (DK) imaging and Q space imaging, have been developed and proven to be useful for the diagnosis of diseases, including cerebral gliomas and cerebrovascular infarction. In particular, apparent diffusion coefficient (ADC) subtraction method (ASM) imaging has become available recently as a novel RD imaging technique. ASM is based on the difference between the ADC values in an image pair of two ADC maps, ADC basic (ADCb) and ADC modify (ADCm), which are created from diffusion-weighted images taken using short and long effective diffusion times, respectively. The present study aimed to assess the potential of different types of ASM imaging by comparing them with DK imaging which is the gold-standard RD imaging technique. In the present basic study using both polyethylene glycol phantom and cell-containing bio-phantom, three different types of ASM images were created using different calculation processes. ASM/A is an image calculated by dividing the absolute difference between ADCb and ADCm by ADCb several times. By contrast, ASM/S is an image created by dividing the absolute difference between ADCb and ADCm by the standard deviation of ADCb several times. As for positive ASM/A image (PASM/A), the positive image, which was resultant after subtracting ADCb from ADCm, was divided by ADCb several times. A comparison was made between the types of ASM and DK images. The results showed the same tendency between ASM/A in addition to both ASM/S and PASM/A. By increasing the number of divisions by ADCb from three to five times, ASM/A images transformed from DK-mimicking to more RD-sensitive images compared with DK images. These observations suggest that ASM/A images may prove useful for future clinical applications in RD imaging protocols for the diagnosis of diseases.
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Affiliation(s)
- Majd Barham
- Department of Oral and Maxillofacial Radiology, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama, Japan
| | - Masahiro Kuroda
- Radiological Technology, Graduate School of Health Sciences, Okayama University, Okayama, Japan
- * E-mail:
| | - Yuuki Yoshimura
- Radiological Technology, Graduate School of Health Sciences, Okayama University, Okayama, Japan
- Radiology Diagnosis, Okayama Saiseikai General Hospital, Okayama, Japan
| | - Kentaro Hamada
- Radiological Technology, Graduate School of Health Sciences, Okayama University, Okayama, Japan
| | - Abdullah Khasawneh
- Department of Oral and Maxillofacial Radiology, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama, Japan
| | - Kohei Sugimoto
- Radiological Technology, Graduate School of Health Sciences, Okayama University, Okayama, Japan
| | - Kohei Konishi
- Radiological Technology, Graduate School of Health Sciences, Okayama University, Okayama, Japan
| | - Nouha Tekiki
- Department of Oral and Maxillofacial Radiology, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama, Japan
| | - Irfan Sugianto
- Department of Oral and Maxillofacial Radiology, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama, Japan
| | - Babatunde O. Bamgbose
- Department of Oral and Maxillofacial Radiology, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama, Japan
| | - Hinata Ishizaka
- Radiological Technology, Graduate School of Health Sciences, Okayama University, Okayama, Japan
| | - Yudai Shimizu
- Department of Oral and Maxillofacial Radiology, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama, Japan
| | - Yuki Nakamitsu
- Radiological Technology, Graduate School of Health Sciences, Okayama University, Okayama, Japan
| | - Wlla E. Al-Hammad
- Department of Oral and Maxillofacial Radiology, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama, Japan
| | - Ryo Kamizaki
- Radiological Technology, Graduate School of Health Sciences, Okayama University, Okayama, Japan
| | - Akira Kurozumi
- Central Division of Radiology, Okayama University Hospital, Okayama, Japan
| | - Toshi Matsushita
- Central Division of Radiology, Okayama University Hospital, Okayama, Japan
| | - Seiichiro Ohno
- Central Division of Radiology, Okayama University Hospital, Okayama, Japan
