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For: Bellomi M, Petralia G, Sonzogni A, Zampino MG, Rocca A. CT perfusion for the monitoring of neoadjuvant chemotherapy and radiation therapy in rectal carcinoma: initial experience. Radiology 2007;244:486-93. [PMID: 17641369 DOI: 10.1148/radiol.2442061189] [Citation(s) in RCA: 149] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]

For:	Bellomi M, Petralia G, Sonzogni A, Zampino MG, Rocca A. CT perfusion for the monitoring of neoadjuvant chemotherapy and radiation therapy in rectal carcinoma: initial experience. Radiology 2007;244:486-93. [PMID: 17641369 DOI: 10.1148/radiol.2442061189] [Citation(s) in RCA: 149] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]

Number

Cited by Other Article(s)

Li J, Chen XY, Wang YH, Wang X, Cheng YJ, Liu MC, Zhu L, Gao X, Deng WY, Liu JY, Lin XJ, Jin ZY, Xue HD. Comparison of Perfusion CT and Conventional Thin-slice Multiphase CT in the Diagnosis of Pancreatic Adenocarcinoma. Acad Radiol 2025:S1076-6332(25)00292-2. [PMID: 40393830 DOI: 10.1016/j.acra.2025.03.049] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2024] [Revised: 03/24/2025] [Accepted: 03/25/2025] [Indexed: 05/22/2025]

Affiliation(s)

Juan Li From the Department of Radiology, State Key Laboratory of Complex Severe and Rare Disease, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China
Xin-Yue Chen From CT collaboration, Siemens-Healthineers, China
Yu-Hong Wang From the Department of Radiology, State Key Laboratory of Complex Severe and Rare Disease, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China
Xiao Wang From the Department of Radiology, State Key Laboratory of Complex Severe and Rare Disease, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China
Yue-Juan Cheng From the Department of Oncology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China
Meng-Chao Liu From the Department of Radiology, State Key Laboratory of Complex Severe and Rare Disease, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China
Liang Zhu From the Department of Radiology, State Key Laboratory of Complex Severe and Rare Disease, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China
Xin Gao From the Department of Radiology, State Key Laboratory of Complex Severe and Rare Disease, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China
Wen-Yi Deng From the Department of Radiology, State Key Laboratory of Complex Severe and Rare Disease, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China
Jing-Yi Liu From the Department of Radiology, State Key Laboratory of Complex Severe and Rare Disease, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China
Xi-Juan Lin From the Department of Radiology, State Key Laboratory of Complex Severe and Rare Disease, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China
Zheng-Yu Jin From the Department of Radiology, State Key Laboratory of Complex Severe and Rare Disease, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China
Hua-Dan Xue From the Department of Radiology, State Key Laboratory of Complex Severe and Rare Disease, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China.

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Lu W, Deng H, Chen W, Zhou Y, Wu L, Shu H, Zhang P, Ye X. Analysis of early response to chemotherapy for non-Hodgkin's lymphoma by quantitative contrast-enhanced ultrasound: A prospective case-control crossectional study. Eur J Radiol 2024;176:111525. [PMID: 38796885 DOI: 10.1016/j.ejrad.2024.111525] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Revised: 05/14/2024] [Accepted: 05/21/2024] [Indexed: 05/29/2024]

Corrias G, Lai E, Ziranu P, Mariani S, Donisi C, Liscia N, Saba G, Pretta A, Persano M, Fanni D, Spanu D, Balconi F, Loi F, Deidda S, Restivo A, Pusceddu V, Puzzoni M, Solinas C, Massa E, Madeddu C, Gerosa C, Zorcolo L, Faa G, Saba L, Scartozzi M. Prediction of Response to Anti-Angiogenic Treatment for Advanced Colorectal Cancer Patients: From Biological Factors to Functional Imaging. Cancers (Basel) 2024;16:1364. [PMID: 38611042 PMCID: PMC11011199 DOI: 10.3390/cancers16071364] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2024] [Revised: 03/24/2024] [Accepted: 03/27/2024] [Indexed: 04/14/2024] Open

Affiliation(s)

Giuseppe Corrias Department of Radiology, University of Cagliari, 09042 Cagliari, Italy;
Eleonora Lai Medical Oncology Unit, University Hospital and University of Cagliari, 09042 Cagliari, Italy; (E.L.); (P.Z.); (S.M.); (C.D.); (G.S.); (A.P.); (M.P.); (D.S.); (F.B.); (F.L.); (V.P.); (M.P.); (C.S.); (E.M.); (C.M.); (M.S.)
Pina Ziranu Medical Oncology Unit, University Hospital and University of Cagliari, 09042 Cagliari, Italy; (E.L.); (P.Z.); (S.M.); (C.D.); (G.S.); (A.P.); (M.P.); (D.S.); (F.B.); (F.L.); (V.P.); (M.P.); (C.S.); (E.M.); (C.M.); (M.S.)
Stefano Mariani Medical Oncology Unit, University Hospital and University of Cagliari, 09042 Cagliari, Italy; (E.L.); (P.Z.); (S.M.); (C.D.); (G.S.); (A.P.); (M.P.); (D.S.); (F.B.); (F.L.); (V.P.); (M.P.); (C.S.); (E.M.); (C.M.); (M.S.)
Clelia Donisi Medical Oncology Unit, University Hospital and University of Cagliari, 09042 Cagliari, Italy; (E.L.); (P.Z.); (S.M.); (C.D.); (G.S.); (A.P.); (M.P.); (D.S.); (F.B.); (F.L.); (V.P.); (M.P.); (C.S.); (E.M.); (C.M.); (M.S.)
Nicole Liscia Department of Medical Oncology, IRCCS San Raffaele Scientific Institute, Vita-Salute San Raffaele University, 20132 Milan, Italy;
Giorgio Saba Medical Oncology Unit, University Hospital and University of Cagliari, 09042 Cagliari, Italy; (E.L.); (P.Z.); (S.M.); (C.D.); (G.S.); (A.P.); (M.P.); (D.S.); (F.B.); (F.L.); (V.P.); (M.P.); (C.S.); (E.M.); (C.M.); (M.S.)
Andrea Pretta Medical Oncology Unit, University Hospital and University of Cagliari, 09042 Cagliari, Italy; (E.L.); (P.Z.); (S.M.); (C.D.); (G.S.); (A.P.); (M.P.); (D.S.); (F.B.); (F.L.); (V.P.); (M.P.); (C.S.); (E.M.); (C.M.); (M.S.)
Mara Persano Medical Oncology Unit, University Hospital and University of Cagliari, 09042 Cagliari, Italy; (E.L.); (P.Z.); (S.M.); (C.D.); (G.S.); (A.P.); (M.P.); (D.S.); (F.B.); (F.L.); (V.P.); (M.P.); (C.S.); (E.M.); (C.M.); (M.S.)
Daniela Fanni Division of Pathology, Department of Medical Sciences and Public Health, AOU Cagliari, University of Cagliari, 09124 Cagliari, Italy; (D.F.); (C.G.); (G.F.)
Dario Spanu Medical Oncology Unit, University Hospital and University of Cagliari, 09042 Cagliari, Italy; (E.L.); (P.Z.); (S.M.); (C.D.); (G.S.); (A.P.); (M.P.); (D.S.); (F.B.); (F.L.); (V.P.); (M.P.); (C.S.); (E.M.); (C.M.); (M.S.)
Francesca Balconi Medical Oncology Unit, University Hospital and University of Cagliari, 09042 Cagliari, Italy; (E.L.); (P.Z.); (S.M.); (C.D.); (G.S.); (A.P.); (M.P.); (D.S.); (F.B.); (F.L.); (V.P.); (M.P.); (C.S.); (E.M.); (C.M.); (M.S.)
Francesco Loi Medical Oncology Unit, University Hospital and University of Cagliari, 09042 Cagliari, Italy; (E.L.); (P.Z.); (S.M.); (C.D.); (G.S.); (A.P.); (M.P.); (D.S.); (F.B.); (F.L.); (V.P.); (M.P.); (C.S.); (E.M.); (C.M.); (M.S.)
Simona Deidda Colorectal Surgery Unit, A.O.U. Cagliari, Department of Surgical Science, University of Cagliari, 09042 Cagliari, Italy; (S.D.); (A.R.); (L.Z.)
Angelo Restivo Colorectal Surgery Unit, A.O.U. Cagliari, Department of Surgical Science, University of Cagliari, 09042 Cagliari, Italy; (S.D.); (A.R.); (L.Z.)
Valeria Pusceddu Medical Oncology Unit, University Hospital and University of Cagliari, 09042 Cagliari, Italy; (E.L.); (P.Z.); (S.M.); (C.D.); (G.S.); (A.P.); (M.P.); (D.S.); (F.B.); (F.L.); (V.P.); (M.P.); (C.S.); (E.M.); (C.M.); (M.S.)
Marco Puzzoni Medical Oncology Unit, University Hospital and University of Cagliari, 09042 Cagliari, Italy; (E.L.); (P.Z.); (S.M.); (C.D.); (G.S.); (A.P.); (M.P.); (D.S.); (F.B.); (F.L.); (V.P.); (M.P.); (C.S.); (E.M.); (C.M.); (M.S.)
Cinzia Solinas Medical Oncology Unit, University Hospital and University of Cagliari, 09042 Cagliari, Italy; (E.L.); (P.Z.); (S.M.); (C.D.); (G.S.); (A.P.); (M.P.); (D.S.); (F.B.); (F.L.); (V.P.); (M.P.); (C.S.); (E.M.); (C.M.); (M.S.)
Elena Massa Medical Oncology Unit, University Hospital and University of Cagliari, 09042 Cagliari, Italy; (E.L.); (P.Z.); (S.M.); (C.D.); (G.S.); (A.P.); (M.P.); (D.S.); (F.B.); (F.L.); (V.P.); (M.P.); (C.S.); (E.M.); (C.M.); (M.S.)
Clelia Madeddu Medical Oncology Unit, University Hospital and University of Cagliari, 09042 Cagliari, Italy; (E.L.); (P.Z.); (S.M.); (C.D.); (G.S.); (A.P.); (M.P.); (D.S.); (F.B.); (F.L.); (V.P.); (M.P.); (C.S.); (E.M.); (C.M.); (M.S.)
Clara Gerosa Division of Pathology, Department of Medical Sciences and Public Health, AOU Cagliari, University of Cagliari, 09124 Cagliari, Italy; (D.F.); (C.G.); (G.F.)
Luigi Zorcolo Colorectal Surgery Unit, A.O.U. Cagliari, Department of Surgical Science, University of Cagliari, 09042 Cagliari, Italy; (S.D.); (A.R.); (L.Z.)
Gavino Faa Division of Pathology, Department of Medical Sciences and Public Health, AOU Cagliari, University of Cagliari, 09124 Cagliari, Italy; (D.F.); (C.G.); (G.F.)
Luca Saba Department of Radiology, University of Cagliari, 09042 Cagliari, Italy;
Mario Scartozzi Medical Oncology Unit, University Hospital and University of Cagliari, 09042 Cagliari, Italy; (E.L.); (P.Z.); (S.M.); (C.D.); (G.S.); (A.P.); (M.P.); (D.S.); (F.B.); (F.L.); (V.P.); (M.P.); (C.S.); (E.M.); (C.M.); (M.S.)

