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Bastiaannet R, Lin M, Frey EC, de Jong HW. Intraprocedural C-arm dual-phase cone-beam enhancement patterns correlate with tumor absorbed dose after radioembolization. Med Phys 2024; 51:3045-3052. [PMID: 38064591 PMCID: PMC10994751 DOI: 10.1002/mp.16882] [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: 03/30/2023] [Revised: 11/17/2023] [Accepted: 11/17/2023] [Indexed: 04/05/2024] Open
Abstract
BACKGROUND Recent studies have shown a clear relationship between absorbed dose and tumor response to treatment after hepatic radioembolization. These findings help to create more personalized treatment planning and dosimetry. However, crucial to this goal is the ability to predict the dose distribution prior to treatment. The microsphere distribution is ultimately determined by (i) the hepatic vasculature and the resulting blood flow dynamics and (ii) the catheter position. PURPOSE To show that pretreatment, intra-procedural imaging of blood flow patterns, as quantified by catheter-directed intra-arterial contrast enhancement, correlate with posttreatment microsphere accumulation and, consequently, absorbed dose. MATERIALS AND METHODS Patients who participated in a clinical trial (NCT01177007) and for whom both a pretreatment dual-phase contrast-enhanced cone-beam CT (CBCT) and a posttreatment 90Y PET/CT scan were available were included in this retrospective study. Tumors and perfused volumes were manually delineated on the CBCT by an experienced radiologist. The mean, sum, and standard deviation of the voxels in each volume were recorded. The delineations were transferred to the PET-based absorbed dose maps by coregistration of the corresponding CTs. Linear multiple regression was used to correlate pretreatment CBCT enhancement to posttreatment 90Y PET/CT-based absorbed dose in each region. Leave-one-out cross-validation and Bland-Altman analyses were performed on the predicted versus measured absorbed doses. RESULTS Nine patients, with a total of 23 tumors were included. All presented with hepatocellular carcinoma (HCC). Visually, all patients had a clear correspondence between CBCT enhancement and absorbed dose. The correlation between CBCT enhancement and posttherapy absorbed tumor dose based was strong (R2 = 0.91), and moderate for the non-tumor liver tissue (R2 = 0.61). Limits of agreement were approximately ±55 Gray for tumor tissue. CONCLUSION There is a linear relationship between pretreatment blood dynamics in HCC tumors and posttreatment absorbed dose, which, if shown to be generalizable, allows for pretreatment tumor absorbed dose prediction.
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Affiliation(s)
- Remco Bastiaannet
- The Russell H Morgan Department of Radiology and Radiological Science, School of Medicine, Johns Hopkins University, Baltimore, MD, United States
- Department of Radiology and Nuclear Medicine, University Medical Center Utrecht, Utrecht, The Netherlands
- Image Sciences Institute, University Medical Center Utrecht, Utrecht, The Netherlands
| | - MingDe Lin
- Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, United States
| | - Eric C. Frey
- The Russell H Morgan Department of Radiology and Radiological Science, School of Medicine, Johns Hopkins University, Baltimore, MD, United States
| | - Hugo W.A.M. de Jong
- Department of Radiology and Nuclear Medicine, University Medical Center Utrecht, Utrecht, The Netherlands
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Roll W, Masthoff M, Köhler M, Rahbar K, Stegger L, Ventura D, Morgül H, Trebicka J, Schäfers M, Heindel W, Wildgruber M, Schindler P. Radiomics-Based Prediction Model for Outcome of Radioembolization in Metastatic Colorectal Cancer. Cardiovasc Intervent Radiol 2024; 47:462-471. [PMID: 38416178 DOI: 10.1007/s00270-024-03680-6] [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: 06/26/2023] [Accepted: 01/31/2024] [Indexed: 02/29/2024]
Abstract
PURPOSE To evaluate the benefit of a contrast-enhanced computed tomography (CT) radiomics-based model for predicting response and survival in patients with colorectal liver metastases treated with transarterial Yttrium-90 radioembolization (TARE). MATERIALS AND METHODS Fifty-one patients who underwent TARE were included in this single-center retrospective study. Response to treatment was assessed using the Response Evaluation Criteria in Solid Tumors (RECIST 1.1) at 3-month follow-up. Patients were stratified as responders (complete/partial response and stable disease, n = 24) or non-responders (progressive disease, n = 27). Radiomic features (RF) were extracted from pre-TARE CT after segmentation of the liver tumor volume. A model was built based on a radiomic signature consisting of reliable RFs that allowed classification of response using multivariate logistic regression. Patients were assigned to high- or low-risk groups for disease progression after TARE according to a cutoff defined in the model. Kaplan-Meier analysis was performed to analyze survival between high- and low-risk groups. RESULTS Two independent RF [Energy, Maximal Correlation Coefficient (MCC)], reflecting tumor heterogeneity, discriminated well between responders and non-responders. In particular, patients with higher magnitude of voxel values in an image (Energy), and texture complexity (MCC), were more likely to fail TARE. For predicting treatment response, the area under the receiver operating characteristic curve of the radiomics-based model was 0.75 (95% CI 0.48-1). The high-risk group had a shorter overall survival than the low-risk group (3.4 vs. 6.4 months, p < 0.001). CONCLUSION Our CT radiomics model may predict the response and survival outcome by quantifying tumor heterogeneity in patients treated with TARE for colorectal liver metastases.
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Affiliation(s)
- Wolfgang Roll
- Department of Nuclear Medicine, University Hospital Münster, Münster, Germany
- West German Cancer Centre (WTZ), Münster Site, Münster, Germany
| | - Max Masthoff
- Clinic for Radiology, University Hospital Münster, Albert-Schweitzer-Campus 1, 48149, Münster, Germany
- West German Cancer Centre (WTZ), Münster Site, Münster, Germany
| | - Michael Köhler
- Clinic for Radiology, University Hospital Münster, Albert-Schweitzer-Campus 1, 48149, Münster, Germany
- West German Cancer Centre (WTZ), Münster Site, Münster, Germany
| | - Kambiz Rahbar
- Department of Nuclear Medicine, University Hospital Münster, Münster, Germany
- West German Cancer Centre (WTZ), Münster Site, Münster, Germany
| | - Lars Stegger
- Department of Nuclear Medicine, University Hospital Münster, Münster, Germany
- West German Cancer Centre (WTZ), Münster Site, Münster, Germany
| | - David Ventura
- Department of Nuclear Medicine, University Hospital Münster, Münster, Germany
- West German Cancer Centre (WTZ), Münster Site, Münster, Germany
| | - Haluk Morgül
- Department for General, Visceral and Transplantation Surgery, University Hospital Münster, Münster, Germany
- West German Cancer Centre (WTZ), Münster Site, Münster, Germany
| | - Jonel Trebicka
- Department of Gastroenterology and Hepatology, University Hospital Münster, Münster, Germany
- West German Cancer Centre (WTZ), Münster Site, Münster, Germany
| | - Michael Schäfers
- Department of Nuclear Medicine, University Hospital Münster, Münster, Germany
- West German Cancer Centre (WTZ), Münster Site, Münster, Germany
| | - Walter Heindel
- Clinic for Radiology, University Hospital Münster, Albert-Schweitzer-Campus 1, 48149, Münster, Germany
- West German Cancer Centre (WTZ), Münster Site, Münster, Germany
| | - Moritz Wildgruber
- Clinic for Radiology, University Hospital Münster, Albert-Schweitzer-Campus 1, 48149, Münster, Germany
- Department of Radiology, University Hospital LMU, Munich, Munich, Germany
| | - Philipp Schindler
- Clinic for Radiology, University Hospital Münster, Albert-Schweitzer-Campus 1, 48149, Münster, Germany.
- West German Cancer Centre (WTZ), Münster Site, Münster, Germany.
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Gómez FM, Van der Reijd DJ, Panfilov IA, Baetens T, Wiese K, Haverkamp-Begemann N, Lam SW, Runge JH, Rice SL, Klompenhouwer EG, Maas M, Helmberger T, Beets-Tan RG. Imaging in interventional oncology, the better you see, the better you treat. J Med Imaging Radiat Oncol 2023; 67:895-902. [PMID: 38062853 DOI: 10.1111/1754-9485.13610] [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: 04/06/2023] [Accepted: 11/22/2023] [Indexed: 01/14/2024]
Abstract
Imaging and image processing is the fundamental pillar of interventional oncology in which diagnostic, procedure planning, treatment and follow-up are sustained. Knowing all the possibilities that the different image modalities can offer is capital to select the most appropriate and accurate guidance for interventional procedures. Despite there is a wide variability in physicians preferences and availability of the different image modalities to guide interventional procedures, it is important to recognize the advantages and limitations for each of them. In this review, we aim to provide an overview of the most frequently used image guidance modalities for interventional procedures and its typical and future applications including angiography, computed tomography (CT) and spectral CT, magnetic resonance imaging, Ultrasound and the use of hybrid systems. Finally, we resume the possible role of artificial intelligence related to image in patient selection, treatment and follow-up.
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Affiliation(s)
- Fernando M Gómez
- Grupo de Investigación Biomédica en Imagen, Instituto de Investigación Sanitaria La Fe, Valencia, Spain
- Área Clínica de Imagen Médica, Hospital Universitario y Politécnico La Fe, Valencia, Spain
- Department of Radiology, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | | | - Ilia A Panfilov
- Department of Radiology, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Tarik Baetens
- Department of Radiology, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Kevin Wiese
- Department of Radiology, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | | | - Siu W Lam
- Department of Radiology, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Jurgen H Runge
- Department of Radiology, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Samuel L Rice
- Radiology, Interventional Radiology Section, UT Southwestern Medical Center, Dallas, TX, USA
| | | | - Monique Maas
- Department of Radiology, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Thomas Helmberger
- Institut für Radiologie, Neuroradiologie und Minimal-Invasive Therapie, München Klinik Bogenhausen, Munich, Germany
| | - Regina Gh Beets-Tan
- Department of Radiology, The Netherlands Cancer Institute, Amsterdam, The Netherlands
- GROW School for Oncology and Developmental Biology, University of Maastricht, Maastricht, The Netherlands
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Garbino N, Brancato V, Salvatore M, Cavaliere C. A Systematic Review on the Role of the Perfusion Computed Tomography in Abdominal Cancer. Dose Response 2021; 19:15593258211056199. [PMID: 34880716 PMCID: PMC8647276 DOI: 10.1177/15593258211056199] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2021] [Revised: 10/06/2021] [Accepted: 10/07/2021] [Indexed: 11/17/2022] Open
Abstract
Background and purpose Perfusion Computed Tomography (CTp) is an imaging technique which allows
quantitative and qualitative evaluation of tissue perfusion through dynamic
CT acquisitions. Since CTp is still considered a research tool in the field
of abdominal imaging, the aim of this work is to provide a systematic
summary of the current literature on CTp in the abdominal region to clarify
the role of this technique for abdominal cancer applications. Materials and Methods A systematic literature search of PubMed, Web of Science, and Scopus was
performed to identify original articles involving the use of CTp for
clinical applications in abdominal cancer since 2011. Studies were included
if they reported original data on CTp and investigated the clinical
applications of CTp in abdominal cancer. Results Fifty-seven studies were finally included in the study. Most of the included
articles (33/57) dealt with CTp at the level of the liver, while a low
number of studies investigated CTp for oncologic diseases involving UGI
tract (8/57), pancreas (8/57), kidneys (3/57), and colon–rectum (5/57). Conclusions Our study revealed that CTp could be a valuable functional imaging tool in
the field of abdominal oncology, particularly as a biomarker for monitoring
the response to anti-tumoral treatment.
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Osman MF, Shawali IH, Metwally LIA, Kamel AH, Ibrahim MES. CT perfusion for response evaluation after interventional ablation of hepatocellular carcinoma: a prospective study. THE EGYPTIAN JOURNAL OF RADIOLOGY AND NUCLEAR MEDICINE 2021. [DOI: 10.1186/s43055-021-00660-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
Abstract
Background
Computed tomography (CT) perfusion was found to be useful in assessing treatment response in a variety of cancers through the evaluation in the arterial perfusion changes. We investigated the performance of CT perfusion parameters for assessment of hepatocellular carcinoma (HCC) response to radiofrequency ablation (RFA) and trans-arterial chemoembolization (TACE). We conducted a prospective diagnostic test accuracy study that recruited 70 HCC patients who were scheduled to undergo TACE or RFA. For each dynamic CT scan acquisition, four single perfusion CT image maps were generated, including functional maps of blood flow (BF), blood volume (BV), mean transit time (MTT), and permeability surface (PS).