| | - Junichi Asaumi
- Department of Oral and Maxillofacial Radiology, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama, Japan
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Clinical and imaging features preoperative evaluation of histological grade and microvascular infiltration of hepatocellular carcinoma. BMC Gastroenterol 2022; 22:369. [PMID: 35915440 PMCID: PMC9341046 DOI: 10.1186/s12876-022-02449-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Accepted: 07/21/2022] [Indexed: 11/13/2022] Open
Abstract
Background To predict the histological grade and microvascular invasion (MVI) in patients with HCC. Methods A retrospective analysis was conducted on 175 patients who underwent MRI enhancement scanning (from September 2016.9 to October 2020). They were divided into MVI positive, MVI negative, Grade-high and Grade-low groups. Results The AFP of 175 HCC patients distributed in MVI positive and negative groups, Grade-low and Grade-high groups were statistically significant (P = 0.002 and 0.03, respectively). Multiple HCC lesions were more common in MVI positive and Grade-high groups. Correspondingly, more single lesions were found in MVI negative and Grade-low groups (P = 0.005 and 0.019, respectively). Capsule on MRI was more common in MVI negative and Grade-high groups, and the difference was statistically significant (P = 0.02 and 0.011, respectively). There were statistical differences in the distribution of three MRI signs: artistic rim enhancement, artistic peripheral enhancement, and tumor margin between MVI positive and MVI negative groups (P = 0.001, < 0.001, and < 0.001, respectively). Tumor hypointensity on HBP was significantly different between MVI positive and negative groups (P < 0.001). Conclusions Our research shows that preoperative enhanced imaging can be used to predict MVI and tumor differentiation grade of HCC. The prognosis of MVI-negative group was better than that of MVI-positive group.
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Qin YL, Wang S, Chen F, Liu HX, Yue KT, Wang XZ, Ning HF, Dong P, Yu XR, Wang GZ. Prediction of outcomes by diffusion kurtosis imaging in patients with large (≥5 cm) hepatocellular carcinoma after liver resection: A retrospective study. Front Oncol 2022; 12:939358. [DOI: 10.3389/fonc.2022.939358] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Accepted: 10/18/2022] [Indexed: 11/18/2022] Open
Abstract
PurposeTo evaluate preoperative diffusion kurtosis imaging (DKI) in predicting the outcomes of large hepatocellular carcinoma (HCC) after liver resection (LR).Materials and methodsFrom January 2015 to December 2017, patients with a large (≥5cm) HCC who underwent preoperative DKI were retrospectively reviewed. The correlations of the mean kurtosis (MK), mean diffusivity (MD), and apparent diffusion coefficient (ADC) with microvascular invasion (MVI) or histological grade were analyzed. Cox regression analyses were performed to identify the predictors of recurrence-free survival (RFS) and overall survival (OS). A nomogram to predict RFS was established. P<0.05 was considered as statistically significant.ResultsA total of 97 patients (59 males and 38 females, 56.0 ± 10.9 years) were included in this study. The MK, MD, and ADC values were correlated with MVI or histological grade (P<0.01). With a median follow-up time of 41.2 months (range 12-69 months), 67 patients (69.1%) experienced recurrence and 41 patients (42.3%) were still alive. The median RFS and OS periods after LR were 29 and 45 months, respectively. The 1-, 3-, and 5-year RFS and OS rates were 88.7%, 41.2%, and 21.7% and 99.0%, 68.3%, and 25.6%, respectively. MK (P<0.001), PVT (P<0.001), and ADC (P=0.033) were identified as independent predictor factors for RFS. A nomogram including the MK value for RFS showed the best performance, and the C-index was 0.895.ConclusionThe MK value obtained from DKI is a potential predictive factor for recurrence and poor survival, which could provide valuable information for guiding the efficacy of LR in patients with large HCC.