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Deng J, Zhang W, Xu M, Zhou J. Imaging advances in efficacy assessment of gastric cancer neoadjuvant chemotherapy. Abdom Radiol (NY) 2023;48:3661-3676. [PMID: 37787962 DOI: 10.1007/s00261-023-04046-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Revised: 08/31/2023] [Accepted: 09/03/2023] [Indexed: 10/04/2023]

Talakić E, Kaufmann-Bühler AK, Igrec J, Adelsmayr G, Janisch M, Döller C, Geyer E, Lackner K, Fuchsjäger M, Schöllnast H. Perfusion Computed Tomography in Rectal Carcinoma: Influence of Optimization of the Patlak Range on Calculation of Equivalent Blood Volume and Flow Extraction. J Comput Assist Tomogr 2023;47:850-855. [PMID: 37948358 DOI: 10.1097/rct.0000000000001506] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/29/2023]

Abstract

PURPOSE

The aim of the study is to assess the influence of manual adjustment of the Patlak range in computed tomography (CT) perfusion analysis of rectal carcinoma compared with default range of the perfusion software.

METHODS

This study was approved by the institutional review board and informed consent was obtained. Twenty-one patients (12 male, 9 female; mean age ± SD, 59 ± 11 years) with rectal cancer were included and underwent perfusion CT before preoperative chemoradiotherapy. Equivalent blood volume (BV) and flow-extraction (FE) were calculated using the Patlak plot model. Two perfusion sets were calculated per patient, a perfusion set using the default setting as provided by the software (dBV, dFE) and an optimized perfusion set after manual adaption of the Patlak range (aBV, aFE), which was limited to the intravascular space clearance of contrast to the extravascular space. Perfusion values calculated with both methods were compared for significance in differences using the Wilcoxon test. A P value of 0.05 or less was defined as statistically significant.

RESULTS

Adjustment of the Patlak range statistically significantly influenced BV and FE calculation. Median dBV was 23.2 mL/100 mL (interquartile range [IQR], 12.1 mL/100 mL), whereas median aBV was 20.3 mL/100 mL (IQR, 10.9 mL/100 mL). The difference in BV was statistically significant ( P = 0.021). Median dFE was 8.3 mL/min/100 mL (IQR, 4.7 mL/min/100 mL), whereas median aFE was 15.4 mL/min/100 mL (IQR, 5.8 mL/min/100 mL). The difference in FE was statistically significant ( P < 0.001).

CONCLUSIONS

Our findings indicate that in perfusion CT of rectal carcinoma, adjustment of the Patlak range may significantly influence BV and FE compared with default setting of the software. This may contribute to standardization in the use of this technique for functional imaging of rectal cancer.

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Khan F, Jones K, Lyon P. Immune checkpoint inhibition: a future guided by radiology. Br J Radiol 2023;96:20220565. [PMID: 36752570 PMCID: PMC10321249 DOI: 10.1259/bjr.20220565] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2022] [Revised: 01/04/2023] [Accepted: 01/29/2023] [Indexed: 02/09/2023] Open

Abstract

The limitation of the function of antitumour immune cells is a common hallmark of cancers that enables their survival. As such, the potential of immune checkpoint inhibition (ICI) acts as a paradigm shift in the treatment of a range of cancers but has not yet been fully capitalised. Combining minimally and non-invasive locoregional therapies offered by radiologists with ICI is now an active field of research with the aim of furthering therapeutic capabilities in medical oncology. In parallel to this impending advancement, the "imaging toolbox" available to radiologists is also growing, enabling more refined tumour characterisation as well as greater accuracy in evaluating responses to therapy. Options range from metabolite labelling to cellular localisation to immune checkpoint screening. It is foreseeable that these novel imaging techniques will be integrated into personalised treatment algorithms. This growth in the field must include updating the current standardised imaging criteria to ensure they are fit for purpose. Such criteria is crucial to both appropriately guide clinical decision-making regarding next steps of treatment, but also provide reliable prognosis. Quantitative approaches to these novel imaging techniques are also already being investigated to further optimise personalised therapeutic decision-making. The therapeutic potential of specific ICIs and locoregional therapies could be determined before administration thus limiting unnecessary side-effects whilst maintaining efficacy. Several radiological aspects of oncological care are advancing simultaneously. Therefore, it is essential that each development is assessed for clinical use and optimised to ensure the best treatment decisions are being offered to the patient. In this review, we discuss state of the art advances in novel functional imaging techniques in the field of immuno-oncology both pre-clinically and clinically.