Results
In TACE-treated lesions, the BV achieved a sensitivity and specific of 100% and 83.3%, at a cutoff level of ≤ 122 ml/min/100 gm, for responders. Likewise, at a cutoff level of > 10 s, transit time had a sensitivity of 90.5% and specificity of 100%. At a cutoff level of ≤ 14 ml/min/100 gm, the PS had a sensitivity of 100% and specificity of 83.33% for responders. In RFA-treated lesions, at a cutoff level of ≤ 170 ml/min/100 gm and ≤ 11 ml/100 gm, the BF and BV had a sensitivity of 100% and specificity 100%, respectively, for responders. At a cutoff level of ≤ 11 ml/min/100 gm, PS had a sensitivity 77.27% and specificity 80%.
Conclusions
The present study confirms the feasibility of CT perfusion for assessment of response to TACE and RFA among patients with HCC.
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Kobe A, Zgraggen J, Messmer F, Puippe G, Sartoretti T, Alkadhi H, Pfammatter T, Mannil M. Prediction of treatment response to transarterial radioembolization of liver metastases: Radiomics analysis of pre-treatment cone-beam CT: A proof of concept study. Eur J Radiol Open 2021; 8:100375. [PMID: 34485629 PMCID: PMC8408624 DOI: 10.1016/j.ejro.2021.100375] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2021] [Revised: 08/23/2021] [Accepted: 08/25/2021] [Indexed: 11/18/2022] Open
Abstract
Purpose To investigate the potential of texture analysis and machine learning to predict treatment response to transarterial radioembolization (TARE) on pre-interventional cone-beam computed tomography (CBCT) images in patients with liver metastases. Materials and Methods In this IRB-approved retrospective single-center study 36 patients with a total of 104 liver metastases (56 % male, mean age 61.1 ± 13 years) underwent CBCT prior to TARE and follow-up imaging 6 months after therapy. Treatment response was evaluated according to RECIST version 1.1 and dichotomized into disease control (partial response/stable disease) versus disease progression (progressive disease). After target lesion segmentation, 104 radiomics features corresponding to seven different feature classes were extracted with the pyRadiomics package. After dimension reduction machine learning classifications were performed on a custom artificial neural network (ANN). Ten-fold cross validation on a previously unseen test data set was performed. Results The average administered cumulative activity from TARE was 1.6 Gbq (± 0.5 Gbq). At a mean follow-up of 5.9 ± 0.8 months disease control was achieved in 82 % of metastases. After dimension reduction, 15 of 104 (15 %) texture analysis features remained for further analysis. On a previously unseen set of liver metastases the Multilayer Perceptron ANN yielded a sensitivity of 94.2 %, specificity of 67.7 % and an area-under-the receiver operating characteristics curve of 0.85. Conclusion Our study indicates that texture analysis-based machine learning may has potential to predict treatment response to TARE using pre-treatment CBCT images of patients with liver metastases with high accuracy.
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Key Words
- 90Y-microspheres, Yttrium-90-microspheres
- 99mTc-MAA, 99mtechnetium labelled macroaggregated albumin
- ANN, Artificial neural network
- CBCT, Cone-beam Computed Tomography
- CR, Complete response
- CT, Computed tomography
- Cone-Beam CT
- DICOM, Digital Imaging and Communications in Medicine
- GLCM, Gray-level co-occurrence matrix
- GLDM, Gray-level dependence matrix
- GLRLM, Gray-level run length matrix
- GLSZM, Gray-level size zone matrix
- ICC, Intraclass-correlation coefficient
- MR, Magnetic resonance
- Machine learning
- NGTDM, Neighboring gray tone difference matrix
- PD, Progressive disease
- PET, Positron emission tomography
- PR, Partial response
- Radiomics
- SD, Stable disease
- TACE, Transarterial chemoembolization
- TARE, Transarterial radioembolization
- Transarterial radioembolization
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Affiliation(s)
- Adrian Kobe
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
- Corresponding author at: Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, Rämistrasse 100, CH-8091, Zurich, Switzerland.
| | - Juliana Zgraggen
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Florian Messmer
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Gilbert Puippe
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Thomas Sartoretti
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Hatem Alkadhi
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Thomas Pfammatter
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Manoj Mannil
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
- Clinic of Radiology, University Hospital Münster, University of Münster, Münster, Germany
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Woeste MR, Geller AE, Martin RCG, Polk HC. Optimizing the Combination of Immunotherapy and Trans-Arterial Locoregional Therapy for Stages B and C Hepatocellular Cancer. Ann Surg Oncol 2021; 28:1499-1510. [PMID: 33393028 DOI: 10.1245/s10434-020-09414-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2020] [Accepted: 11/10/2020] [Indexed: 02/07/2023]
Abstract
Hepatocellular carcinoma (HCC), the most common primary hepatic malignancy worldwide, is the second leading cause of cancer-related death. Underlying liver dysfunction and advanced stage of disease require treatments to be optimally timed and implemented to minimize hepatic parenchymal damage while maximizing disease response and quality of life. Locoregional therapies (LRTs) such as trans-arterial chemo- and radio-embolization remain effective for intermediate liver-only and advanced HCC disease (i.e., Barcelona-Clinic liver cancer stages B and C) not amendable to primary resection or ablation. Additionally, these minimally invasive interventions have been shown to augment the immune system. This and the recent success of immune-oncologic treatments for HCC have generated interest in applying these therapies in combination with such locoregional interventions to improve patient outcomes and response rates. This report reviews the use of trans-arterial LRTs with immunotherapy for stages B and C HCC, potential biomarkers, and imaging methods for assessing the response and safety of such combinations.
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Affiliation(s)
- Matthew R Woeste
- Division of Surgical Oncology, Department of Surgery, University of Louisville School of Medicine, Louisville, KY, USA.,Department of Microbiology and Immunology, University of Louisville School of Medicine, Louisville, KY, USA
| | - Anne E Geller
- Division of Surgical Oncology, Department of Surgery, University of Louisville School of Medicine, Louisville, KY, USA.,Department of Microbiology and Immunology, University of Louisville School of Medicine, Louisville, KY, USA
| | - Robert C G Martin
- Division of Surgical Oncology, Department of Surgery, University of Louisville School of Medicine, Louisville, KY, USA.
| | - Hiram C Polk
- Division of Surgical Oncology, Department of Surgery, University of Louisville School of Medicine, Louisville, KY, USA
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Gregory J, Dioguardi Burgio M, Corrias G, Vilgrain V, Ronot M. Evaluation of liver tumour response by imaging. JHEP Rep 2020; 2:100100. [PMID: 32514496 PMCID: PMC7267412 DOI: 10.1016/j.jhepr.2020.100100] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/14/2020] [Revised: 03/10/2020] [Accepted: 03/10/2020] [Indexed: 12/12/2022] Open
Abstract
The goal of assessing tumour response on imaging is to identify patients who are likely to benefit - or not - from anticancer treatment, especially in relation to survival. The World Health Organization was the first to develop assessment criteria. This early score, which assessed tumour burden by standardising lesion size measurements, laid the groundwork for many of the criteria that followed. This was then improved by the Response Evaluation Criteria in Solid Tumours (RECIST) which was quickly adopted by the oncology community. At the same time, many interventional oncology treatments were developed to target specific features of liver tumours that result in significant changes in tumours but have little effect on tumour size. New criteria focusing on the viable part of tumours were therefore designed to provide more appropriate feedback to guide patient management. Targeted therapy has resulted in a breakthrough that challenges conventional response criteria due to the non-linear relationship between response and tumour size, requiring the development of methods that emphasize the appearance of tumours. More recently, research into functional and quantitative imaging has created new opportunities in liver imaging. These results have suggested that certain parameters could serve as early predictors of response or could predict later tumour response at baseline. These approaches have now been extended by machine learning and deep learning. This clinical review focuses on the progress made in the evaluation of liver tumours on imaging, discussing the rationale for this approach, addressing challenges and controversies in the field, and suggesting possible future developments.
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Key Words
- (c)TACE, (conventional) transarterial chemoembolisation
- (m)RECIST, (modified) Response Evaluation Criteria in Solid Tumours
- 18F-FDG, 18F-fluorodeoxyglucose
- 90Y, yttrium-90
- ADC, apparent diffusion coefficient
- APHE, arterial phase hyperenhancement
- CEUS, contrast-enhanced ultrasound
- CRLM, colorectal liver metastases
- DWI, diffusion-weighted imaging
- EASL
- EASL, European Association for the Study of the Liver criteria
- GIST, gastrointestinal stromal tumours
- HCC, hepatocellular carcinoma
- HU, Hounsfield unit
- Imaging
- LI-RADS
- LI-RADS, Liver Imaging Reporting And Data System
- Liver
- Metastases
- PD, progressive disease
- PET, positron emission tomography
- PR, partial response
- RECIST
- SD, stable disease
- SIRT, selective internal radiotherapy
- TR, treatment response
- Tumours
- WHO, World Health Organization
- mRECIST
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Affiliation(s)
- Jules Gregory
- Department of Radiology, APHP, University Hospitals Paris Nord Val de Seine, Beaujon, Clichy, France
- University of Paris, Paris, France
- INSERM U1149, CRI, Paris, France
| | - Marco Dioguardi Burgio
- Department of Radiology, APHP, University Hospitals Paris Nord Val de Seine, Beaujon, Clichy, France
- University of Paris, Paris, France
- INSERM U1149, CRI, Paris, France
| | - Giuseppe Corrias
- Department of Radiology, APHP, University Hospitals Paris Nord Val de Seine, Beaujon, Clichy, France
- University of Paris, Paris, France
- INSERM U1149, CRI, Paris, France
| | - Valérie Vilgrain
- Department of Radiology, APHP, University Hospitals Paris Nord Val de Seine, Beaujon, Clichy, France
- University of Paris, Paris, France
- INSERM U1149, CRI, Paris, France
| | - Maxime Ronot
- Department of Radiology, APHP, University Hospitals Paris Nord Val de Seine, Beaujon, Clichy, France
- University of Paris, Paris, France
- INSERM U1149, CRI, Paris, France
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Lauenstein TC, Schelhorn J, Kinner S. Assessment of Tumor Response with MRI and CT After Radioembolization. Clin Nucl Med 2020. [DOI: 10.1007/978-3-030-39457-8_37] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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Computed Tomography for 4-Dimensional Angiography and Perfusion Imaging of the Prostate for Embolization Planning of Benign Prostatic Hyperplasia. Invest Radiol 2019; 54:661-668. [PMID: 31211710 DOI: 10.1097/rli.0000000000000582] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
OBJECTIVES The aim of this study was to evaluate the feasibility of a computed tomography (CT) protocol enabling the visualization of the prostatic artery (PA) before prostatic artery embolization (PAE) in benign prostatic hyperplasia, which provides quantitative perfusion information of the prostate gland. MATERIALS AND METHODS In this institutional review board-approved study, 22 consecutive patients (mean age, 67 ± 7 years) who were planned to undergo PAE underwent a dynamic CT scan of the pelvis (scan range, 22.4 cm; cycle time, 1.5 seconds; scan time, 44 seconds; 25 scan cycles; 70 kVp; 100 mAs) after the administration of 70 mL of iodinated contrast media (flow rate, 6 mL/s; 10 seconds' delay). Image postprocessing consisted of a spatiotemporal, frequency-depending multiband filtering technique with noise reduction, motion correction, resulting in (1) time-resolved, temporal maximum intensity projection (MIP) images from fusion of multiple arterial time points; (2) 4-dimensional (4D) CT angiography images after bone and calcium plaque removal; and (3) parametric perfusion maps of the prostate. Intraprocedural cone-beam CT was performed with a microcatheter in the PA. In both modalities, the contrast-to-noise ratio of the right internal iliac artery or the PA was calculated, respectively. Visibility of the PA was scored using a Likert scale (score 1 = not seen, to score 4 = intraprostatic PA branches seen). Quantitative perfusion analysis of the dynamic pelvic CT included calculation of the blood flow, blood volume, mean transit time, and flow extraction product. RESULTS The average volume CT dose index and dose length product of CT was 35.7 ± 6.8 mGy and 737.4 ± 146.3 mGy·cm, respectively. Contrast-to-noise ratio of the pelvic vessels on temporal MIP images and cone-beam CT were 45 ± 19 and 69 ± 27, respectively (P < 0.01). The mean visibility score of the PA was 3.6 ± 0.6 for 4D-CT angiography and 3.97 ± 0.2 for cone-beam CT (P < 0.001). The PA was visualized in 100% of 4D-CT angiography examinations, with one PA being visible only proximally. Prostate CT perfusion analysis showed blood flow, blood volume, mean transit time, and flow extraction product values of 27.9 ± 12.5 mL/100 mL/min, 2.0 ± 0.8 mL/100 mL, 4.5 ± 0.5 second, and 12.6 ± 5.4 mL/100 mL/min, respectively, for the whole prostate gland. About half the patients showed a pronounced difference between the lobes. CONCLUSIONS We introduced a CT protocol for PAE planning providing excellent visualization of the PA on temporal MIP images and 4D-CT angiography at a reasonable dose and low contrast volume. In addition, quantitative perfusion information is available, which might be useful for outcome prediction after embolization.