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Granata V, Fusco R, Belli A, Danti G, Bicci E, Cutolo C, Petrillo A, Izzo F. Diffusion weighted imaging and diffusion kurtosis imaging in abdominal oncological setting: why and when. Infect Agent Cancer 2022; 17:25. [PMID: 35681237 PMCID: PMC9185934 DOI: 10.1186/s13027-022-00441-3] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2022] [Accepted: 05/30/2022] [Indexed: 12/13/2022] Open
Abstract
This article provides an overview of diffusion kurtosis (DKI) imaging in abdominal oncology. DKI allows for more data on tissue structures than the conventional diffusion model (DWI). However, DKI requires high quality images at b-values greater than 1000 s/mm2 and high signal-to-noise ratio (SNR) that traditionally MRI systems are not able to acquire and therefore there are generally amplified anatomical distortions on the images due to less homogeneity of the field. Advances in both hardware and software on modern MRI scanners have currently enabled ultra-high b-value imaging and offered the ability to apply DKI to multiple extracranial sites. Previous studies have evaluated the ability of DKI to characterize and discriminate tumor grade compared to conventional DWI. Additionally, in several studies the DKI sequences used were based on planar echo (EPI) acquisition, which is susceptible to motion, metal and air artefacts and prone to low SNRs and distortions, leading to low quality images for some small lesions, which may affect the accuracy of the results. Another problem is the optimal b-value of DKI, which remains to be explored and not yet standardized, as well as the manual selection of the ROI, which could affect the accuracy of some parameters.
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Affiliation(s)
- Vincenza Granata
- Division of Radiology, "Istituto Nazionale Tumori IRCCS Fondazione Pascale - IRCCS di Napoli", I-80131, Naples, Italy.
| | | | - Andrea Belli
- Division of Hepatobiliary Surgical Oncology, "Istituto Nazionale Tumori IRCCS Fondazione Pascale - IRCCS di Napoli", I-80131, Naples, Italy
| | - Ginevra Danti
- Department of Radiology, Azienda Ospedaliero-Universitaria Careggi, Florence, Italy.,Italian Society of Medical and Interventional Radiology, SIRM Foundation, Milan, Italy
| | - Eleonora Bicci
- Department of Radiology, Azienda Ospedaliero-Universitaria Careggi, Florence, Italy
| | - Carmen Cutolo
- Department of Medicine, Surgery and Dentistry, University of Salerno, Salerno, Italy
| | - Antonella Petrillo
- Division of Radiology, "Istituto Nazionale Tumori IRCCS Fondazione Pascale - IRCCS di Napoli", I-80131, Naples, Italy
| | - Francesco Izzo
- Division of Hepatobiliary Surgical Oncology, "Istituto Nazionale Tumori IRCCS Fondazione Pascale - IRCCS di Napoli", I-80131, Naples, Italy
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Wang F, Yan CY, Wang CH, Yang Y, Zhang D. The Roles of Diffusion Kurtosis Imaging and Intravoxel Incoherent Motion Diffusion-Weighted Imaging Parameters in Preoperative Evaluation of Pathological Grades and Microvascular Invasion in Hepatocellular Carcinoma. Front Oncol 2022; 12:884854. [PMID: 35646649 PMCID: PMC9131658 DOI: 10.3389/fonc.2022.884854] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2022] [Accepted: 03/31/2022] [Indexed: 12/14/2022] Open
Abstract
Background Currently, there are disputes about the parameters of diffusion kurtosis imaging (DKI), intravoxel incoherent motion (IVIM), and diffusion-weighted imaging (DWI) in predicting pathological grades and microvascular invasion (MVI) in hepatocellular carcinoma (HCC). The aim of our study was to investigate and compare the predictive power of DKI and IVIM-DWI parameters for preoperative evaluation of pathological grades and MVI in HCC. Methods PubMed, Web of Science, and Embase databases were searched for relevant studies published from inception to October 2021. Review Manager 5.3 was used to summarize standardized mean differences (SMDs) of mean kurtosis (MK), mean diffusivity (MD), tissue diffusivity (D), pseudo diffusivity (D*), perfusion fraction (f), mean apparent diffusion coefficient (ADCmean), and minimum apparent diffusion coefficient (ADCmin). Stata12.0 was used to pool the sensitivity, specificity, and