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Agostini A, Borgheresi A, Mariotti F, Ottaviani L, Carotti M, Valenti M, Giovagnoni A. New Frontiers in Oncological Imaging With Computed Tomography: From Morphology to Function. Semin Ultrasound CT MR 2023;44:214-227. [PMID: 37245886 DOI: 10.1053/j.sult.2023.03.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/03/2023]

Dual-energy computed tomography as a lower radiation dose alternative to perfusion computed tomography in tumor viability assessment. Sci Rep 2023;13:120. [PMID: 36599882 DOI: 10.1038/s41598-022-27221-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2022] [Accepted: 12/28/2022] [Indexed: 01/06/2023] Open

Wang C, Wu N, Zhang Z, Zhang LX, Yuan XD. Evaluation of the dual vascular supply patterns in ground-glass nodules with a dynamic volume computed tomography. World J Radiol 2022;14:155-164. [PMID: 35978977 PMCID: PMC9258305 DOI: 10.4329/wjr.v14.i6.155] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/02/2021] [Revised: 04/20/2022] [Accepted: 06/17/2022] [Indexed: 02/06/2023] Open

Abstract

BACKGROUND

In recent years, the detection rate of ground-glass nodules (GGNs) has been improved dramatically due to the popularization of low-dose computed tomography (CT) screening with high-resolution CT technique. This presents challenges for the characterization and management of the GGNs, which depends on a thorough investigation and sufficient diagnostic knowledge of the GGNs. In most diagnostic studies of the GGNs, morphological manifestations are used to differentiate benignancy and malignancy. In contrast, few studies are dedicated to the assessment of the hemodynamics, i.e., perfusion parameters of the GGNs.

AIM

To assess the dual vascular supply patterns of GGNs on different histopathology and opacities.

METHODS

Forty-seven GGNs from 47 patients were prospectively included and underwent the dynamic volume CT. Histopathologic diagnoses were obtained within two weeks after the CT examination. Blood flow from the bronchial artery [bronchial flow (BF)] and pulmonary artery [pulmonary flow (PF)] as well as the perfusion index (PI) = [PF/(PF + BF)] were obtained using first-pass dual-input CT perfusion analysis and compared respectively between different histopathology and lesion types (pure or mixed GGNs) and correlated with the attenuation values of the lesions using one-way ANOVA, student’s t test and Pearson correlation analysis.

RESULTS

Of the 47 GGNs (mean diameter, 8.17 mm; range, 5.3-12.7 mm), 30 (64%) were carcinoma, 6 (13%) were atypical adenomatous hyperplasia and 11 (23%) were organizing pneumonia. All perfusion parameters (BF, PF and PI) demonstrated no significant difference among the three conditions (all P > 0.05). The PFs were higher than the BFs in all the three conditions (all P < 0.001). Of the 30 GGN carcinomas, 14 showed mixed GGNs and 16 pure GGNs with a higher PI in the latter (P < 0.01). Of the 17 benign GGNs, 4 showed mixed GGNs and 13 pure GGNs with no significant difference of the PI between the GGN types (P = 0.21). A negative correlation (r = -0.76, P < 0.001) was demonstrated between the CT attenuation values and the PIs in the 30 GGN carcinomas.

CONCLUSION

The GGNs are perfused dominantly by the PF regardless of its histopathology while the weight of the BF in the GGN carcinomas increases gradually during the progress of its opacification.

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Maehira H, Tsuji Y, Iida H, Mori H, Nitta N, Maekawa T, Kaida S, Miyake T, Tani M. Estimated tumor blood flow as a predictive imaging indicator of therapeutic response in pancreatic ductal adenocarcinoma: use of three-phase contrast-enhanced computed tomography. Int J Clin Oncol 2022;27:373-382. [PMID: 34783936 DOI: 10.1007/s10147-021-02066-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2021] [Accepted: 10/28/2021] [Indexed: 10/19/2022]

Chen SH, Miles K, Taylor SA, Ganeshan B, Rodriquez M, Fraioli F, Wan S, Afaq A, Shortman R, Walls D, Hoy L, Endozo R, Bhargava A, Hanson M, Huang J, Raouf S, Francis D, Siddiqi S, Arulampalam T, Sizer B, Machesney M, Reay-Jones N, Dindyal S, Ng T, Groves AM. FDG-PET/CT in colorectal cancer: potential for vascular-metabolic imaging to provide markers of prognosis. Eur J Nucl Med Mol Imaging 2021;49:371-384. [PMID: 33837843 PMCID: PMC8712298 DOI: 10.1007/s00259-021-05318-y] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2020] [Accepted: 03/13/2021] [Indexed: 02/07/2023]

Affiliation(s)

Shih-hsin Chen Division of Medicine, Research Department of Imaging, University College London (UCL), London, UK Department of Nuclear Medicine, Keelung Chang Gung Memorial Hospital, Keelung, Taiwan
Kenneth Miles Division of Medicine, Research Department of Imaging, University College London (UCL), London, UK
Stuart A. Taylor Division of Medicine, Research Department of Imaging, University College London (UCL), London, UK Centre for Medical Imaging, University College London, London, UK
Balaji Ganeshan Division of Medicine, Research Department of Imaging, University College London (UCL), London, UK
Manuel Rodriquez University College London Hospitals (UCLH) NHS Foundation Trust, Surgery and Cancer Board, Imaging Division, University College Hospital (UCH), London, UK Department of Research Pathology, Cancer Institute, UCL, London, UK
Francesco Fraioli University College London Hospitals (UCLH) NHS Foundation Trust, Surgery and Cancer Board, Imaging Division, University College Hospital (UCH), London, UK
Simon Wan University College London Hospitals (UCLH) NHS Foundation Trust, Surgery and Cancer Board, Imaging Division, University College Hospital (UCH), London, UK
Asim Afaq University College London Hospitals (UCLH) NHS Foundation Trust, Surgery and Cancer Board, Imaging Division, University College Hospital (UCH), London, UK University of Iowa, Carver College of Medicine, Iowa City, USA
Robert Shortman Department of Nuclear Medicine, Keelung Chang Gung Memorial Hospital, Keelung, Taiwan
Darren Walls Division of Medicine, Research Department of Imaging, University College London (UCL), London, UK
Luke Hoy Division of Medicine, Research Department of Imaging, University College London (UCL), London, UK
Raymond Endozo University College London Hospitals (UCLH) NHS Foundation Trust, Surgery and Cancer Board, Imaging Division, University College Hospital (UCH), London, UK
Aman Bhargava Institute of Health Barts and London Medical School, Queen Mary University of London (QMUL), London, UK
Matthew Hanson Barking, Havering and Redbridge University Hospitals NHS Trust, Division of Cancer and Clinical Support, Queens and King George Hospitals, Essex, UK
Joseph Huang Barking, Havering and Redbridge University Hospitals NHS Trust, Division of Cancer and Clinical Support, Queens and King George Hospitals, Essex, UK
Sherif Raouf Barking, Havering and Redbridge University Hospitals NHS Trust, Division of Cancer and Clinical Support, Queens and King George Hospitals, Essex, UK Radiotherapy Department, Barts Cancer Centre, St Bartholomew’s Hospital, West Smithfield, London, UK
Daren Francis Royal Free London NHS Foundation Trust, Department of Colorectal Surgery, Barnet and Chase Farm Hospitals, London, UK
Shahab Siddiqi Mid Essex Hospital Services NHS Trust, Department of Lower GI Surgery and Coloproctology, Broomfield Hospital, Essex, UK
Tan Arulampalam East Suffolk and North Essex NHS Foundation Trust, Department of Surgery & Department of Clinical Oncology, Colchester General Hospital, Essex, UK
Bruce Sizer East Suffolk and North Essex NHS Foundation Trust, Department of Surgery & Department of Clinical Oncology, Colchester General Hospital, Essex, UK
Michael Machesney Barts Health NHS Trust, Cancer Clinical Board, Colorectal Surgery, Whipps Cross Hospital, London, UK
Nicholas Reay-Jones East and North Hertfordshire NHS Trust, Colorectal Surgery, Queen Elizabeth II Hospital, Hertfordshire, UK
Sanjay Dindyal East and North Hertfordshire NHS Trust, Colorectal Surgery, Lister Hospital, Hertfordshire, UK
Tony Ng School of Cancer & Pharmaceutical Sciences, Kings College London (KCL), London, UK
Ashley M Groves Division of Medicine, Research Department of Imaging, University College London (UCL), London, UK

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Kruis MF. Improving radiation physics, tumor visualisation, and treatment quantification in radiotherapy with spectral or dual-energy CT. J Appl Clin Med Phys 2021;23:e13468. [PMID: 34743405 PMCID: PMC8803285 DOI: 10.1002/acm2.13468] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Revised: 10/13/2021] [Accepted: 10/19/2021] [Indexed: 12/11/2022] Open