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Reimer RP, Reimer P, Mahnken AH. Assessment of Therapy Response to Transarterial Radioembolization for Liver Metastases by Means of Post-treatment MRI-Based Texture Analysis. Cardiovasc Intervent Radiol 2018; 41:1545-1556. [PMID: 29881933 DOI: 10.1007/s00270-018-2004-2] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/01/2018] [Accepted: 05/28/2018] [Indexed: 12/13/2022]
Abstract
INTRODUCTION To determine whether post-treatment magnetic resonance imaging (MRI)-based texture analysis of liver metastases (LM) may be suited predicting therapy response to transarterial radioembolization (TARE) during follow-up. MATERIALS AND METHODS Thirty-seven patients with LM treated by TARE (mean age 63.4 years) between January 2006 and December 2014 were identified in this retrospective feasibility study. They underwent dynamic contrast-enhanced and hepatocellular phase MRI after TARE (mean 2.2 days). Response was evaluated on follow-up imaging scheduled in intervals of 3 months (median follow-up, 7.3 months) based on response evaluation criteria in solid tumors 1.1 (RECIST 1.1). Results of texture analysis [mean, standard deviation, skewness (s), kurtosis (k), entropy and uniformity] were compared between patients with progressive disease (PD) and patients with stable disease (SD), partial or complete response (PR/CR). Receiver operating characteristics including the area under the curve (AUC) and cutoff values including the sensitivity and specificity were calculated. RESULTS According to RECIST 1.1, 24 patients (64.9%) had PD, 8 SD (21.6%) and 5 PR (13.5%). MRI-based texture analysis showed an earlier differentiation between patients with and without PD when compared with RECIST 1.1. Median k (2.88 vs. 2.35) in arterial phase MRI and median s (0.48 vs. 0.25) and k (2.85 vs. 2.25) in venous phase MRI were significantly different (p < 0.05). The AUC for k derived from arterial phase MRI was 0.73 (cutoff = 2.55, sensitivity = 0.83, specificity = 0.62) (p < 0.05). The AUC for s and k in venous phase MRI was 0.76 (cutoff = 0.35, sensitivity = 0.71, specificity = 0.85) (p > 0.05) and 0.83 (cutoff = 2.50, sensitivity = 0.75, specificity = 0.85) (p < 0.05). CONCLUSION This study indicates the potential of MRI-based texture analysis at arterial and venous phase MRI for the early prediction of PD after TARE. LEVEL OF EVIDENCE IV.
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Affiliation(s)
- Robert P Reimer
- Department of Radiology, University of Cologne, Kerpener Straße 62, 50937, Cologne, Germany. .,Department of Diagnostic and Interventional Radiology, Marburg University Hospital, Philipps-University, Baldingerstrasse, 35043, Marburg, Germany.
| | - Peter Reimer
- Institute of Diagnostic and Interventional Radiology, Klinikum Karlsruhe, Academic Teaching Hospital of the University of Freiburg, 76133, Karlsruhe, Germany
| | - Andreas H Mahnken
- Department of Diagnostic and Interventional Radiology, Marburg University Hospital, Philipps-University, Baldingerstrasse, 35043, Marburg, Germany
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Kang HJ, Kim SH, Bae JS, Jeon SK, Han JK. Can quantitative iodine parameters on DECT replace perfusion CT parameters in colorectal cancers? Eur Radiol 2018; 28:4775-4782. [PMID: 29789907 DOI: 10.1007/s00330-018-5502-3] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2018] [Accepted: 04/18/2018] [Indexed: 01/29/2023]
Abstract
OBJECTIVES To determine the correlation between iodine concentrations derived from dual-energy CT (DECT) and perfusion CT (PCT) parameters in patients with pathologically proven colorectal cancers (CRC) and to evaluate their reproducibility and respective radiation exposures. METHODS Institutional review board approval and written informed consents were obtained for this study. Forty-one patients with CRCs who underwent same-day DECT and PCT were prospectively enrolled. Three radiologists independently analyzed the iodine concentration of the tumors and iodine ratios [ratio of lesion to aorta (IRa) or to infrarenal IVC (IRv)] from DECT as well as blood flow (BF), blood volume (BV), permeability (PMB), and mean transit time (MTT) from PCT. Pearson R and linear correlation, paired t-test, and intraclass correlation coefficients (ICCs) were used. RESULTS Significant correlations were found between iodine parameters from DECT and PCT parameters: iodine concentration of tumors and BV (r = 0.32, p = 0.04), PMB (r = 0.34, p = 0.03), and MTT (r = -0.38, p = 0.02); iodine ratio (IRa) and MTT (r = -0.32, p = 0.04); iodine ratio (IRv) and BF (r = 0.32, p = 0.04) and PMB (r = 0.44, p = <0.01). DECT showed better intra- and interobserver agreements (ICC = 0.98, 0.90 in iodine concentration; 0.98, 0.91 in IRa; and 0.91, 0.93 in IRv, respectively) than PCT (ICC = 0.90, 0.78 in BF; 0.82, 0.76 in BV; 0.75, 0.75 in PMB; 0.64, 0.79 in MTT, respectively). As for radiation dosage, CTDIvol and DLP in DECT (10.48 ± 1.84 mGy and 519.7 ± 116.7 mGy·cm) were significantly lower than those of PCT (75.76 mGy and 911 mGy·cm) (p < 0.01). CONCLUSION Iodine parameters from DECT are significantly correlated with PCT parameters, but have higher intra- and interobserver agreements and lower radiation exposure. KEY POINTS • Quantitative iodine concentrations from DECT are significantly correlated with perfusion CT parameters. • Intra- and interobserver agreements of DECT are better than those of perfusion CT. • Effective radiation doses of DECT are significantly lower than those of perfusion CT. • DECT can be used as an alternative to perfusion CT with lower radiation doses.
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Affiliation(s)
- Hyo-Jin Kang
- Department of Radiology, Seoul National University Hospital, Seoul, Korea
- Department of Radiology, Seoul National University College of Medicine, Seoul, Korea
| | - Se Hyung Kim
- Department of Radiology, Seoul National University Hospital, Seoul, Korea.
- Department of Radiology, Seoul National University College of Medicine, Seoul, Korea.
| | - Jae Seok Bae
- Department of Radiology, Seoul National University Hospital, Seoul, Korea
- Department of Radiology, Seoul National University College of Medicine, Seoul, Korea
| | - Sun Kyung Jeon
- Department of Radiology, Seoul National University Hospital, Seoul, Korea
- Department of Radiology, Seoul National University College of Medicine, Seoul, Korea
| | - Joon Koo Han
- Department of Radiology, Seoul National University Hospital, Seoul, Korea
- Department of Radiology, Seoul National University College of Medicine, Seoul, Korea
- Department of Radiology, Institute of Radiation Medicine, Seoul National University Medical Research Center, Seoul, Korea
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Popovic P, Leban A, Kregar K, Garbajs M, Dezman R, Bunc M. Computed Tomographic Perfusion Imaging for the Prediction of Response and Survival to Transarterial Chemoembolization of Hepatocellular Carcinoma. Radiol Oncol 2017. [PMID: 29520201 PMCID: PMC5839077 DOI: 10.1515/raon-2017-0052] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Abstract
Background The purpose of this retrospective cohort study was to evaluate the clinical value of computed tomographic perfusion imaging (CTPI) parameters in predicting the response to treatment and overall survival in patients with hepatocellular carcinoma (HCC) treated with drug-eluting beads transarterial chemoembolization (DEBTACE). Patients and methods Between December 2010 and January 2013 eighteen patients (17 men, 1 woman; mean age 69 ± 5.8 years) with intermediate stage HCC underwent CTPI of the liver prior to treatment with DEBTACE. Treatment response was evaluated on follow-up imaging according to modified Response Evaluation Criteria in Solid Tumors. Pre-treatment CTPI parameters were compared between patients with complete response and partial response with a Student t-test. We compared survival times with Kaplan-Meier method. Results CTPI parameters of patients with complete response and others did not show statistical significant difference. The mean survival time was 25.4 ± 3.2 months (95%; CI: 18.7-32.1). Survival was statistically significantly longer in patients with hepatic blood flow (BF) lower than 50.44 ml/100 ml/min (p = 0.033), hepatic blood volume (BV) lower than 13.32 ml/100 ml (p = 0.028) and time to peak (TTP) longer than 19.035 s (p = 0.015). Conclusions CTPI enables prediction of survival in patients with intermediate stage HCC, treated with DEBTACE based on the pre-treatment values of BF, BV and TTP perfusion parameters. CT perfusion imaging can’t be used to predict treatment response to DEBTACE.
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Affiliation(s)
- Peter Popovic
- Clinical Institute of Radiology, University Medical Centre, Ljubljana, Slovenia
| | - Ana Leban
- General Hospital Dr. Franca Derganca, Šempeter pri Gorici, Slovenia
| | | | - Manca Garbajs
- Clinical Institute of Radiology, University Medical Centre, Ljubljana, Slovenia
| | - Rok Dezman
- Clinical Institute of Radiology, University Medical Centre, Ljubljana, Slovenia
| | - Matjaz Bunc
- Department of Cardiology, University Medical Centre, Ljubljana, Slovenia
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Marquez HP, Karalli A, Haubenreisser H, Mathew RP, Alkadhi H, Brismar TB, Henzler T, Fischer MA. Computed tomography perfusion imaging for monitoring transarterial chemoembolization of hepatocellular carcinoma. Eur J Radiol 2017. [PMID: 28629564 DOI: 10.1016/j.ejrad.2017.03.014] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
PURPOSE To prospectively monitor changes in tumor perfusion of hepatocellular carcinoma (HCC) in response to doxorubicin-eluted bead based transarterial chemoembolization (DEB-TACE) using perfusion-CT (P-CT). METHODS AND MATERIALS 24 patients (54-79 years) undergoing P-CT before and shortly after DEB-TACE of HCC were prospectively included in this dual-center study. Two readers determined arterial-liver-perfusion (ALP, mL/min/100mL), portal-venous-perfusion (PLP, mL/min/100mL) and the hepatic-perfusion-index (HPI, %) by placing matched regions-of-interests within each HCC before and after DEB-TACE. Imaging follow-up was used to determine treatment response and to distinguish complete from incomplete responders. Performance of P-CT for prediction and early response assessment was determined using receiver-operating-characteristics curve analysis. RESULTS Interreader agreement was fair to excellent (ICC, 0.716-0.942). PLP before DEB-TACE was significantly higher in pre-treated vs non-treated lesions (P<0.05). Mean changes of ALP, PLP and HPI from before to after DEB-TACE were -55%, +24% and -27%. ALP and HPI after DEB-TACE were correlating with response-grades (r=0.45/0.48; both, p<0.04), showing an area-under-the-curve (AUC) of 0.74 and 0.80 respectively for identification of complete response. CONCLUSION High arterial and low portal-venous perfusion of HCC early after DEB-TACE indicates incomplete response with good diagnostic accuracy.