area under the curve (AUC). Overall, 42 up-to-standard studies with 3,807 cases of HCC were included in the meta-analysis. Results The SMDs of ADCmean, ADCmin, and D values, but not those of D* and f values, significantly differed between well, moderately, and poorly differentiated HCC (P < 0.01). The sensitivity, specificity, and AUC of the MK, D, ADCmean, and ADCmin for preoperative prediction of poorly differentiated HCC were 69%/94%/0.89, 87%/80%/0.89, 82%/75%/0.86, and 83%/64%/0.81, respectively. In addition, the sensitivity, specificity, and AUC of the D and ADCmean for preoperative prediction of well-differentiated HCC were 87%/83%/0.92 and 82%/88%/0.90, respectively. The SMDs of ADCmean, ADCmin, D, MD, and MK values, but not f values, showed significant differences (P < 0.01) between MVI-positive (MVI+) and MVI-negative (MVI-) HCC. The sensitivity and specificity of D and ADCmean for preoperative prediction of MVI+ were 80%/80% and 74%/71%, respectively; the AUC of the D (0.87) was significantly higher than that of ADCmean (0.78) (Z = −2.208, P = 0.027). Sensitivity analysis showed that the results of the above parameters were stable and reliable, and subgroup analysis confirmed a good prediction effect. Conclusion DKI parameters (MD and MK) and IVIM-DWI parameters (D value, ADCmean, and ADCmin) can be used as a noninvasive and simple preoperative examination method to predict the grade and MVI in HCC. Compared with ADCmean and ADCmin, MD and D values have higher diagnostic efficacy in predicting the grades of HCC, and D value has superior diagnostic efficacy to ADCmean in predicting MVI+ in HCC. However, f value cannot predict the grade or MVI in HCC.
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Affiliation(s)
- Fei Wang
- Department of Medical Imaging, Luzhou People's Hospital, Luzhou, China.,Department of Radiology, Xinqiao Hospital, Third Military Medical University, Chongqing, China
| | - Chun Yue Yan
- Department of Obstetrics, Luzhou People's Hospital, Luzhou, China
| | - Cai Hong Wang
- Department of Radiology, Xinqiao Hospital, Third Military Medical University, Chongqing, China
| | - Yan Yang
- Department of Radiology, Xinqiao Hospital, Third Military Medical University, Chongqing, China
| | - Dong Zhang
- Department of Radiology, Xinqiao Hospital, Third Military Medical University, Chongqing, China
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Xia W, Peng T, Guan R, Zhou Y, Zeng C, Lin Y, Wu Z, Tan H. Development of a novel prognostic nomogram for the early recurrence of liver cancer after curative hepatectomy. ANNALS OF TRANSLATIONAL MEDICINE 2021; 9:1541. [PMID: 34790747 PMCID: PMC8576734 DOI: 10.21037/atm-21-4837] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/11/2021] [Accepted: 10/22/2021] [Indexed: 02/05/2023]
Abstract
BACKGROUND Hepatocellular carcinoma (HCC) is one of the most common malignant cancers worldwide. Curative resection is an effective treatment but HCC recurrence rates remain high. This study aimed to establish a novel prognostic nomogram to assess the risk of recurrence in patients following curative resection. METHODS A total of 410 patients undergoing HCC curative resection were recruited from the Guangdong Provincial People's Hospital (GDPH). The cohort was divided into a training group (n=291) and a validation group (n=97). The risk factors for HCC early recurrence within 1 year of curative hepatectomy were identified. Finally, a multivariate prognostic nomogram was developed and validated. RESULTS Age, tumor number, tumor capsule, portal vein tumor thrombi, pathological grade, vascular tumor emboli, activated partial thromboplastin time (APTT), and tumor size were identified as independent prognostic risk factors for HCC early recurrence within 1 year of curative hepatectomy. The area under the receiver operating characteristic (ROC) curve (AUC) was 0.806 [95% confidence interval (CI): 0.755 to 0.857; P<0.001], and no AUC/ROC statistical difference was detected between the training and validation sets. CONCLUSIONS The nomogram effectively predicted postoperative HCC recurrence within 1 year after curative hepatectomy, which may be a useful tool for the postoperative treatment or follow up for HCC patients.