Ko CC, Yeh LR, Kuo YT, Chen JH. Imaging biomarkers for evaluating tumor response: RECIST and beyond. Biomark Res 2021;9:52. [PMID: 34215324 PMCID: PMC8252278 DOI: 10.1186/s40364-021-00306-8] [Citation(s) in RCA: 85] [Impact Index Per Article: 21.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Accepted: 06/10/2021] [Indexed: 12/12/2022] Open

Foley KG, Pearson B, Riddell Z, Taylor SA. Opportunities in cancer imaging: a review of oesophageal, gastric and colorectal malignancies. Clin Radiol 2021;76:748-762. [PMID: 33579518 DOI: 10.1016/j.crad.2021.01.001] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2020] [Accepted: 01/13/2021] [Indexed: 02/07/2023]

Ponnatapura J, Lalwani N. Imaging of Colorectal Cancer: Screening, Staging, and Surveillance. Semin Roentgenol 2020;56:128-139. [PMID: 33858639 DOI: 10.1053/j.ro.2020.07.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]

Badia S, Picchia S, Bellini D, Ferrari R, Caruso D, Paolantonio P, Carbone I, Laghi A, Rengo M. The Role of Contrast-Enhanced Imaging for Colorectal Cancer Management. CURRENT COLORECTAL CANCER REPORTS 2019. [DOI: 10.1007/s11888-019-00443-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]

A prospective feasibility study evaluating the role of multimodality imaging and liquid biopsy for response assessment in locally advanced rectal carcinoma. Abdom Radiol (NY) 2019;44:3641-3651. [PMID: 31327041 DOI: 10.1007/s00261-019-02135-8] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]

Abstract

PURPOSE

Colorectal cancer is a commonly encountered disease that poses several diagnostic and therapeutic challenges. The inherent heterogeneity of tumor biology and propensity to relapse despite "curative" resection pose significant challenges with regard to response assessment. Although MR imaging already plays a key role in primary staging of patients with rectal carcinoma, its reliability in restaging after neoadjuvant therapy is debatable (Van der broek et al. in Dis Colon Rectum 60(3):274-283, 2017). Therefore, there is significant interest in developing additional methods which may improve diagnostic accuracy. This study aims to evaluate the role of multimodality imaging and liquid biopsy in therapeutic response assessment.

METHODS

Seventeen patients were enrolled into the study over a span of 24 months. All underwent hybrid PET-MRI and CT-perfusion (CT-P), prior to and following neoadjuvant therapy for locally advanced rectal carcinoma. Twelve of the 17 patients also underwent liquid biopsy, which consisted of blood sampling and analysis of circulating tumor cells (CTCs) and extracellular vesicles (EVs), including cell fragments and microparticles (MPs), using the Cell Search System (Menarini Silicon Biosystems). SUV, DWI, and ADC were calculated during PET-MRI, and several parameters were evaluated during CT-perfusion, including average perfusion, blood flow (BF), blood volume (BV), mean transit time (MTT), permeability-surface area product (PS), contrast extraction efficiency (E), and K-trans (K). Changes observed pre- and post-neoadjuvant therapy in each modality were compared to tumor response at histopathology using a modified Ryan tumor regression grading system.

RESULTS

Of the 17 patients included in the study, 14 were classified as non-responders, and 3 were classified as responders as determined by the modified Ryan Tumor Regression Grade (TRG) scoring system (Van der broek et al. in Dis Colon Rectum 60(3):274-283, 2017). When combined, blood markers and CT-P parameters (mean transit time (MTT), K-trans, and permeability-surface area product (PS)) produced the strongest models (p < 0.01). PET (SUV measurement) combined with CT-P-derived K-trans produced a marginally significant (p = 0.057) model for predicting response. MRI-derived ADC value did not provide a significant model for response prediction.

CONCLUSION

A model of CT-P parameters plus liquid biopsy more accurately predicts tumor response than PET-MRI, CT-P alone, or liquid biopsy alone. These results suggest that in the evaluation of treatment response, liquid biopsy could provide additional information to functional imaging modalities such as CT-P and should therefore be explored further in a trial with larger sample size.

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Mainenti PP, Stanzione A, Guarino S, Romeo V, Ugga L, Romano F, Storto G, Maurea S, Brunetti A. Colorectal cancer: Parametric evaluation of morphological, functional and molecular tomographic imaging. World J Gastroenterol 2019;25:5233-5256. [PMID: 31558870 PMCID: PMC6761241 DOI: 10.3748/wjg.v25.i35.5233] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/18/2019] [Revised: 08/06/2019] [Accepted: 08/24/2019] [Indexed: 02/06/2023] Open

Abstract

Colorectal cancer (CRC) represents one of the leading causes of tumor-related deaths worldwide. Among the various tools at physicians' disposal for the diagnostic management of the disease, tomographic imaging (e.g., CT, MRI, and hybrid PET imaging) is considered essential. The qualitative and subjective evaluation of tomographic images is the main approach used to obtain valuable clinical information, although this strategy suffers from both intrinsic and operator-dependent limitations. More recently, advanced imaging techniques have been developed with the aim of overcoming these issues. Such techniques, such as diffusion-weighted MRI and perfusion imaging, were designed for the "in vivo" evaluation of specific biological tissue features in order to describe them in terms of quantitative parameters, which could answer questions difficult to address with conventional imaging alone (e.g., questions related to tissue characterization and prognosis). Furthermore, it has been observed that a large amount of numerical and statistical information is buried inside tomographic images, resulting in their invisibility during conventional assessment. This information can be extracted and represented in terms of quantitative parameters through different processes (e.g., texture analysis). Numerous researchers have focused their work on the significance of these quantitative imaging parameters for the management of CRC patients. In this review, we aimed to focus on evidence reported in the academic literature regarding the application of parametric imaging to the diagnosis, staging and prognosis of CRC while discussing future perspectives and present limitations. While the transition from purely anatomical to quantitative tomographic imaging appears achievable for CRC diagnostics, some essential milestones, such as scanning and analysis standardization and the definition of robust cut-off values, must be achieved before quantitative tomographic imaging can be incorporated into daily clinical practice.

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Dercle L, Lu L, Lichtenstein P, Yang H, Wang D, Zhu J, Wu F, Piessevaux H, Schwartz LH, Zhao B. Impact of Variability in Portal Venous Phase Acquisition Timing in Tumor Density Measurement and Treatment Response Assessment: Metastatic Colorectal Cancer as a Paradigm. JCO Clin Cancer Inform 2019;1:1-8. [PMID: 30657405 DOI: 10.1200/cci.17.00108] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022] Open

Abstract

PURPOSE

New response patterns to anticancer drugs have led tumor size-based response criteria to shift to also include density measurements. Choi criteria, for instance, categorize antiangiogenic therapy response as a decrease in tumor density > 15% at the portal venous phase (PVP). We studied the effect that PVP timing has on measurement of the density of liver metastases (LM) from colorectal cancer (CRC).

METHODS

Pretreatment PVP computed tomography images from 291 patients with LM-CRC from the CRYSTAL trial (Cetuximab Combined With Irinotecan in First-Line Therapy for Metastatic Colorectal Cancer; ClinicalTrials.gov identifier: NCT00154102) were included. Four radiologists independently scored the scans' timing according to a three-point scoring system: early, optimal, late PVP. Using this, we developed, by machine learning, a proprietary computer-aided quality-control algorithm to grade PVP timing. The reference standard was a computer-refined consensus. For each patient, we contoured target liver lesions and calculated their mean density.

RESULTS

Contrast-product administration data were not recorded in the digital imaging and communications in medicine headers for injection volume (94%), type (93%), and route (76%). The PVP timing was early, optimal, and late in 52, 194, and 45 patients, respectively. The mean (95% CI) accuracy of the radiologists for detection of optimal PVP timing was 81.7% (78.3 to 85.2) and was outperformed by the 88.6% (84.8 to 92.4) computer accuracy. The mean ± standard deviation of LM-CRC density was 68 ± 15 Hounsfield units (HU) overall and 59.5 ± 14.9 HU, 71.4 ± 14.1 HU, 62.4 ± 12.5 HU at early, optimal, and late PVP timing, respectively. LM-CRC density was thus decreased at nonoptimal PVP timing by 14.8%: 16.7% at early PVP ( P < .001) and 12.6% at late PVP ( P < .001).