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Affiliation(s)
- Herman P Marquez
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich and University of Zurich, CH-8091 Zurich, Switzerland
| | - Amar Karalli
- Division of Medical Imaging and Technology, Department of Clinical Science, Intervention and Technology (CLINTEC), Karolinska Institutet, SE-14186, Stockholm, Sweden
| | - Holger Haubenreisser
- Institute of Clinical Radiology and Nuclear Medicine, University Medical Center Mannheim, Medical Faculty Mannheim, Heidelberg University, D-68167, Mannheim, Germany
| | - Rishi P Mathew
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich and University of Zurich, CH-8091 Zurich, Switzerland
| | - Hatem Alkadhi
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich and University of Zurich, CH-8091 Zurich, Switzerland
| | - Torkel B Brismar
- Division of Medical Imaging and Technology, Department of Clinical Science, Intervention and Technology (CLINTEC), Karolinska Institutet, SE-14186, Stockholm, Sweden
| | - Thomas Henzler
- Institute of Clinical Radiology and Nuclear Medicine, University Medical Center Mannheim, Medical Faculty Mannheim, Heidelberg University, D-68167, Mannheim, Germany
| | - Michael A Fischer
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich and University of Zurich, CH-8091 Zurich, Switzerland.
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Ronot M, Clift AK, Vilgrain V, Frilling A. Functional imaging in liver tumours. J Hepatol 2016; 65:1017-1030. [PMID: 27395013 DOI: 10.1016/j.jhep.2016.06.024] [Citation(s) in RCA: 41] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/29/2016] [Revised: 06/20/2016] [Accepted: 06/20/2016] [Indexed: 02/08/2023]
Abstract
Functional imaging encompasses techniques capable of assessing physiological parameters of tissues, and offers useful clinical information in addition to that obtained from morphological imaging. Such techniques may include magnetic resonance imaging with diffusion-weighted sequences or hepatobiliary contrast agents, perfusion imaging, or molecular imaging with radiolabelled tracers. The liver is of major importance in oncological practice; not only is hepatocellular carcinoma one of the malignancies with steadily rising incidence worldwide, but hepatic metastases are regularly observed with a range of solid neoplasms. Within the realm of hepatic oncology, different functional imaging modalities may occupy pivotal roles in lesion characterisation, treatment selection and follow-up, depending on tumour size and type. In this review, we characterise the major forms of functional imaging, discuss their current application to the management of patients with common primary and secondary liver tumours, and anticipate future developments within this field.
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Affiliation(s)
- Maxime Ronot
- Department of Radiology, APHP, University Hospitals Paris Nord Val de Seine, Beaujon, Clichy, Hauts-de-Seine, France; University Paris Diderot, Sorbonne Paris Cité, Paris, France; INSERM U1149, Centre de recherche biomédicale Bichat-Beaujon, CRB3, Paris, France
| | | | - Valérie Vilgrain
- Department of Radiology, APHP, University Hospitals Paris Nord Val de Seine, Beaujon, Clichy, Hauts-de-Seine, France; University Paris Diderot, Sorbonne Paris Cité, Paris, France; INSERM U1149, Centre de recherche biomédicale Bichat-Beaujon, CRB3, Paris, France.
| | - Andrea Frilling
- Department of Surgery and Cancer, Imperial College London, London, UK
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Yttrium-90 Radioembolization of Advanced, Unresectable Breast Cancer Liver Metastases-A Single-Center Experience. J Vasc Interv Radiol 2016; 27:1305-1315. [PMID: 27461588 DOI: 10.1016/j.jvir.2016.05.028] [Citation(s) in RCA: 35] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2016] [Revised: 05/21/2016] [Accepted: 05/21/2016] [Indexed: 12/30/2022] Open
Abstract
PURPOSE To determine value of transarterial radioembolization (TARE) for palliative treatment of unresectable liver-dominant breast metastases (LdBM) and to determine prognostic parameters. MATERIALS AND METHODS Records of patients undergoing TARE for progressing LdBM between June 2006 and March 2015 were retrospectively reviewed; 44 female patients (mean age 56.1 y; range, 34.9-85.3 y) underwent 69 TAREs (56 resin-based, 13 glass-based). Of 44 patients, 42 had bilobar disease. Mean administered activity was 1.35 GBq ± 0.71. Median clinical and imaging follow-up times were 121 days (range, 26-870 d; n = 42 patients) and 93 days (range, 26-2,037 d; n = 38 patients). Clinical and biochemical toxicities, imaging response (according to Response Evaluation Criteria In Solid Tumors), time to progression, and overall survival (OS) were evaluated. Data were analyzed with stratification according to clinical and procedural parameters. RESULTS Toxicities included 1 cholecystitis (grade 2) and 1 duodenal ulceration (grade 3); no grade ≥ 4 clinical toxicities were noted. Objective response rate (complete + partial response) was 28.9% (11/38); disease control rate (response + stable disease) was 71.1% (27/38). Median time to progression of treated liver lobe was 101 days (range, 30-2,037 d). During follow-up, 34/42 patients died (median OS after first TARE: 184 d [range 29-2,331 d]). On multivariate analysis, baseline Eastern Cooperative Oncology Group (ECOG) status of 0 (P < .0001, hazard ratio [HR] = 0.146) and low baseline γ-glutamyltransferase (GGT) levels (P = .0146, HR = 0.999) were predictors of longer OS. CONCLUSIONS TARE can successfully delay progression of therapy-refractory LdBM with low complication rate. Nonelevated baseline ECOG status and low GGT levels were identified as prognostic factors.
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Pieper CC, Meyer C, Sprinkart AM, Block W, Ahmadzadehfar H, Schild HH, Mürtz P, Kukuk GM. The value of intravoxel incoherent motion model-based diffusion-weighted imaging for outcome prediction in resin-based radioembolization of breast cancer liver metastases. Onco Targets Ther 2016; 9:4089-98. [PMID: 27462163 PMCID: PMC4940017 DOI: 10.2147/ott.s104770] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Abstract
Purpose To evaluate prognostic values of clinical and diffusion-weighted magnetic resonance imaging-derived intravoxel incoherent motion (IVIM) parameters in patients undergoing primary radioembolization for metastatic breast cancer liver metastases. Subjects and methods A total of 21 females (mean age 54 years, range 43–72 years) with liver-dominant metastatic breast cancer underwent standard liver magnetic resonance imaging (1.5 T, diffusion-weighted imaging with b-values of 0, 50, and 800 s/mm2) before and 4–6 weeks after radioembolization. The IVIM model-derived estimated diffusion coefficient D’ and the perfusion fraction f’ were evaluated by averaging the values of the two largest treated metastases in each patient. Kaplan–Meier and Cox regression analyses for overall survival (OS) were performed. Investigated parameters were changes in f’- and D’-values after therapy, age, sex, Eastern Cooperative Oncology Group (ECOG) status, grading of primary tumor, hepatic tumor burden, presence of extrahepatic disease, baseline bilirubin, previous bevacizumab therapy, early stasis during radioembolization, chemotherapy after radioembolization, repeated radioembolization and Response Evaluation Criteria in Solid Tumors (RECIST) response at 6-week follow-up. Results Median OS after radioembolization was 6 (range 1.5–54.9) months. In patients with therapy-induced decreasing or stable f’-values, median OS was significantly longer than in those with increased f’-values (7.6 [range 2.6–54.9] vs 2.6 [range 1.5–17.4] months, P<0.0001). Longer median OS was also seen in patients with increased D’-values (6 [range 1.6–54.9] vs 2.8 [range 1.5–17.4] months, P=0.008). Patients with remission or stable disease (responders) according to RECIST survived longer than nonresponders (7.2 [range 2.6–54.9] vs 2.6 [range 1.5–17.4] months, P<0.0001). An ECOG status ≤1 resulted in longer median OS than >1 (7.6 [range 2.6–54.9] vs 1.7 [range 1.5–4.5] months, P<0.0001). Pretreatment IVIM parameters and the other clinical characteristics were not associated with OS. Classification by f’-value changes and ECOG status remained as independent predictors of OS on multivariate analysis, while RECIST response and D’-value changes did not predict survival. Conclusion Following radioembolization of breast cancer liver metastases, early changes in the IVIM model-derived perfusion fraction f’ and baseline ECOG score were predictive of patient outcome, and may thus help to guide treatment strategy.
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Quantitative Measurements of Enhancement on Preprocedure Triphasic CT Can Predict Response of Colorectal Liver Metastases to Radioembolization. AJR Am J Roentgenol 2016; 207:671-5. [PMID: 27248430 DOI: 10.2214/ajr.15.15767] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Abstract
OBJECTIVE Colorectal liver metastases (CLM) have a variable response to radioembolization. This may be due at least partly to differences in tumor arterial perfusion. The present study examines whether quantitative measurements of enhancement on preprocedure triphasic CT can be used to predict the response of CLM to radioembolization. MATERIALS AND METHODS We retrospectively reviewed patients with CLM treated with radioembolization who underwent pretreatment PET/CT and triphasic CT examinations and posttreatment PET/CT examinations. A total of 31 consecutive patients with 60 target tumors were included in the present study. For each tumor, we calculated the hepatic artery coefficient (HAC), portal vein coefficient (PVC), and arterial enhancement fraction (AEF) based on enhancement measurements on pretreatment triphasic CT. HAC and PVC are estimates of the hepatic artery and portal vein blood supply. AEF, which is the arterial phase enhancement divided by the portal phase enhancement, provides an estimate of the hepatic artery blood supply as a fraction of the total blood supply. For each tumor, the metabolic response to radioembolization was based on findings from the initial follow-up PET/CT scan obtained at 4-8 weeks after treatment. RESULTS A total of 55% of CLM had a complete or partial metabolic response. Arterial phase enhancement, the HAC, and the PVC did not predict which tumors responded to radioembolization. However, the AEF was statistically significantly greater in tumors with a complete or partial metabolic response than in tumors with no metabolic response (i.e., those with stable disease or disease progression) (p = 0.038). An AEF of less than 0.4 was associated with a 40% response rate, whereas an AEF greater than 0.75 was associated with a 78% response rate. CONCLUSION Response to radioembolization can be predicted using the AEF calculated from the preprocedure triphasic CT.
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Pieper CC, Sprinkart AM, Meyer C, König R, Schild HH, Kukuk GM, Mürtz P. Evaluation of a Simplified Intravoxel Incoherent Motion (IVIM) Analysis of Diffusion-Weighted Imaging for Prediction of Tumor Size Changes and Imaging Response in Breast Cancer Liver Metastases Undergoing Radioembolization: A Retrospective Single Center Analysis. Medicine (Baltimore) 2016; 95:e3275. [PMID: 27057887 PMCID: PMC4998803 DOI: 10.1097/md.0000000000003275] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/08/2016] [Revised: 02/10/2016] [Accepted: 03/04/2016] [Indexed: 12/11/2022] Open
Abstract
To investigate the value of a simplified intravoxel incoherent motion (IVIM) analysis for evaluation of therapy-induced tumor changes and response of breast cancer liver metastases (mBRC) undergoing radioembolization.In 21 females (mean age 54 years, range 43-72) with mBRC tumor size changes and response evaluation criteria in solid tumors (RECIST) response to 26 primary radioembolization procedures were analyzed. Standard 1.5-T liver magnetic resonance imaging including respiratory-gated diffusion-weighted imaging (DWI) with b0 = 0 s/mm, b1 = 50 s/mm, b2 = 800 s/mm before and 6 weeks after each treatment was performed. In addition to the apparent diffusion coefficient (ADC)(0,800), the estimated diffusion coefficient D' and the perfusion fraction f' were determined using a simplified IVIM approach. For each radioembolization, the 2 largest treated metastases (if available) were analyzed. Lesions were categorized according to size changes into group A (reduction of longest diameter [LD]) and group B (LD increase) after 3 months. Radioembolization procedures were further categorized into "response" (partial response and stable disease) and "nonresponse" (progressive disease) according to RECIST after 3 months. ADC and D' are given in 10 mm/s.Forty-five metastases were analyzed. Thirty-two lesions were categorized as A; 13 as B. Before therapy, group A lesions showed significantly larger f'-values than B (P = 0.001), but ADC(0,800) and D' did not differ. After therapy, in group A lesions the ADC(0,800)- and D'-values increased and f' decreased (P < 0.0001); in contrast in group B lesions f' increased (P = 0.001). Groups could be differentiated by preinterventional f' and by changes of D' and f' between pre and postinterventional imaging (area under the curve [AUC] of 0.903, 0.747 and 1.0, respectively).Preinterventional parameters did not differ between responders and nonresponders according to RECIST. ADC(0,800)- and D'-values showed a larger increase in responders compared with nonresponders (P = 0.013 and P = 0.001, respectively). After therapy f'-values decreased significantly in responders (P = 0.001). Good to excellent prediction of long-term RECIST response was possible by therapy-induced changes in LD, D', and f' (AUC 0.903, 0.879, and 0.867, respectively).A simplified IVIM model-based analysis of early post-treatment DWI can deliver additional information on tumor size changes and long-term RECIST response after radioembolization of mBRC. The estimated perfusion fraction f' is better suited for response assessment than the conventional ADC(0,800) or D'. This can be useful to guide further treatment strategy.