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Affiliation(s)
- Wuzheng Xia
- Department of Organ Transplant, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Tianyi Peng
- Department of Hepatobiliary Surgery, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
- Shantou University Medical College, Shantou, China
| | - Renguo Guan
- Department of Hepatobiliary Surgery, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Yu Zhou
- Department of Pancreatic Surgery, Department of General Surgery, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Cong Zeng
- Department of General Practice, Hospital of South China Normal University, Guangzhou, China
| | - Ye Lin
- Department of Hepatobiliary Surgery, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Zhongshi Wu
- Department of Hepatobiliary Surgery, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Hongmei Tan
- Day Operating Room, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
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Wang M, Perucho JA, Vardhanabhuti V, Ip P, Ngan HY, Lee EY. Radiomic Features of T2-weighted Imaging and Diffusion Kurtosis Imaging in Differentiating Clinicopathological Characteristics of Cervical Carcinoma. Acad Radiol 2021; 29:1133-1140. [PMID: 34583867 DOI: 10.1016/j.acra.2021.08.018] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2021] [Revised: 07/28/2021] [Accepted: 08/12/2021] [Indexed: 01/06/2023]
Abstract
RATIONALE AND OBJECTIVES Clinicopathological characteristics including histological subtypes, tumour grades and International Federation of Gynecology and Obstetrics (FIGO) stages are crucial factors in the clinical decision for cervical carcinoma (CC). The purpose of this study was to evaluate the ability of T2-weighted imaging (T2WI) and diffusion kurtosis imaging (DKI) radiomics in differentiating clinicopathological characteristics of CC. MATERIALS AND METHODS One hundred and seventeen histologically confirmed CC patients (mean age 56.5 ± 14.0 years) with pre-treatment magnetic resonance imaging were retrospectively reviewed. DKI was acquired with 4 b-values (0-1500 s/mm2). Volumes of interest were contoured around the tumours on T2WI and DKI. Radiomic features including shape, first-order and grey-level co-occurrence matrix with wavelet transforms were extracted. Intraclass correlation coeffient between 2 radiologists was used for features reduction. Feature selection was achieved by elastic net and minimum redundancy maximum relevance. Selected features were used to build random forest (RF) models. The performances for differentiating histological subtypes, tumour grades and FIGO stages were assessed by receiver operating characteristic analysis. RESULTS Area under the curves (AUCs) for T2WI-only RF models for discriminating histological subtypes, tumour grades and FIGO stages were 0.762, 0.686, and 0.719. AUCs for DWI-only models were 0.663, 0.645, and 0.868, respectively. AUCs of the combined T2WI and DKI models were 0.823, 0.790, and 0.850, respectively. CONCLUSION T2WI and DKI radiomic features could differentiate the clinicopathological characteristics of CC. A combined model showed excellent diagnostic discrimination for histological subtypes, while a DKI-only model presented the best performance in differentiating FIGO stages.
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Granata V, Grassi R, Fusco R, Belli A, Cutolo C, Pradella S, Grazzini G, La Porta M, Brunese MC, De Muzio F, Ottaiano A, Avallone A, Izzo F, Petrillo A. Diagnostic evaluation and ablation treatments assessment in hepatocellular carcinoma. Infect Agent Cancer 2021; 16:53. [PMID: 34281580 PMCID: PMC8287696 DOI: 10.1186/s13027-021-00393-0] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2021] [Accepted: 07/06/2021] [Indexed: 02/07/2023] Open
Abstract
This article provides an overview of diagnostic evaluation and ablation treatment assessment in Hepatocellular Carcinoma (HCC). Only studies, in the English language from January 2010 to January 202, evaluating the diagnostic tools and assessment of ablative therapies in HCC patients were included. We found 173 clinical studies that satisfied the inclusion criteria.HCC may be noninvasively diagnosed by imaging findings. Multiphase contrast-enhanced imaging is necessary to assess HCC. Intravenous extracellular contrast agents are used for CT, while the agents used for MRI may be extracellular or hepatobiliary. Both gadoxetate disodium and gadobenate dimeglumine may be used in hepatobiliary phase imaging. For treatment-naive patients undergoing CT, unenhanced imaging is optional; however, it is required in the post treatment setting for CT and all MRI studies. Late arterial phase is strongly preferred over early arterial phase. The choice of modality (CT, US/CEUS or MRI) and MRI contrast agent (extracelllar or hepatobiliary) depends on patient, institutional, and regional factors. MRI allows to link morfological and functional data in the HCC evaluation. Also, Radiomics is an emerging field in the assessment of HCC patients.Postablation imaging is necessary to assess the treatment results, to monitor evolution of the ablated tissue over time, and to evaluate for complications. Post- thermal treatments, imaging should be performed at regularly scheduled intervals to assess treatment response and to evaluate for new lesions and potential complications.