CONCLUSION

Nonoptimal PVP timing should be identified because it significantly decreased tumor density by 14.8%. Our computer-aided quality-control system outperformed the accuracy, reproducibility, and speed of radiologists' visual scoring. PVP-timing scoring could improve the extraction of tumor quantitative imaging biomarkers and the monitoring of anticancer therapy efficacy at the patient and clinical trial levels.

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Affiliation(s)

Laurent Dercle Laurent Dercle, Lin Lu, Philip Lichtenstein, Hao Yang, Jianguo Zhu, Feiyun Wu, Lawrence H. Schwartz, and Binsheng Zhao, Columbia University Medical Center, and Presbyterian Hospital, New York, NY; Laurent Dercle, Gustave Roussy, Université Paris-Saclay, UMR1015, Villejuif, France; Deling Wang, Sun Yat-sen University Cancer Center; Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong; State Key Laboratory of Oncology in South China, Hong Kong, Special Administrative Region, People's Republic of China; and Hubert Piessevaux, Cliniques Universitaires Saint-Luc, Brussels, Belgium
Lin Lu Laurent Dercle, Lin Lu, Philip Lichtenstein, Hao Yang, Jianguo Zhu, Feiyun Wu, Lawrence H. Schwartz, and Binsheng Zhao, Columbia University Medical Center, and Presbyterian Hospital, New York, NY; Laurent Dercle, Gustave Roussy, Université Paris-Saclay, UMR1015, Villejuif, France; Deling Wang, Sun Yat-sen University Cancer Center; Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong; State Key Laboratory of Oncology in South China, Hong Kong, Special Administrative Region, People's Republic of China; and Hubert Piessevaux, Cliniques Universitaires Saint-Luc, Brussels, Belgium
Philip Lichtenstein Laurent Dercle, Lin Lu, Philip Lichtenstein, Hao Yang, Jianguo Zhu, Feiyun Wu, Lawrence H. Schwartz, and Binsheng Zhao, Columbia University Medical Center, and Presbyterian Hospital, New York, NY; Laurent Dercle, Gustave Roussy, Université Paris-Saclay, UMR1015, Villejuif, France; Deling Wang, Sun Yat-sen University Cancer Center; Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong; State Key Laboratory of Oncology in South China, Hong Kong, Special Administrative Region, People's Republic of China; and Hubert Piessevaux, Cliniques Universitaires Saint-Luc, Brussels, Belgium
Hao Yang Laurent Dercle, Lin Lu, Philip Lichtenstein, Hao Yang, Jianguo Zhu, Feiyun Wu, Lawrence H. Schwartz, and Binsheng Zhao, Columbia University Medical Center, and Presbyterian Hospital, New York, NY; Laurent Dercle, Gustave Roussy, Université Paris-Saclay, UMR1015, Villejuif, France; Deling Wang, Sun Yat-sen University Cancer Center; Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong; State Key Laboratory of Oncology in South China, Hong Kong, Special Administrative Region, People's Republic of China; and Hubert Piessevaux, Cliniques Universitaires Saint-Luc, Brussels, Belgium
Deling Wang Laurent Dercle, Lin Lu, Philip Lichtenstein, Hao Yang, Jianguo Zhu, Feiyun Wu, Lawrence H. Schwartz, and Binsheng Zhao, Columbia University Medical Center, and Presbyterian Hospital, New York, NY; Laurent Dercle, Gustave Roussy, Université Paris-Saclay, UMR1015, Villejuif, France; Deling Wang, Sun Yat-sen University Cancer Center; Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong; State Key Laboratory of Oncology in South China, Hong Kong, Special Administrative Region, People's Republic of China; and Hubert Piessevaux, Cliniques Universitaires Saint-Luc, Brussels, Belgium
Jianguo Zhu Laurent Dercle, Lin Lu, Philip Lichtenstein, Hao Yang, Jianguo Zhu, Feiyun Wu, Lawrence H. Schwartz, and Binsheng Zhao, Columbia University Medical Center, and Presbyterian Hospital, New York, NY; Laurent Dercle, Gustave Roussy, Université Paris-Saclay, UMR1015, Villejuif, France; Deling Wang, Sun Yat-sen University Cancer Center; Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong; State Key Laboratory of Oncology in South China, Hong Kong, Special Administrative Region, People's Republic of China; and Hubert Piessevaux, Cliniques Universitaires Saint-Luc, Brussels, Belgium
Feiyun Wu Laurent Dercle, Lin Lu, Philip Lichtenstein, Hao Yang, Jianguo Zhu, Feiyun Wu, Lawrence H. Schwartz, and Binsheng Zhao, Columbia University Medical Center, and Presbyterian Hospital, New York, NY; Laurent Dercle, Gustave Roussy, Université Paris-Saclay, UMR1015, Villejuif, France; Deling Wang, Sun Yat-sen University Cancer Center; Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong; State Key Laboratory of Oncology in South China, Hong Kong, Special Administrative Region, People's Republic of China; and Hubert Piessevaux, Cliniques Universitaires Saint-Luc, Brussels, Belgium
Hubert Piessevaux Laurent Dercle, Lin Lu, Philip Lichtenstein, Hao Yang, Jianguo Zhu, Feiyun Wu, Lawrence H. Schwartz, and Binsheng Zhao, Columbia University Medical Center, and Presbyterian Hospital, New York, NY; Laurent Dercle, Gustave Roussy, Université Paris-Saclay, UMR1015, Villejuif, France; Deling Wang, Sun Yat-sen University Cancer Center; Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong; State Key Laboratory of Oncology in South China, Hong Kong, Special Administrative Region, People's Republic of China; and Hubert Piessevaux, Cliniques Universitaires Saint-Luc, Brussels, Belgium
Lawrence H Schwartz Laurent Dercle, Lin Lu, Philip Lichtenstein, Hao Yang, Jianguo Zhu, Feiyun Wu, Lawrence H. Schwartz, and Binsheng Zhao, Columbia University Medical Center, and Presbyterian Hospital, New York, NY; Laurent Dercle, Gustave Roussy, Université Paris-Saclay, UMR1015, Villejuif, France; Deling Wang, Sun Yat-sen University Cancer Center; Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong; State Key Laboratory of Oncology in South China, Hong Kong, Special Administrative Region, People's Republic of China; and Hubert Piessevaux, Cliniques Universitaires Saint-Luc, Brussels, Belgium
Binsheng Zhao Laurent Dercle, Lin Lu, Philip Lichtenstein, Hao Yang, Jianguo Zhu, Feiyun Wu, Lawrence H. Schwartz, and Binsheng Zhao, Columbia University Medical Center, and Presbyterian Hospital, New York, NY; Laurent Dercle, Gustave Roussy, Université Paris-Saclay, UMR1015, Villejuif, France; Deling Wang, Sun Yat-sen University Cancer Center; Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong; State Key Laboratory of Oncology in South China, Hong Kong, Special Administrative Region, People's Republic of China; and Hubert Piessevaux, Cliniques Universitaires Saint-Luc, Brussels, Belgium

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Hamdy A, Ichikawa Y, Toyomasu Y, Nagata M, Nagasawa N, Nomoto Y, Sami H, Sakuma H. Perfusion CT to Assess Response to Neoadjuvant Chemotherapy and Radiation Therapy in Pancreatic Ductal Adenocarcinoma: Initial Experience. Radiology 2019;292:628-635. [PMID: 31287389 DOI: 10.1148/radiol.2019182561] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]