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Affiliation(s)
- Claus C Pieper
- From the Department of Radiology, University of Bonn, Bonn, Germany
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Fischer MA, Brehmer K, Svensson A, Aspelin P, Brismar TB. Renal versus splenic maximum slope based perfusion CT modelling in patients with portal-hypertension. Eur Radiol 2016; 26:4030-4036. [DOI: 10.1007/s00330-016-4277-7] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2015] [Revised: 02/04/2016] [Accepted: 02/08/2016] [Indexed: 12/15/2022]
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Gordic S, Puippe GD, Krauss B, Klotz E, Desbiolles L, Lesurtel M, Müllhaupt B, Pfammatter T, Alkadhi H. Correlation between Dual-Energy and Perfusion CT in Patients with Hepatocellular Carcinoma. Radiology 2016; 280:78-87. [PMID: 26824712 DOI: 10.1148/radiol.2015151560] [Citation(s) in RCA: 54] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Purpose To develop a dual-energy contrast media-enhanced computed tomographic (CT) protocol by using time-attenuation curves from previously acquired perfusion CT data and to evaluate prospectively the relationship between iodine enhancement metrics at dual-energy CT and perfusion CT parameters in patients with hepatocellular carcinoma (HCC). Materials and Methods Institutional review board and local ethics committee approval and written informed consent were obtained. The retrospective part of this study included the development of a dual-energy CT contrast-enhanced protocol to evaluate peak arterial enhancement of HCC in the liver on the basis of time-attenuation curves from previously acquired perfusion CT data in 20 patients. The prospective part of the study consisted of an intraindividual comparison of dual-energy CT and perfusion CT data in another 20 consecutive patients with HCC. Iodine density and iodine ratio (iodine attenuation of the lesion divided by iodine attenuation in the aorta) from dual-energy CT and arterial perfusion (AP), portal venous perfusion, and total perfusion (TP) from perfusion CT were compared. Pearson R and linear correlation coefficients were calculated for AP and iodine density, AP and iodine ratio, TP and iodine density, and TP and iodine ratio. Results The dual-energy CT protocol consisted of bolus tracking in the abdominal aorta (threshold, 150 HU; scan delay, 9 seconds). The strongest intraindividual correlations in HCCs were found between iodine density and AP (r = 0.75, P = .0001). Moderate correlations were found between iodine ratio and AP (r = 0.50, P = .023) and between iodine density and TP (r = 0.56, P = .011). No further significant correlations were found. The volume CT dose index (11.4 mGy) and dose-length product (228.0 mGy · cm) of dual-energy CT was lower than those of the arterial phase of perfusion CT (36.1 mGy and 682.3 mGy · cm, respectively). Conclusion A contrast-enhanced dual-energy CT protocol developed by using time-attenuation curves from previously acquired perfusion CT data sets in patients with HCC could show good correlation between iodine density from dual-energy CT with AP from perfusion CT. (©) RSNA, 2016.
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Affiliation(s)
- Sonja Gordic
- From the Institute of Diagnostic and Interventional Radiology (S.G., G.P., T.P., H.A.), Department of Surgery, Swiss Hepato-Pancreatico-Biliary and Transplantation Center (M.L.), and Department of Hepatology and Gastroenterology (B.M.), University Hospital Zurich, University of Zurich, Raemistrasse 100, Zurich 8091, Switzerland; Computed Tomography Division, Siemens Healthcare, Forchheim, Germany (B.K., E.K.); and Division of Radiology and Nuclear Medicine, Kantonsspital St. Gallen, St. Gallen, Switzerland (L.D.)
| | - Gilbert D Puippe
- From the Institute of Diagnostic and Interventional Radiology (S.G., G.P., T.P., H.A.), Department of Surgery, Swiss Hepato-Pancreatico-Biliary and Transplantation Center (M.L.), and Department of Hepatology and Gastroenterology (B.M.), University Hospital Zurich, University of Zurich, Raemistrasse 100, Zurich 8091, Switzerland; Computed Tomography Division, Siemens Healthcare, Forchheim, Germany (B.K., E.K.); and Division of Radiology and Nuclear Medicine, Kantonsspital St. Gallen, St. Gallen, Switzerland (L.D.)
| | - Bernhard Krauss
- From the Institute of Diagnostic and Interventional Radiology (S.G., G.P., T.P., H.A.), Department of Surgery, Swiss Hepato-Pancreatico-Biliary and Transplantation Center (M.L.), and Department of Hepatology and Gastroenterology (B.M.), University Hospital Zurich, University of Zurich, Raemistrasse 100, Zurich 8091, Switzerland; Computed Tomography Division, Siemens Healthcare, Forchheim, Germany (B.K., E.K.); and Division of Radiology and Nuclear Medicine, Kantonsspital St. Gallen, St. Gallen, Switzerland (L.D.)
| | - Ernst Klotz
- From the Institute of Diagnostic and Interventional Radiology (S.G., G.P., T.P., H.A.), Department of Surgery, Swiss Hepato-Pancreatico-Biliary and Transplantation Center (M.L.), and Department of Hepatology and Gastroenterology (B.M.), University Hospital Zurich, University of Zurich, Raemistrasse 100, Zurich 8091, Switzerland; Computed Tomography Division, Siemens Healthcare, Forchheim, Germany (B.K., E.K.); and Division of Radiology and Nuclear Medicine, Kantonsspital St. Gallen, St. Gallen, Switzerland (L.D.)
| | - Lotus Desbiolles
- From the Institute of Diagnostic and Interventional Radiology (S.G., G.P., T.P., H.A.), Department of Surgery, Swiss Hepato-Pancreatico-Biliary and Transplantation Center (M.L.), and Department of Hepatology and Gastroenterology (B.M.), University Hospital Zurich, University of Zurich, Raemistrasse 100, Zurich 8091, Switzerland; Computed Tomography Division, Siemens Healthcare, Forchheim, Germany (B.K., E.K.); and Division of Radiology and Nuclear Medicine, Kantonsspital St. Gallen, St. Gallen, Switzerland (L.D.)
| | - Mickaël Lesurtel
- From the Institute of Diagnostic and Interventional Radiology (S.G., G.P., T.P., H.A.), Department of Surgery, Swiss Hepato-Pancreatico-Biliary and Transplantation Center (M.L.), and Department of Hepatology and Gastroenterology (B.M.), University Hospital Zurich, University of Zurich, Raemistrasse 100, Zurich 8091, Switzerland; Computed Tomography Division, Siemens Healthcare, Forchheim, Germany (B.K., E.K.); and Division of Radiology and Nuclear Medicine, Kantonsspital St. Gallen, St. Gallen, Switzerland (L.D.)
| | - Beat Müllhaupt
- From the Institute of Diagnostic and Interventional Radiology (S.G., G.P., T.P., H.A.), Department of Surgery, Swiss Hepato-Pancreatico-Biliary and Transplantation Center (M.L.), and Department of Hepatology and Gastroenterology (B.M.), University Hospital Zurich, University of Zurich, Raemistrasse 100, Zurich 8091, Switzerland; Computed Tomography Division, Siemens Healthcare, Forchheim, Germany (B.K., E.K.); and Division of Radiology and Nuclear Medicine, Kantonsspital St. Gallen, St. Gallen, Switzerland (L.D.)
| | - Thomas Pfammatter
- From the Institute of Diagnostic and Interventional Radiology (S.G., G.P., T.P., H.A.), Department of Surgery, Swiss Hepato-Pancreatico-Biliary and Transplantation Center (M.L.), and Department of Hepatology and Gastroenterology (B.M.), University Hospital Zurich, University of Zurich, Raemistrasse 100, Zurich 8091, Switzerland; Computed Tomography Division, Siemens Healthcare, Forchheim, Germany (B.K., E.K.); and Division of Radiology and Nuclear Medicine, Kantonsspital St. Gallen, St. Gallen, Switzerland (L.D.)
| | - Hatem Alkadhi
- From the Institute of Diagnostic and Interventional Radiology (S.G., G.P., T.P., H.A.), Department of Surgery, Swiss Hepato-Pancreatico-Biliary and Transplantation Center (M.L.), and Department of Hepatology and Gastroenterology (B.M.), University Hospital Zurich, University of Zurich, Raemistrasse 100, Zurich 8091, Switzerland; Computed Tomography Division, Siemens Healthcare, Forchheim, Germany (B.K., E.K.); and Division of Radiology and Nuclear Medicine, Kantonsspital St. Gallen, St. Gallen, Switzerland (L.D.)
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Kennedy AS, Ball DS, Cohen SJ, Cohn M, Coldwell DM, Drooz A, Ehrenwald E, Kanani S, Nutting CW, Moeslein FM, Putnam SG, Rose SC, Savin MA, Schirm S, Sharma NK, Wang EA. Hepatic imaging response to radioembolization with yttrium-90-labeled resin microspheres for tumor progression during systemic chemotherapy in patients with colorectal liver metastases. J Gastrointest Oncol 2015; 6:594-604. [PMID: 26697190 DOI: 10.3978/j.issn.2078-6891.2015.082] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/27/2022] Open
Abstract
BACKGROUND To assess response and the impact of imaging artifacts following radioembolization with yttrium-90-labeled resin microspheres ((90)Y-RE) based on the findings from a central independent review of patients with liver-dominant metastatic colorectal cancer (mCRC). METHODS Patients with mCRC who received (90)Y-RE (SIR-Spheres(®); Sirtex Medical, Sydney, Australia) at nine US institutions between July 2002 and December 2011 were included in the analysis. Tumor response was assessed at baseline and 3 months using either the Response Evaluation Criteria in Solid Tumors (RECIST) version 1.0 or 1.1. For each lesion, known artifacts affecting the interpretation of response (peri-tumoral edema and necrosis) were documented. Survivals (Kaplan-Meier analyses) were compared in responders [partial response (PR)] and non-responders [stable (SD) or progressive disease (PD)]. RESULTS Overall, 195 patients (mean age 62 years) received (90)Y-RE after a median of 2 (range, 1-6) lines of prior chemotherapy. Using RECIST 1.0 and RECIST 1.1, 7.6% and 6.9% of patients were partial responders, 47.3% and 48.1% had SD, and 55.0% and 55.0% PD, respectively. RECIST 1.0 and RECIST 1.1 showed excellent agreement {Kappa =0.915 [95% confidence interval (CI): 0.856-0.975]}. Peri-tumoral edema was documented in 32.8%, necrosis in 48.1% and both in 57.3% of cases (using RECIST 1.0). Although baseline characteristics were similar in responders and non-responders (P>0.05), responders survived significantly longer in an analysis according to RECIST 1.0: PR median (95% CI) 25.2 (range, 9.2-49.4) months vs. SD 15.8 (range, 9.3-21.1) months vs. PD 7.1 (range, 6.0-9.5) months (P<0.0001). CONCLUSIONS RECIST 1.0 and RECIST 1.1 imaging responses provide equivalent interpretations in the assessment of hepatic tumors following (90)Y-RE. Radiologic lesion responses at 3 months must be interpreted with caution due to the significant proportion of patients with peri-tumoral edema and necrosis, which may lead to an under-estimation of PR/SD. Nevertheless, 3-month radiologic responses were predictive of prolonged survival.