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Affiliation(s)
- Vincenza Granata
- Division of Radiology, Istituto Nazionale Tumori IRCCS Fondazione Pascale - IRCCS di Napoli, Naples, Italy
| | - Roberta Grassi
- Division of Radiology, Università degli Studi della Campania Luigi Vanvitelli, Naples, Italy
- Italian Society of Medical and Interventional Radiology SIRM, SIRM Foundation, Milan, Italy
| | | | - Andrea Belli
- Division of Hepatobiliary Surgical Oncology, Istituto Nazionale Tumori IRCCS Fondazione Pascale - IRCCS di Napoli, Naples, Italy
| | - Carmen Cutolo
- Department of Medicine, Surgery and Dentistry, University of Salerno, Salerno, Italy
| | - Silvia Pradella
- Radiology Division, Azienda Ospedaliero-Universitaria Careggi, Florence, Italy
| | - Giulia Grazzini
- Radiology Division, Azienda Ospedaliero-Universitaria Careggi, Florence, Italy
| | | | - Maria Chiara Brunese
- Department of Medicine and Health Sciences "Vincenzo Tiberio", University of Molise, Campobasso, Italy
| | - Federica De Muzio
- Department of Medicine and Health Sciences "Vincenzo Tiberio", University of Molise, Campobasso, Italy
| | - Alessandro Ottaiano
- Abdominal Oncology Division, Istituto Nazionale Tumori IRCCS Fondazione Pascale - IRCCS di Napoli, Naples, Italy
| | - Antonio Avallone
- Abdominal Oncology Division, Istituto Nazionale Tumori IRCCS Fondazione Pascale - IRCCS di Napoli, Naples, Italy
| | - Francesco Izzo
- Division of Hepatobiliary Surgical Oncology, Istituto Nazionale Tumori IRCCS Fondazione Pascale - IRCCS di Napoli, Naples, Italy
| | - Antonella Petrillo
- Division of Radiology, Istituto Nazionale Tumori IRCCS Fondazione Pascale - IRCCS di Napoli, Naples, Italy
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The Role of Non-Gaussian Models of Diffusion Weighted MRI in Hepatocellular Carcinoma: A Systematic Review. J Clin Med 2021; 10:jcm10122641. [PMID: 34203995 PMCID: PMC8232758 DOI: 10.3390/jcm10122641] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2021] [Revised: 06/10/2021] [Accepted: 06/14/2021] [Indexed: 12/14/2022] Open
Abstract
The importance of Diffusion Weighted Imaging (DWI) in hepatocellular carcinoma (HCC) has been widely handled in the literature. Due to the mono-exponential model limitations, several studies recently investigated the role of non-Gaussian DWI models in HCC. However, their results are variable and inconsistent. Therefore, the aim of this systematic review is to summarize current knowledge on non-Gaussian DWI techniques in HCC. A systematic search of the literature, including PubMed, Google Scholar, MEDLINE, and ScienceDirect databases, was performed to identify original articles since 2010 that evaluated the role of non-Gaussian DWI models for HCC diagnosis, grading, response to treatment, and prognosis. Studies were grouped and summarized according to the non-Gaussian DWI models investigated. We focused on the most used non-Gaussian DWI models (Intravoxel Incoherent Motion (IVIM), Diffusion Kurtosis Imaging (DKI), and Stretched Exponential—SE). The quality of included studies was evaluated by using QUADAS-2 and QUIPS tools. Forty-three articles were included, with IVIM and DKI being the most investigated models. Although the role of non-Gaussian DWI models in clinical settings has not fully been established, our findings showed that their parameters may potentially play a role in HCC. Further studies are required to identify a standardized DWI acquisition protocol for HCC diagnosis, grading, response to treatment, and prognosis.
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