Abstract

BackgroundChange in tumor size at CT is insufficient for reliable assessment of treatment response after neoadjuvant chemotherapy and radiation therapy (CRT) and shows poor correlation with histologic grading of response.PurposeTo investigate the use of perfusion CT to predict the response of pancreatic ductal adenocarcinoma (PDA) to CRT.Materials and MethodsBetween June 2016 and May 2018, study participants with biopsy-proven PDA were prospectively recruited to undergo perfusion CT before and after planned CRT. Blood flow (BF), blood volume (BV), and permeability-surface area product (PSP) were quantified from CT images. Participants were categorized into responders and nonresponders according to therapy response. The Mann-Whitney test was used to compare the baseline perfusion values between responders and nonresponders, and the Wilcoxon matched-pairs signed rank test was used to compare perfusion values before and after CRT.ResultsThe final cohort of 21 participants (median age, 68 years; interquartile range [IQR], 65-72 years; eight men) underwent dynamic perfusion (dual-source) CT before neoadjuvant CRT. All participants underwent pancreatectomy. Eighteen participants underwent post-CRT perfusion CT. Baseline BF was higher in responders (n = 10) than in nonresponders (n = 11) (median, 44 [IQR, 39-56] vs 28 [IQR, 16-52] mL/100 g/min; P = .04), while BV and PSP were similar between groups (median BV, 4.3 [IQR, 3.5-6.9] vs 2.0 [IQR, 1.6-6.5] mL/100 g, P = .15; median PSP, 25 [IQR, 21-30] vs 20 [IQR, 10-34] mL/100 g/min, P = .31). Response Evaluation Criteria in Solid Tumors (RECIST) and carbohydrate antigen (CA) 19-9 showed no correlation with perfusion parameters (eg, RECIST and BF: r = 0.05, P = .84, 95% confidence interval [CI]: -0.40, 0.48; CA 19-9 and BF: r = 0.06, P = .78, 95% CI: -0.39, 0.49) or histopathologic response (r = 0.16, P = .47, 95% CI: -0.3, 0.57 and r = 0.09, P = .71, 95% CI: -0.37, 0.51, respectively). For responders, perfusion parameters increased after CRT (eg, median BF, 54 [IQR, 42-73] vs 43 [IQR, 28-53] mL/100 g/min; P = .04). The perfusion change in nonresponders was not significant (median BF, 43 [IQR, 28-53] vs 33 [IQR, 16-52] mL/100 g/min; P = .06).ConclusionPerfusion CT may be useful in helping predict the histopathologic response to therapy in pancreatic ductal adenocarcinoma.© RSNA, 2019See also the editorial by Sinitsyn in this issue.

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Affiliation(s)

Ahmed Hamdy From the Department of Radiology, Mie University Hospital, 2-174 Edobashi, Tsu, Mie 514-8507, Japan (A.H., Y.I., Y.T., M.N., N.N., Y.N., H. Sakuma); and Kasr Alainy Faculty of Medicine, Cairo University, Cairo, Egypt (A.H., H. Sami)
Yasutaka Ichikawa From the Department of Radiology, Mie University Hospital, 2-174 Edobashi, Tsu, Mie 514-8507, Japan (A.H., Y.I., Y.T., M.N., N.N., Y.N., H. Sakuma); and Kasr Alainy Faculty of Medicine, Cairo University, Cairo, Egypt (A.H., H. Sami)
Yutaka Toyomasu From the Department of Radiology, Mie University Hospital, 2-174 Edobashi, Tsu, Mie 514-8507, Japan (A.H., Y.I., Y.T., M.N., N.N., Y.N., H. Sakuma); and Kasr Alainy Faculty of Medicine, Cairo University, Cairo, Egypt (A.H., H. Sami)
Motonori Nagata From the Department of Radiology, Mie University Hospital, 2-174 Edobashi, Tsu, Mie 514-8507, Japan (A.H., Y.I., Y.T., M.N., N.N., Y.N., H. Sakuma); and Kasr Alainy Faculty of Medicine, Cairo University, Cairo, Egypt (A.H., H. Sami)
Naoki Nagasawa From the Department of Radiology, Mie University Hospital, 2-174 Edobashi, Tsu, Mie 514-8507, Japan (A.H., Y.I., Y.T., M.N., N.N., Y.N., H. Sakuma); and Kasr Alainy Faculty of Medicine, Cairo University, Cairo, Egypt (A.H., H. Sami)
Yoshihito Nomoto From the Department of Radiology, Mie University Hospital, 2-174 Edobashi, Tsu, Mie 514-8507, Japan (A.H., Y.I., Y.T., M.N., N.N., Y.N., H. Sakuma); and Kasr Alainy Faculty of Medicine, Cairo University, Cairo, Egypt (A.H., H. Sami)
Haney Sami From the Department of Radiology, Mie University Hospital, 2-174 Edobashi, Tsu, Mie 514-8507, Japan (A.H., Y.I., Y.T., M.N., N.N., Y.N., H. Sakuma); and Kasr Alainy Faculty of Medicine, Cairo University, Cairo, Egypt (A.H., H. Sami)
Hajime Sakuma From the Department of Radiology, Mie University Hospital, 2-174 Edobashi, Tsu, Mie 514-8507, Japan (A.H., Y.I., Y.T., M.N., N.N., Y.N., H. Sakuma); and Kasr Alainy Faculty of Medicine, Cairo University, Cairo, Egypt (A.H., H. Sami)

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Trinidad López C, De La Fuente Aguado J, Oca Pernas R, Delgado Sánchez-Gracián C, Santos Armentia E, Vaamonde Liste A, Prada González R, Souto Bayarri M. Evaluation of response to conventional chemotherapy and radiotherapy by perfusion computed tomography in non-small cell lung cancer (NSCLC). Eur Radiol Exp 2019;3:23. [PMID: 31197486 PMCID: PMC6565789 DOI: 10.1186/s41747-019-0101-x] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2019] [Accepted: 05/02/2019] [Indexed: 12/16/2022] Open

Lee DH, Kim SH, Lee SM, Han JK. Prediction of Treatment Outcome of Chemotherapy Using Perfusion Computed Tomography in Patients with Unresectable Advanced Gastric Cancer. Korean J Radiol 2019;20:589-598. [PMID: 30887741 PMCID: PMC6424833 DOI: 10.3348/kjr.2018.0306] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2018] [Accepted: 10/03/2018] [Indexed: 02/06/2023] Open

Abstract

Objective

To evaluate whether data acquired from perfusion computed tomography (PCT) parameters can aid in the prediction of treatment outcome after palliative chemotherapy in patients with unresectable advanced gastric cancer (AGC).

Materials and Methods

Twenty-one patients with unresectable AGCs, who underwent both PCT and palliative chemotherapy, were prospectively included. Treatment response was assessed according to Response Evaluation Criteria in Solid Tumors version 1.1 (i.e., patients who achieved complete or partial response were classified as responders). The relationship between tumor response and PCT parameters was evaluated using the Mann-Whitney test and receiver operating characteristic analysis. One-year survival was estimated using the Kaplan-Meier method.

Results

After chemotherapy, six patients exhibited partial response and were allocated to the responder group while the remaining 15 patients were allocated to the non-responder group. Permeability surface (PS) value was shown to be significantly different between the responder and non-responder groups (51.0 mL/100 g/min vs. 23.4 mL/100 g/min, respectively; p = 0.002), whereas other PCT parameters did not demonstrate a significant difference. The area under the curve for prediction in responders was 0.911 (p = 0.004) for PS value, with a sensitivity of 100% (6/6) and specificity of 80% (12/15) at a cut-off value of 29.7 mL/100 g/min. One-year survival in nine patients with PS value > 29.7 mL/100 g/min was 66.7%, which was significantly higher than that in the 12 patients (33.3%) with PS value ≤ 29.7 mL/100 g/min (p = 0.019).

Conclusion

Perfusion parameter data acquired from PCT demonstrated predictive value for treatment outcome after palliative chemotherapy, reflected by the significantly higher PS value in the responder group compared with the non-responder group.