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Affiliation(s)
- Andrew S Kennedy
- 1 Cancer Centers of North Carolina, Cary, NC, USA ; 2 Sarah Cannon Research Institute, Nashville, TN, USA ; 3 Fox Chase Cancer Center, Philadelphia, PA, USA ; 4 Radiology Associates of Hollywood, Pembroke Pines, FL, USA ; 5 James Graham Brown Cancer Center, University of Louisville, Louisville, KY, USA ; 6 Fairfax Radiological Consultants, Fairfax, VA, USA ; 7 Abbot Northwestern Hospital, Minneapolis, MN, USA ; 8 Inova Fairfax Hospital, Annandale, VA, USA ; 9 Radiology Imaging Associates, Englewood, CO, USA ; 10 University of Maryland Medical Center, Baltimore, MD, USA ; 11 University of California, San Diego Health Sciences, San Diego, CA, USA ; 12 Oakland University William Beaumont School of Medicine, Royal Oak, MI, USA ; 13 University of Maryland School of Medicine, Baltimore, MD, USA ; 14 Charlotte Radiology, Charlotte, NC, USA
| | - David S Ball
- 1 Cancer Centers of North Carolina, Cary, NC, USA ; 2 Sarah Cannon Research Institute, Nashville, TN, USA ; 3 Fox Chase Cancer Center, Philadelphia, PA, USA ; 4 Radiology Associates of Hollywood, Pembroke Pines, FL, USA ; 5 James Graham Brown Cancer Center, University of Louisville, Louisville, KY, USA ; 6 Fairfax Radiological Consultants, Fairfax, VA, USA ; 7 Abbot Northwestern Hospital, Minneapolis, MN, USA ; 8 Inova Fairfax Hospital, Annandale, VA, USA ; 9 Radiology Imaging Associates, Englewood, CO, USA ; 10 University of Maryland Medical Center, Baltimore, MD, USA ; 11 University of California, San Diego Health Sciences, San Diego, CA, USA ; 12 Oakland University William Beaumont School of Medicine, Royal Oak, MI, USA ; 13 University of Maryland School of Medicine, Baltimore, MD, USA ; 14 Charlotte Radiology, Charlotte, NC, USA
| | - Steven J Cohen
- 1 Cancer Centers of North Carolina, Cary, NC, USA ; 2 Sarah Cannon Research Institute, Nashville, TN, USA ; 3 Fox Chase Cancer Center, Philadelphia, PA, USA ; 4 Radiology Associates of Hollywood, Pembroke Pines, FL, USA ; 5 James Graham Brown Cancer Center, University of Louisville, Louisville, KY, USA ; 6 Fairfax Radiological Consultants, Fairfax, VA, USA ; 7 Abbot Northwestern Hospital, Minneapolis, MN, USA ; 8 Inova Fairfax Hospital, Annandale, VA, USA ; 9 Radiology Imaging Associates, Englewood, CO, USA ; 10 University of Maryland Medical Center, Baltimore, MD, USA ; 11 University of California, San Diego Health Sciences, San Diego, CA, USA ; 12 Oakland University William Beaumont School of Medicine, Royal Oak, MI, USA ; 13 University of Maryland School of Medicine, Baltimore, MD, USA ; 14 Charlotte Radiology, Charlotte, NC, USA
| | - Michael Cohn
- 1 Cancer Centers of North Carolina, Cary, NC, USA ; 2 Sarah Cannon Research Institute, Nashville, TN, USA ; 3 Fox Chase Cancer Center, Philadelphia, PA, USA ; 4 Radiology Associates of Hollywood, Pembroke Pines, FL, USA ; 5 James Graham Brown Cancer Center, University of Louisville, Louisville, KY, USA ; 6 Fairfax Radiological Consultants, Fairfax, VA, USA ; 7 Abbot Northwestern Hospital, Minneapolis, MN, USA ; 8 Inova Fairfax Hospital, Annandale, VA, USA ; 9 Radiology Imaging Associates, Englewood, CO, USA ; 10 University of Maryland Medical Center, Baltimore, MD, USA ; 11 University of California, San Diego Health Sciences, San Diego, CA, USA ; 12 Oakland University William Beaumont School of Medicine, Royal Oak, MI, USA ; 13 University of Maryland School of Medicine, Baltimore, MD, USA ; 14 Charlotte Radiology, Charlotte, NC, USA
| | - Douglas M Coldwell
- 1 Cancer Centers of North Carolina, Cary, NC, USA ; 2 Sarah Cannon Research Institute, Nashville, TN, USA ; 3 Fox Chase Cancer Center, Philadelphia, PA, USA ; 4 Radiology Associates of Hollywood, Pembroke Pines, FL, USA ; 5 James Graham Brown Cancer Center, University of Louisville, Louisville, KY, USA ; 6 Fairfax Radiological Consultants, Fairfax, VA, USA ; 7 Abbot Northwestern Hospital, Minneapolis, MN, USA ; 8 Inova Fairfax Hospital, Annandale, VA, USA ; 9 Radiology Imaging Associates, Englewood, CO, USA ; 10 University of Maryland Medical Center, Baltimore, MD, USA ; 11 University of California, San Diego Health Sciences, San Diego, CA, USA ; 12 Oakland University William Beaumont School of Medicine, Royal Oak, MI, USA ; 13 University of Maryland School of Medicine, Baltimore, MD, USA ; 14 Charlotte Radiology, Charlotte, NC, USA
| | - Alain Drooz
- 1 Cancer Centers of North Carolina, Cary, NC, USA ; 2 Sarah Cannon Research Institute, Nashville, TN, USA ; 3 Fox Chase Cancer Center, Philadelphia, PA, USA ; 4 Radiology Associates of Hollywood, Pembroke Pines, FL, USA ; 5 James Graham Brown Cancer Center, University of Louisville, Louisville, KY, USA ; 6 Fairfax Radiological Consultants, Fairfax, VA, USA ; 7 Abbot Northwestern Hospital, Minneapolis, MN, USA ; 8 Inova Fairfax Hospital, Annandale, VA, USA ; 9 Radiology Imaging Associates, Englewood, CO, USA ; 10 University of Maryland Medical Center, Baltimore, MD, USA ; 11 University of California, San Diego Health Sciences, San Diego, CA, USA ; 12 Oakland University William Beaumont School of Medicine, Royal Oak, MI, USA ; 13 University of Maryland School of Medicine, Baltimore, MD, USA ; 14 Charlotte Radiology, Charlotte, NC, USA
| | - Eduardo Ehrenwald
- 1 Cancer Centers of North Carolina, Cary, NC, USA ; 2 Sarah Cannon Research Institute, Nashville, TN, USA ; 3 Fox Chase Cancer Center, Philadelphia, PA, USA ; 4 Radiology Associates of Hollywood, Pembroke Pines, FL, USA ; 5 James Graham Brown Cancer Center, University of Louisville, Louisville, KY, USA ; 6 Fairfax Radiological Consultants, Fairfax, VA, USA ; 7 Abbot Northwestern Hospital, Minneapolis, MN, USA ; 8 Inova Fairfax Hospital, Annandale, VA, USA ; 9 Radiology Imaging Associates, Englewood, CO, USA ; 10 University of Maryland Medical Center, Baltimore, MD, USA ; 11 University of California, San Diego Health Sciences, San Diego, CA, USA ; 12 Oakland University William Beaumont School of Medicine, Royal Oak, MI, USA ; 13 University of Maryland School of Medicine, Baltimore, MD, USA ; 14 Charlotte Radiology, Charlotte, NC, USA
| | - Samir Kanani
- 1 Cancer Centers of North Carolina, Cary, NC, USA ; 2 Sarah Cannon Research Institute, Nashville, TN, USA ; 3 Fox Chase Cancer Center, Philadelphia, PA, USA ; 4 Radiology Associates of Hollywood, Pembroke Pines, FL, USA ; 5 James Graham Brown Cancer Center, University of Louisville, Louisville, KY, USA ; 6 Fairfax Radiological Consultants, Fairfax, VA, USA ; 7 Abbot Northwestern Hospital, Minneapolis, MN, USA ; 8 Inova Fairfax Hospital, Annandale, VA, USA ; 9 Radiology Imaging Associates, Englewood, CO, USA ; 10 University of Maryland Medical Center, Baltimore, MD, USA ; 11 University of California, San Diego Health Sciences, San Diego, CA, USA ; 12 Oakland University William Beaumont School of Medicine, Royal Oak, MI, USA ; 13 University of Maryland School of Medicine, Baltimore, MD, USA ; 14 Charlotte Radiology, Charlotte, NC, USA
| | - Charles W Nutting
- 1 Cancer Centers of North Carolina, Cary, NC, USA ; 2 Sarah Cannon Research Institute, Nashville, TN, USA ; 3 Fox Chase Cancer Center, Philadelphia, PA, USA ; 4 Radiology Associates of Hollywood, Pembroke Pines, FL, USA ; 5 James Graham Brown Cancer Center, University of Louisville, Louisville, KY, USA ; 6 Fairfax Radiological Consultants, Fairfax, VA, USA ; 7 Abbot Northwestern Hospital, Minneapolis, MN, USA ; 8 Inova Fairfax Hospital, Annandale, VA, USA ; 9 Radiology Imaging Associates, Englewood, CO, USA ; 10 University of Maryland Medical Center, Baltimore, MD, USA ; 11 University of California, San Diego Health Sciences, San Diego, CA, USA ; 12 Oakland University William Beaumont School of Medicine, Royal Oak, MI, USA ; 13 University of Maryland School of Medicine, Baltimore, MD, USA ; 14 Charlotte Radiology, Charlotte, NC, USA
| | - Fred M Moeslein
- 1 Cancer Centers of North Carolina, Cary, NC, USA ; 2 Sarah Cannon Research Institute, Nashville, TN, USA ; 3 Fox Chase Cancer Center, Philadelphia, PA, USA ; 4 Radiology Associates of Hollywood, Pembroke Pines, FL, USA ; 5 James Graham Brown Cancer Center, University of Louisville, Louisville, KY, USA ; 6 Fairfax Radiological Consultants, Fairfax, VA, USA ; 7 Abbot Northwestern Hospital, Minneapolis, MN, USA ; 8 Inova Fairfax Hospital, Annandale, VA, USA ; 9 Radiology Imaging Associates, Englewood, CO, USA ; 10 University of Maryland Medical Center, Baltimore, MD, USA ; 11 University of California, San Diego Health Sciences, San Diego, CA, USA ; 12 Oakland University William Beaumont School of Medicine, Royal Oak, MI, USA ; 13 University of Maryland School of Medicine, Baltimore, MD, USA ; 14 Charlotte Radiology, Charlotte, NC, USA
| | - Samuel G Putnam
- 1 Cancer Centers of North Carolina, Cary, NC, USA ; 2 Sarah Cannon Research Institute, Nashville, TN, USA ; 3 Fox Chase Cancer Center, Philadelphia, PA, USA ; 4 Radiology Associates of Hollywood, Pembroke Pines, FL, USA ; 5 James Graham Brown Cancer Center, University of Louisville, Louisville, KY, USA ; 6 Fairfax Radiological Consultants, Fairfax, VA, USA ; 7 Abbot Northwestern Hospital, Minneapolis, MN, USA ; 8 Inova Fairfax Hospital, Annandale, VA, USA ; 9 Radiology Imaging Associates, Englewood, CO, USA ; 10 University of Maryland Medical Center, Baltimore, MD, USA ; 11 University of California, San Diego Health Sciences, San Diego, CA, USA ; 12 Oakland University William Beaumont School of Medicine, Royal Oak, MI, USA ; 13 University of Maryland School of Medicine, Baltimore, MD, USA ; 14 Charlotte Radiology, Charlotte, NC, USA
| | - Steven C Rose
- 1 Cancer Centers of North Carolina, Cary, NC, USA ; 2 Sarah Cannon Research Institute, Nashville, TN, USA ; 3 Fox Chase Cancer Center, Philadelphia, PA, USA ; 4 Radiology Associates of Hollywood, Pembroke Pines, FL, USA ; 5 James Graham Brown Cancer Center, University of Louisville, Louisville, KY, USA ; 6 Fairfax Radiological Consultants, Fairfax, VA, USA ; 7 Abbot Northwestern Hospital, Minneapolis, MN, USA ; 8 Inova Fairfax Hospital, Annandale, VA, USA ; 9 Radiology Imaging Associates, Englewood, CO, USA ; 10 University of Maryland Medical Center, Baltimore, MD, USA ; 11 University of California, San Diego Health Sciences, San Diego, CA, USA ; 12 Oakland University William Beaumont School of Medicine, Royal Oak, MI, USA ; 13 University of Maryland School of Medicine, Baltimore, MD, USA ; 14 Charlotte Radiology, Charlotte, NC, USA
| | - Michael A Savin
- 1 Cancer Centers of North Carolina, Cary, NC, USA ; 2 Sarah Cannon Research Institute, Nashville, TN, USA ; 3 Fox Chase Cancer Center, Philadelphia, PA, USA ; 4 Radiology Associates of Hollywood, Pembroke Pines, FL, USA ; 5 James Graham Brown Cancer Center, University of Louisville, Louisville, KY, USA ; 6 Fairfax Radiological Consultants, Fairfax, VA, USA ; 7 Abbot Northwestern Hospital, Minneapolis, MN, USA ; 8 Inova Fairfax Hospital, Annandale, VA, USA ; 9 Radiology Imaging Associates, Englewood, CO, USA ; 10 University of Maryland Medical Center, Baltimore, MD, USA ; 11 University of California, San Diego Health Sciences, San Diego, CA, USA ; 12 Oakland University William Beaumont School of Medicine, Royal Oak, MI, USA ; 13 University of Maryland School of Medicine, Baltimore, MD, USA ; 14 Charlotte Radiology, Charlotte, NC, USA
| | - Sabine Schirm
- 1 Cancer Centers of North Carolina, Cary, NC, USA ; 2 Sarah Cannon Research Institute, Nashville, TN, USA ; 3 Fox Chase Cancer Center, Philadelphia, PA, USA ; 4 Radiology Associates of Hollywood, Pembroke Pines, FL, USA ; 5 James Graham Brown Cancer Center, University of Louisville, Louisville, KY, USA ; 6 Fairfax Radiological Consultants, Fairfax, VA, USA ; 7 Abbot Northwestern Hospital, Minneapolis, MN, USA ; 8 Inova Fairfax Hospital, Annandale, VA, USA ; 9 Radiology Imaging Associates, Englewood, CO, USA ; 10 University of Maryland Medical Center, Baltimore, MD, USA ; 11 University of California, San Diego Health Sciences, San Diego, CA, USA ; 12 Oakland University William Beaumont School of Medicine, Royal Oak, MI, USA ; 13 University of Maryland School of Medicine, Baltimore, MD, USA ; 14 Charlotte Radiology, Charlotte, NC, USA