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Emerging Functional Imaging Biomarkers of Tumour Responses to Radiotherapy. Cancers (Basel) 2019;11:cancers11020131. [PMID: 30678055 PMCID: PMC6407112 DOI: 10.3390/cancers11020131] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2018] [Revised: 01/11/2019] [Accepted: 01/13/2019] [Indexed: 12/11/2022] Open

MRI-Based Apparent Diffusion Coefficient for Predicting Pathologic Response of Rectal Cancer After Neoadjuvant Therapy: Systematic Review and Meta-Analysis. AJR Am J Roentgenol 2018;211:W205-W216. [PMID: 30240291 DOI: 10.2214/ajr.17.19135] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]

Ippolito D, Querques G, Okolicsanyi S, Talei Franzesi C, Pecorelli A, Lombardi S, Orsini E, Strazzabosco M, Sironi S. Dynamic contrast enhanced perfusion CT imaging: A diagnostic biomarker tool for survival prediction of tumour response to antiangiogenetic treatment in patients with advanced HCC lesions. Eur J Radiol 2018;106:62-68. [PMID: 30150052 DOI: 10.1016/j.ejrad.2018.07.012] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2018] [Revised: 05/24/2018] [Accepted: 07/12/2018] [Indexed: 02/08/2023]

Niu T, Yang P, Sun X, Mao T, Xu L, Yue N, Kuang Y, Shi L, Nie K. Variations of quantitative perfusion measurement on dynamic contrast enhanced CT for colorectal cancer: implication of standardized image protocol. Phys Med Biol 2018;63:165009. [PMID: 29889046 DOI: 10.1088/1361-6560/aacb99] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023]

Abstract

Tumor angiogenesis is considered an important prognostic factor. With an increasing emphasis on imaging evaluation of the tumor microenvironment, dynamic contrast enhanced-computed tomography (DCE-CT) has evolved as an important functional technique in this setting. Yet many questions remain as to how and when these functional measurements should be performed for each agent and tumor type, and what quantitative models should be used in the fitting process. In this study, we evaluated the variations of perfusion measurement on DCE-CT for rectal cancer patients from (1) different tracer kinetic models, (2) different scan acquisition lengths, and (3) different scan intervals. A total of seven commonly used models were studied: the adiabatic approximation to the tissue homogeneity (AATH) model, adiabatic approximation to the homogeneity tissue with fixed transit time (AATHFT) model, the Tofts model (TM), the extended Tofts model (ETM), Patlak model, Logan model, and the model-free deconvolution method. Akaike's information criterion was used to identify the best fitting model. The interchangeability of different models was further evaluated using Bland-Altman analysis. All models gave comparable blood volume (BV) measurements except the Patlak method. While for the volume transfer constant (K_trans) estimation, AATHFT, AATH, and ETM generated reasonable agreement among each other but not for the other models. Regarding the blood flow (BF) measurement, no two models were interchangeable. In addition, the perfusion parameters were compared with four acquisition times (45, 65, 85, and 105 s) and four temporal intervals (1, 2, 3, and 4 s). No significant difference was observed in the volume transfer constant (K_trans), BV, and BF measurements when comparing data acquired over 65 s with data acquired over 105 s using any of the DCE models in this study. Yet increasing the temporal interval led to a significant overestimation of BF in the deconvolution method. In conclusion, the perfusion measurement is indeed model dependent and the image acquisition/processing technique is dependent. The radiation dose of DCE-CT was an average of 1.5-2 times an abdomen/pelvic CT, which is not insubstantial. To take the DCE-CT forward as a biomarker in oncology, prospective studies should be carefully designed with the optimal image acquisition and analysis technique.

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Armstrong G, Croft J, Corrigan N, Brown JM, Goh V, Quirke P, Hulme C, Tolan D, Kirby A, Cahill R, O'Connell PR, Miskovic D, Coleman M, Jayne D. IntAct: intra-operative fluorescence angiography to prevent anastomotic leak in rectal cancer surgery: a randomized controlled trial. Colorectal Dis 2018;20:O226-O234. [PMID: 29751360 PMCID: PMC6099475 DOI: 10.1111/codi.14257] [Citation(s) in RCA: 84] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/09/2017] [Accepted: 05/02/2018] [Indexed: 02/06/2023]

Venkat B, Sharma S, Sharma D, Sood S, Aggarwal N, Sarkar M, Seam RK, Mittal N, Rana L. CT perfusion in non-small cell lung cancers for assessing treatment response, monitoring treatment and predicting prognosis. THE EGYPTIAN JOURNAL OF RADIOLOGY AND NUCLEAR MEDICINE 2018. [DOI: 10.1016/j.ejrnm.2017.12.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/17/2022] Open

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: 2.0] [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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Variability and Reproducibility of 3^rd-generation dual-source dynamic volume perfusion CT Parameters in Comparison to MR-perfusion Parameters in Rectal Cancer. Sci Rep 2018;8:6868. [PMID: 29720622 PMCID: PMC5932032 DOI: 10.1038/s41598-018-25307-w] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2017] [Accepted: 04/19/2018] [Indexed: 12/22/2022] Open

Sun Z, Cheng X, Ge Y, Shao L, Xuan Y, Yan G. An application study of low-dose computed tomography perfusion imaging for evaluation of the efficacy of neoadjuvant chemotherapy for advanced gastric adenocarcinoma. Gastric Cancer 2018;21:413-420. [PMID: 28871423 DOI: 10.1007/s10120-017-0763-0] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/16/2017] [Accepted: 08/30/2017] [Indexed: 02/07/2023]

Zhang P, Chen Y, Liu J, Yang Y, Lv Q, Wang J, Zhang L, Xie M. Quantitative Evaluation of Combretastatin A4 Phosphate Early Efficacy in a Tumor Model with Dynamic Contrast-Enhanced Ultrasound. ULTRASOUND IN MEDICINE & BIOLOGY 2018;44:840-852. [PMID: 29395676 DOI: 10.1016/j.ultrasmedbio.2017.12.002] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/06/2017] [Revised: 11/23/2017] [Accepted: 12/03/2017] [Indexed: 06/07/2023]

Abstract

Combretastatin A4 phosphate (CA4P) is a vascular disrupting agent that rapidly shuts down blood supply to tumors. Early monitoring of tumor perfusion plays a crucial role in determining the optimal strategy to managing treatment and guiding future therapy. The aim of this study was to investigate the potential value of dynamic contrast-enhanced ultrasound (CEUS) in quantitative evaluation of tumor perfusion at an early stage in CA4P therapy. Central and peripheral perfusion of tumors was detected by CEUS pre-treatment (0 h) and 2, 12 and 48 h after CA4P injection. Two perfusion parameters, maximum intensity (IMAX) and time to peak (TTP), were calculated from the time-intensity curve. After CEUS, the efficacy of CA4P was immediately confirmed by immunofluorescence assay and hematoxylin and eosin, Hoechst 33342 and fluorescein isothiocyanate-lectin staining. In CEUS of the center region of tumors, IMAX gradually decreased from 0 to 12 h and regrew at 48 h (p < 0.01). TTP increased only at 2 h. In the peripheral regions, IMAX did not change obviously from 0 to 12 h (p > 0.05) and just increased at 48 h (p < 0.01). The TTP of peripheral regions had the same tendency to vary tendency as that of center regions. In addition, microvascular density (MVD), vascular perfusion and necrotic area of the tumor were quantitatively analyzed. A close correlation between IMAX and MVD was observed in the center areas of tumors (r = 0.72, p < 0.01), whereas the correlation between IMAX and MVD in peripheral areas was weak (r = 0.37, p < 0.01). However, IMAX was positively correlated with tumor perfusion in both center and peripheral areas of tumors (r = 0.82, p < 0.01, and r = 0.63, p < 0.01, respectively). Consequently, IMAX was a reliable indicator of tumor perfusion evaluation by CEUS. The use of CEUS to quantify tumor perfusion could a promising method for the early detection of tumor responses in anti-vascular treatment.

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Affiliation(s)

Pingyu Zhang Department of Ultrasound, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China; Hubei Key Laboratory of Molecular Imaging, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
Yihan Chen Department of Ultrasound, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China; Hubei Key Laboratory of Molecular Imaging, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
JinFeng Liu Department of Ultrasound, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China; Hubei Key Laboratory of Molecular Imaging, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
Yali Yang Department of Ultrasound, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China; Hubei Key Laboratory of Molecular Imaging, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
Qing Lv Department of Ultrasound, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China; Hubei Key Laboratory of Molecular Imaging, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
Jing Wang Department of Ultrasound, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China; Hubei Key Laboratory of Molecular Imaging, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
Li Zhang Department of Ultrasound, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China; Hubei Key Laboratory of Molecular Imaging, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
Mingxing Xie Department of Ultrasound, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China; Hubei Key Laboratory of Molecular Imaging, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China.