| | - Navesh K Sharma
- 1 Cancer Centers of North Carolina, Cary, NC, USA ; 2 Sarah Cannon Research Institute, Nashville, TN, USA ; 3 Fox Chase Cancer Center, Philadelphia, PA, USA ; 4 Radiology Associates of Hollywood, Pembroke Pines, FL, USA ; 5 James Graham Brown Cancer Center, University of Louisville, Louisville, KY, USA ; 6 Fairfax Radiological Consultants, Fairfax, VA, USA ; 7 Abbot Northwestern Hospital, Minneapolis, MN, USA ; 8 Inova Fairfax Hospital, Annandale, VA, USA ; 9 Radiology Imaging Associates, Englewood, CO, USA ; 10 University of Maryland Medical Center, Baltimore, MD, USA ; 11 University of California, San Diego Health Sciences, San Diego, CA, USA ; 12 Oakland University William Beaumont School of Medicine, Royal Oak, MI, USA ; 13 University of Maryland School of Medicine, Baltimore, MD, USA ; 14 Charlotte Radiology, Charlotte, NC, USA
| | - Eric A Wang
- 1 Cancer Centers of North Carolina, Cary, NC, USA ; 2 Sarah Cannon Research Institute, Nashville, TN, USA ; 3 Fox Chase Cancer Center, Philadelphia, PA, USA ; 4 Radiology Associates of Hollywood, Pembroke Pines, FL, USA ; 5 James Graham Brown Cancer Center, University of Louisville, Louisville, KY, USA ; 6 Fairfax Radiological Consultants, Fairfax, VA, USA ; 7 Abbot Northwestern Hospital, Minneapolis, MN, USA ; 8 Inova Fairfax Hospital, Annandale, VA, USA ; 9 Radiology Imaging Associates, Englewood, CO, USA ; 10 University of Maryland Medical Center, Baltimore, MD, USA ; 11 University of California, San Diego Health Sciences, San Diego, CA, USA ; 12 Oakland University William Beaumont School of Medicine, Royal Oak, MI, USA ; 13 University of Maryland School of Medicine, Baltimore, MD, USA ; 14 Charlotte Radiology, Charlotte, NC, USA
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Assessment of bronchial and pulmonary blood supply in non-small cell lung cancer subtypes using computed tomography perfusion. Invest Radiol 2015; 50:179-86. [PMID: 25500892 DOI: 10.1097/rli.0000000000000124] [Citation(s) in RCA: 34] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
OBJECTIVES The aim of this study was to investigate the dual blood supply of non-small cell lung cancer (NSCLC) and its association with tumor subtype, size, and stage, using computed tomography perfusion (CTP). MATERIALS AND METHODS A total of 54 patients (median age, 65 years; range, 42-79 years; 15 women, 39 men) with suspected lung cancer underwent a CTP scan of the lung tumor. Pulmonary and bronchial vasculature regions of interest were used to calculate independently CTP parameters (blood flow [BF], blood volume [BV], and mean transit time [MTT]) of the tumor tissue. The mean and maximum pulmonary and bronchial perfusion indexes (PImean and PImax) were calculated. The tumoral volume and the largest tumoral diameter were assessed. Differences in CTP parameters and indexes among NSCLC subtypes, tumor stages and tumor dimensions were analyzed using non-parametric tests. RESULTS According to biopsy, 37 patients had NSCLC (22 adenocarcinomas [ACs], 8 squamous cell carcinomas [SCCs], 7 large-cell carcinomas [LCC]). The mean bronchial BF/pulmonary BF, bronchial BV/pulmonary BV, and bronchial MTT/pulmonary MTT was 41.2 ± 30.0/36.9 ± 24.2 mL/100 mL/min, 11.4 ± 9.7/10.4 ± 9.4 mL/100 mL, and 11.4 ± 4.3/14.9 ± 4.4 seconds, respectively. In general, higher bronchial BF than pulmonary BF was observed in NSCLC (P = 0.014). Using a tumoral volume cutoff of 3.5 cm, a significant difference in pulmonary PImax was found (P = 0.028). There was a significantly higher mean pulmonary BF in LCCs and SCCs compared with ACs (P = 0.018 and P = 0.044, respectively), whereas the mean bronchial BF was only significantly higher in LCCs compared with ACs (P = 0.024). Correspondingly, the PImax was significantly higher in LCCs and SCCs than in ACs (P = 0.001 for both). Differences between bronchial and pulmonary PImean and PImax among T stages and Union Internationale Contre le Cancer stages were not statistically significant (P values ranging from 0.691 to 0.753). CONCLUSIONS The known dual blood supply of NSCLC, which depends on tumor size and histological subtype, is reflected in CTP parameters, with parameters depending both on tumor size and histological subtype. This has to be accounted for when analyzing NSCLC with CTP.
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Histogram Analysis of CT Perfusion of Hepatocellular Carcinoma for Predicting Response to Transarterial Radioembolization: Value of Tumor Heterogeneity Assessment. Cardiovasc Intervent Radiol 2015. [PMID: 26216725 DOI: 10.1007/s00270-015-1185-1] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/02/2023]
Abstract
PURPOSE To evaluate in patients with hepatocellular carcinoma (HCC), whether assessment of tumor heterogeneity by histogram analysis of computed tomography (CT) perfusion helps predicting response to transarterial radioembolization (TARE). MATERIALS AND METHODS Sixteen patients (15 male; mean age 65 years; age range 47-80 years) with HCC underwent CT liver perfusion for treatment planning prior to TARE with Yttrium-90 microspheres. Arterial perfusion (AP) derived from CT perfusion was measured in the entire tumor volume, and heterogeneity was analyzed voxel-wise by histogram analysis. Response to TARE was evaluated on follow-up imaging (median follow-up, 129 days) based on modified Response Evaluation Criteria in Solid Tumors (mRECIST). Results of histogram analysis and mean AP values of the tumor were compared between responders and non-responders. Receiver operating characteristics were calculated to determine the parameters' ability to discriminate responders from non-responders. RESULTS According to mRECIST, 8 patients (50%) were responders and 8 (50%) non-responders. Comparing responders and non-responders, the 50th and 75th percentile of AP derived from histogram analysis was significantly different [AP 43.8/54.3 vs. 27.6/34.3 mL min(-1) 100 mL(-1)); p < 0.05], while the mean AP of HCCs (43.5 vs. 27.9 mL min(-1) 100 mL(-1); p > 0.05) was not. Further heterogeneity parameters from histogram analysis (skewness, coefficient of variation, and 25th percentile) did not differ between responders and non-responders (p > 0.05). If the cut-off for the 75th percentile was set to an AP of 37.5 mL min(-1) 100 mL(-1), therapy response could be predicted with a sensitivity of 88% (7/8) and specificity of 75% (6/8). CONCLUSION Voxel-wise histogram analysis of pretreatment CT perfusion indicating tumor heterogeneity of HCC improves the pretreatment prediction of response to TARE.
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Lv WF, Han JK, Cheng DL, Zhou CZ, Ni M, Lu D. CT Perfusion Imaging Can Predict Patients' Survival and Early Response to Transarterial Chemo-Lipiodol Infusion for Liver Metastases from Colorectal Cancers. Korean J Radiol 2015; 16:810-20. [PMID: 26175580 PMCID: PMC4499545 DOI: 10.3348/kjr.2015.16.4.810] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2014] [Accepted: 05/13/2015] [Indexed: 02/06/2023] Open
Abstract
Objective To prospectively evaluate the performance of computed tomography perfusion imaging (CTPI) in predicting the early response to transarterial chemo-lipiodol infusion (TACLI) and survival of patients with colorectal cancer liver metastases (CRLM). Materials and Methods Computed tomography perfusion imaging was performed before and 1 month after TACLI in 61 consecutive patients. Therapeutic response was evaluated on CT scans 1 month and 4 months after TACLI; the patients were classified as responders and non-responders based on 4-month CT scans after TACLI. The percentage change of CTPI parameters of target lesions were compared between responders and non-responders at 1 month after TACLI. The optimal parameter and cutoff value were determined. The patients were divided into 2 subgroups according to the cutoff value. The log-rank test was used to compare the survival rates of the 2 subgroups. Results Four-month images were obtained from 58 patients, of which 39.7% were responders and 60.3% were non-responders. The percentage change in hepatic arterial perfusion (HAP) 1 month after TACLI was the optimal predicting parameter (p = 0.003). The best cut-off value was -21.5% and patients who exhibited a ≥ 21.5% decrease in HAP had a significantly higher overall survival rate than those who exhibited a < 21.5% decrease (p < 0.001). Conclusion Computed tomography perfusion imaging can predict the early response to TACLI and survival of patients with CRLM. The percentage change in HAP after TACLI with a cutoff value of -21.5% is the optimal predictor.
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Affiliation(s)
- Wei-Fu Lv
- PET/CT Center, Qilu Hospital, First Affiliated Hospital of Shandong University, Jinan 250012, China. ; Department of Radiology, Affiliated Anhui Provincial Hospital of Anhui Medical University, Hefei 230001, China
| | - Jian-Kui Han
- PET/CT Center, Qilu Hospital, First Affiliated Hospital of Shandong University, Jinan 250012, China
| | - De-Lei Cheng
- Department of Radiology, Affiliated Anhui Provincial Hospital of Anhui Medical University, Hefei 230001, China
| | - Chun-Ze Zhou
- Department of Radiology, Affiliated Anhui Provincial Hospital of Anhui Medical University, Hefei 230001, China
| | - Ming Ni
- Department of Radiology, Affiliated Anhui Provincial Hospital of Anhui Medical University, Hefei 230001, China
| | - Dong Lu
- Department of Radiology, Affiliated Anhui Provincial Hospital of Anhui Medical University, Hefei 230001, China
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Liver Computed Tomographic Perfusion in the Assessment of Microvascular Invasion in Patients With Small Hepatocellular Carcinoma. Invest Radiol 2015; 50:188-94. [DOI: 10.1097/rli.0000000000000098] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
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CT Liver Imaging: What is New? CURRENT RADIOLOGY REPORTS 2015. [DOI: 10.1007/s40134-015-0088-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
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Investigation of hepatic blood perfusion by laser speckle imaging and changes of hepatic vasoactive substances in mice after electroacupuncture. EVIDENCE-BASED COMPLEMENTARY AND ALTERNATIVE MEDICINE 2014; 2014:715316. [PMID: 25140188 PMCID: PMC4129169 DOI: 10.1155/2014/715316] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/26/2014] [Revised: 05/28/2014] [Accepted: 06/20/2014] [Indexed: 11/18/2022]
Abstract
The study was conducted to observe the effect of electroacupuncture (EA) on hepatic blood perfusion (HBP) and vascular regulation. We investigated 60 male anesthetized mice under the following 3 conditions: without EA stimulation (control group); EA stimulation at Zusanli (ST36 group); EA stimulation at nonacupoint (NA group) during 30 min. The HBP was measured using the laser speckle perfusion imaging (LSPI). The level of nitric oxide (NO), endothelin-1 (ET-1), and noradrenaline (NE) in liver tissue was detected by biochemical methods. Results were as follows. At each time point, HBP increase in ST36 group was higher than that in the NA group in anesthetized mice. HBP gradually decreased during 30 min in control group. The level of NO in ST36 group was higher than that in NA group. The level of both ET-1 and NE was the highest in control group, followed by NA group and ST36 group. It is concluded that EA at ST36 could increase HBP possibly by increasing the blood flow velocity (BFV), changing vascular activity, increasing the level of NO, and inhibiting the level of ET-1 in liver tissue.
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Perfusion CT best predicts outcome after radioembolization of liver metastases: a comparison of radionuclide and CT imaging techniques. Eur Radiol 2014; 24:1455-65. [PMID: 24817083 DOI: 10.1007/s00330-014-3180-3] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2013] [Revised: 04/01/2014] [Accepted: 04/07/2014] [Indexed: 10/25/2022]
Abstract
OBJECTIVE To determine the best predictor for the response to and survival with transarterial radioembolisation (RE) with (90)yttrium microspheres in patients with liver metastases. METHODS Forty consecutive patients with liver metastases undergoing RE were evaluated with multiphase CT, perfusion CT and (99m)Tc-MAA SPECT. Arterial perfusion (AP) from perfusion CT, HU values from the arterial (aHU) and portal venous phase (pvHU) CT, and (99m)Tc-MAA uptake ratio of metastases were determined. Morphologic response was evaluated after 4 months and available in 30 patients. One-year survival was calculated with Kaplan-Meier curves. RESULTS We found significant differences between responders and non-responders for AP (P < 0.001) and aHU (P = 0.001) of metastases, while no differences were found for pvHU (P = 0.07) and the (99m)Tc-MAA uptake ratio (P = 0.40). AP had a significantly higher specificity than aHU (P = 0.003) for determining responders to RE. Patients with an AP >20 ml/100 ml/min had a significantly (P = 0.01) higher 1-year survival, whereas an aHU value >55 HU did not discriminate survival (P = 0.12). The Cox proportional hazard model revealed AP as the only significant (P = 0.02) independent predictor of survival. CONCLUSION Compared to arterial and portal venous enhancement and the (99m)Tc-MAA uptake ratio of liver metastases, the AP from perfusion CT is the best predictor of morphologic response to and 1-year survival with RE. KEY POINTS • Perfusion CT allows for calculation of the liver arterial perfusion. • Arterial perfusion of liver metastases differs between responders and non-responders to RE. • Arterial perfusion can be used to select patients responding to RE.
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Fischer MA, Vrugt B, Alkadhi H, Hahnloser D, Hany TF, Veit-Haibach P. Integrated ¹⁸F-FDG PET/perfusion CT for the monitoring of neoadjuvant chemoradiotherapy in rectal carcinoma: correlation with histopathology. Eur J Nucl Med Mol Imaging 2014; 41:1563-73. [PMID: 24760269 DOI: 10.1007/s00259-014-2752-4] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2013] [Accepted: 03/04/2014] [Indexed: 12/13/2022]
Abstract
PURPOSE The aim of this study was to prospectively monitor changes in the flow-metabolic phenotype (ΔFMP) of rectal carcinoma (RC) after neoadjuvant chemoradiotherapy (CRT) and to evaluate whether ΔFMP of RC correlate with histopathological prognostic factors including response to CRT. METHODS Sixteen patients with RC (12 men, mean age 60.7 ± 12.8 years) underwent integrated (18)F-fluorodeoxyglucose (FDG) positron emission tomography (PET)/perfusion CT (PET/PCT), followed by neoadjuvant CRT and surgery. In 13 patients, PET/PCT was repeated after CRT. Perfusion [blood flow (BF), blood volume (BV), mean transit time (MTT)] and metabolic [maximum and mean standardized uptake values (SUVmax, SUVmean)] parameters as well as the FMP (BF × SUVmax) were determined before and after CRT by two independent readers and correlated to histopathological prognostic factors of RC (microvessel density, necrosis index, regression index, vascular invasion) derived from resected specimens. The diagnostic performance of ΔFMP for prediction of treatment response was determined. RESULTS FMP significantly decreased after CRT (p < 0.001), exploiting higher changes after CRT as compared to changes of perfusion and metabolic parameters alone. Before CRT, no significant correlations were found between integrated PET/PCT and any of the histopathological parameters (all p > 0.05). After CRT, BV and SUVmax correlated positively with the necrosis index (r = 0.67/0.70), SUVmax with the invasion of blood vessels (r = 0.62) and ΔFMP with the regression index (r = 0.88; all p < 0.05). ΔFMP showed high accuracy for prediction of histopathological response to CRT (AUC 0.955, 95 % confidence interval 0.833-1.000, p < 0.01) using a cut-off value of -75%. CONCLUSION In RC, ΔFMP derived from integrated (18)F-FDG PET/PCT is useful for monitoring the effects of neoadjuvant CRT and allows prediction of histopathological response to CRT.
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Affiliation(s)
- Michael A Fischer
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, Raemistrasse 100, 8091, Zurich, Switzerland,
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Early treatment response evaluation after yttrium-90 radioembolization of liver malignancy with CT perfusion. J Vasc Interv Radiol 2014; 25:747-59. [PMID: 24630751 DOI: 10.1016/j.jvir.2014.01.025] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2013] [Revised: 12/30/2013] [Accepted: 01/01/2014] [Indexed: 12/21/2022] Open
Abstract
PURPOSE To evaluate computed tomography (CT) perfusion for assessment of early treatment response after transarterial radioembolization of patients with liver malignancy. MATERIALS AND METHODS Dynamic contrast-enhanced CT liver perfusion was performed before and 4 weeks after transarterial radioembolization in 40 patients (25 men and 15 women; mean age, 64 y ± 11; range, 35-80 y) with liver metastases (n = 27) or hepatocellular carcinoma (HCC) (n = 13). Arterial perfusion (AP) of tumors derived from CT perfusion and tumor diameters were measured on CT perfusion before and after transarterial radioembolization. Success of transarterial radioembolization was evaluated on morphologic follow-up imaging (median follow-up time, 4 mo) based on Response Evaluation Criteria in Solid Tumors (Version 1.1). CT perfusion parameters before and after transarterial radioembolization for different response groups were compared. Kaplan-Meier curves were plotted to illustrate overall 1-year survival rates. RESULTS Liver metastases showed significant differences in AP before and after transarterial radioembolization in responders (P < .05) but not in nonresponders (P = .164). In HCC, AP values before and after transarterial radioembolization were not significantly different in responders and nonresponders (P = .180 and P = .052). Tumor diameters were not significantly different on CT perfusion before and after transarterial radioembolization in responders and nonresponders with liver metastases and HCC (P = .654, P = .968, P = .148, P = .164). In patients with significant decrease of AP in liver metastases after transarterial radioembolization, 1-year overall survival was significantly higher than in patients showing no reduction of AP. CONCLUSIONS CT perfusion showed early reduction of AP in liver metastases responding to transarterial radioembolization; tumor diameter remained unchanged early after treatment. No significant early treatment response to transarterial radioembolization was found in patients with HCC. In patients with liver metastases, a decrease of AP after transarterial radioembolization was associated with a higher 1-year overall survival rate.
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Fujishiro T, Shuto K, Hayano K, Satoh A, Kono T, Ohira G, Tohma T, Gunji H, Narushima K, Tochigi T, Hanaoka T, Ishii S, Yanagawa N, Matsubara H. Preoperative hepatic CT perfusion as an early predictor for the recurrence of esophageal squamous cell carcinoma: initial clinical results. Oncol Rep 2014; 31:1083-8. [PMID: 24452736 PMCID: PMC3926648 DOI: 10.3892/or.2014.2992] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2013] [Accepted: 12/27/2013] [Indexed: 12/13/2022] Open
Abstract
Reports suggest that hepatic blood flow may have an association with cancer progression. The aim of the present study was to evaluate whether the hepatic blood flow measured by CT perfusion (CTP) may identify patients at high-risk for postoperative recurrence of esophageal squamous cell carcinoma (ESCC). Prior to surgery, hepatic CTP images were obtained using a 320-row area detector CT. The data were analyzed by a commercially available software based on the dual input maximum slope method, and arterial blood flow (AF, ml/min/100 ml tissue), portal blood flow (PF, ml/min/100 ml tissue) and perfusion index [PI (%) = AF/AF + PF × 100] were measured. These parameters were compared with the pathological stage and outcome of the ESCC patients. Forty-five patients with ESCC were eligible for this study. The median follow-up period was 17 months, and recurrences were observed in 9 patients (20%). The preoperative PI values of the 9 patients with recurrence were significantly higher than those of the 36 patients without recurrence (23.9 vs. 15.9, P=0.0022). Patients were categorized into the following two groups; high PI (>20) and low PI (<20). The recurrence-free survival of the low PI group was significantly better than that of the high PI group (P<0.0001). A multivariate analysis showed that a high PI was an independent risk factor for recurrence (odds ratio, 19.1; P=0.0369). Therefore, the preoperative PI of the liver may be a useful imaging biomarker for predicting the recurrence of patients with esophageal cancer.
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Affiliation(s)
- Takeshi Fujishiro
- Department of Frontier Surgery, Chiba University Graduate School of Medicine, Chuo‑ku, Chiba, Chiba 260‑8677, Japan
| | - Kiyohiko Shuto
- Department of Surgery, Teikyo University Medical Center, Ichihara, Chiba 299-0111, Japan
| | - Koichi Hayano
- Department of Frontier Surgery, Chiba University Graduate School of Medicine, Chuo‑ku, Chiba, Chiba 260‑8677, Japan
| | - Asami Satoh
- Department of Frontier Surgery, Chiba University Graduate School of Medicine, Chuo‑ku, Chiba, Chiba 260‑8677, Japan
| | - Tsuguaki Kono
- Department of Frontier Surgery, Chiba University Graduate School of Medicine, Chuo‑ku, Chiba, Chiba 260‑8677, Japan
| | - Gaku Ohira
- Department of Frontier Surgery, Chiba University Graduate School of Medicine, Chuo‑ku, Chiba, Chiba 260‑8677, Japan
| | - Takayuki Tohma
- Department of Frontier Surgery, Chiba University Graduate School of Medicine, Chuo‑ku, Chiba, Chiba 260‑8677, Japan
| | - Hisashi Gunji
- Department of Frontier Surgery, Chiba University Graduate School of Medicine, Chuo‑ku, Chiba, Chiba 260‑8677, Japan
| | - Kazuo Narushima
- Department of Frontier Surgery, Chiba University Graduate School of Medicine, Chuo‑ku, Chiba, Chiba 260‑8677, Japan
| | - Toru Tochigi
- Department of Frontier Surgery, Chiba University Graduate School of Medicine, Chuo‑ku, Chiba, Chiba 260‑8677, Japan
| | - Toshiharu Hanaoka
- Department of Frontier Surgery, Chiba University Graduate School of Medicine, Chuo‑ku, Chiba, Chiba 260‑8677, Japan
| | - Sayaka Ishii
- Department of Frontier Surgery, Chiba University Graduate School of Medicine, Chuo‑ku, Chiba, Chiba 260‑8677, Japan
| | - Noriyuki Yanagawa
- Department of Radiological Technology, Chiba University Hospital, Chuo-ku, Chiba, Chiba 260-8677, Japan
| | - Hisahiro Matsubara
- Department of Frontier Surgery, Chiba University Graduate School of Medicine, Chuo‑ku, Chiba, Chiba 260‑8677, Japan
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