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Dynamic Measurement of Arterial Liver Perfusion With an Interventional C-Arm System. Invest Radiol 2018;52:456-461. [PMID: 28306699 DOI: 10.1097/rli.0000000000000368] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]

Sade R, Kantarci M, Genc B, Ogul H, Gundogdu B, Yilmaz O. Computed Tomography Perfusion Imaging for the Diagnosis of Hepatic Alveolar Echinococcosis. Eurasian J Med 2018;50:1-5. [PMID: 29531482 PMCID: PMC5843444 DOI: 10.5152/eurasianjmed.2017.17321] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2017] [Accepted: 11/11/2017] [Indexed: 01/21/2023] Open

Kawamoto S, Fuld MK, Laheru D, Huang P, Fishman EK. Assessment of iodine uptake by pancreatic cancer following chemotherapy using dual-energy CT. Abdom Radiol (NY) 2018;43:445-456. [PMID: 29473093 PMCID: PMC7385923 DOI: 10.1007/s00261-017-1338-6] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]

Liang JX, Bi XJ, Li XM, Gao ZL, Suo F, Cui EG, Li HF, Lv HL. Evaluation of Multislice Spiral Computed Tomography Perfusion Imaging for the Efficacy of Preoperative Concurrent Chemoradiotherapy in Middle-aged and Elderly Patients with Locally Advanced Gastric Cancer. Med Sci Monit 2018;24:235-245. [PMID: 29326419 PMCID: PMC5774178 DOI: 10.12659/msm.905143] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022] Open

Lin Q, Wang J, Li Q, Lin C, Guo Z, Zheng W, Yan C, Li A, Zhou J. Ultrasonic RF time series for early assessment of the tumor response to chemotherapy. Oncotarget 2017;9:2668-2677. [PMID: 29416800 PMCID: PMC5788668 DOI: 10.18632/oncotarget.23625] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2017] [Accepted: 12/15/2017] [Indexed: 11/25/2022] Open

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: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open

Kruk-Bachonko J, Krupski W, Czechowski M, Kurys-Denis E, Mądro P, Sierocińska-Sawa J, Dąbrowski A, Wallner G, Skoczylas T. Perfusion CT - A novel quantitative and qualitative imaging biomarker in gastric cancer. Eur J Radiol 2017;95:399-408. [PMID: 28987697 DOI: 10.1016/j.ejrad.2017.08.033] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2017] [Revised: 06/22/2017] [Accepted: 08/28/2017] [Indexed: 01/19/2023]

Abstract

OBJECTIVES

The aim of this research was to examine whether Perfusion Computed Tomography (P-CT) can qualitatively and quantitatively help detect gastric cancer neoangiogenesis in vivo as well as treatment response evaluation. We attempted to explore which P-CT parameters are best used in neoangiogenesis and neoadjuvant therapy for most effective evaluation. We also tried to recognize a positive prediction value of P-CT in early responders and non-responders patients identification.

MATERIALS AND METHODS

Twenty-four patients with positive biopsy results and/or clinically proven gastric cancer were enrolled in the P-CT exam. Patients were qualified for systemic treatment (16 patients received chemotherapy and 8 patients received radiochemotherapy). The baseline Perfusion-CT exam and after neoadjuvant treatment Perfusion-CT exam were conducted using a 64-row GE tomograph based on a deconvolution model in first-pass protocol perfusion. The P-CT examined the following parameters: Blood Flow (BF), Blood Volume (BV), Mean Transit Time (MTT) and Permeability Surface (PS). Positive clinical response to neoadjuvant treatment (CHT and RCT) was defined as tumor size reduction 25% or more.

RESULTS

Tumor dimension reduction after neoadjuvant therapy was significantly correlated with the BF and the PS. Neoadjuvant therapy was more effective for patients with higher output BF and PS values. We did not register a significant relationship between BV and MTT parameters and tumor dimension reduction. Patients with a positive treatment response showed a decrease in BF, BV and PS perfusion parameters with an increase in MTT.

CONCLUSIONS

P-CT examination allows a noninvasive neoangiogenesis assessment in vivo, leading to early identification of responding and non-responding patients. As a standard procedure, a full evaluation of treatment response should include a P-CT exam assessing neoangiogenesis.

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Prezzi D, Goh V, Virdi S, Mallett S, Grierson C, Breen D, On behalf of the PROSPeCT Investigators. Adaptive statistical iterative reconstruction improves image quality without affecting perfusion CT quantitation in primary colorectal cancer. Eur J Radiol Open 2017;4:69-74. [PMID: 28616448 PMCID: PMC5458094 DOI: 10.1016/j.ejro.2017.05.003] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2017] [Revised: 05/22/2017] [Accepted: 05/22/2017] [Indexed: 01/28/2023] Open

Vallance A, Wexner S, Berho M, Cahill R, Coleman M, Haboubi N, Heald RJ, Kennedy RH, Moran B, Mortensen N, Motson RW, Novell R, O'Connell PR, Ris F, Rockall T, Senapati A, Windsor A, Jayne DG. A collaborative review of the current concepts and challenges of anastomotic leaks in colorectal surgery. Colorectal Dis 2017;19:O1-O12. [PMID: 27671222 DOI: 10.1111/codi.13534] [Citation(s) in RCA: 94] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/16/2016] [Accepted: 07/27/2016] [Indexed: 02/06/2023]

Can quantitative contrast-enhanced ultrasonography predict cervical tumor response to neoadjuvant chemotherapy? Eur J Radiol 2016;85:2111-2118. [DOI: 10.1016/j.ejrad.2016.09.025] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2016] [Revised: 09/22/2016] [Accepted: 09/24/2016] [Indexed: 11/22/2022]

Computed Tomography Perfusion Imaging Detection of Microcirculatory Dysfunction in Small Intestinal Ischemia-Reperfusion Injury in a Porcine Model. PLoS One 2016;11:e0160102. [PMID: 27458696 PMCID: PMC4961382 DOI: 10.1371/journal.pone.0160102] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2016] [Accepted: 07/13/2016] [Indexed: 01/19/2023] Open

Chen PC, Lee JC. Treatment of locally advanced low rectal cancer. FORMOSAN JOURNAL OF SURGERY 2016. [DOI: 10.1016/j.fjs.2016.02.003] [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] Open

Kim JI, Lee HJ, Goo JM, Kim MA, Chung DH. Correlation of volumetric perfusion CT parameters with hypoxia inducible factor-1 alpha expression in a rabbit VX2 tumor model. Acta Radiol 2016;57:708-15. [PMID: 26339038 DOI: 10.1177/0284185115603243] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2014] [Accepted: 08/01/2015] [Indexed: 11/17/2022]

Hill EJ, Roberts C, Franklin JM, Enescu M, West N, MacGregor TP, Chu KY, Boyle L, Blesing C, Wang LM, Mukherjee S, Anderson EM, Brown G, Dutton S, Love SB, Schnabel JA, Quirke P, Muschel R, McKenna WG, Partridge M, Sharma RA. Clinical Trial of Oral Nelfinavir before and during Radiation Therapy for Advanced Rectal Cancer. Clin Cancer Res 2016;22:1922-31. [PMID: 26861457 PMCID: PMC4835023 DOI: 10.1158/1078-0432.ccr-15-1489] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2015] [Accepted: 12/28/2015] [Indexed: 01/13/2023]

Affiliation(s)

Esme J Hill Oxford Cancer Imaging Centre and NIHR Oxford Biomedical Research Centre, Department of Oncology, University of Oxford, Oxford, United Kingdom
Corran Roberts Centre for Statistics in Medicine, Nuffield Department of Orthopaedics Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, United Kingdom
Jamie M Franklin Oxford Cancer Imaging Centre and NIHR Oxford Biomedical Research Centre, Department of Oncology, University of Oxford, Oxford, United Kingdom
Monica Enescu Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, United Kingdom
Nicholas West Section of Pathology and Tumour Biology, Leeds Institute of Cancer and Pathology, University of Leeds, St James's University Hospital, Leeds, United Kingdom
Thomas P MacGregor Oxford Cancer Imaging Centre and NIHR Oxford Biomedical Research Centre, Department of Oncology, University of Oxford, Oxford, United Kingdom
Kwun-Ye Chu Oxford Cancer Imaging Centre and NIHR Oxford Biomedical Research Centre, Department of Oncology, University of Oxford, Oxford, United Kingdom
Lucy Boyle Oncology Clinical Trials Office (OCTO), Department of Oncology, University of Oxford, Oxford, United Kingdom
Claire Blesing Oxford University Hospitals NHS Trust, Churchill Hospital, Oxford, United Kingdom
Lai-Mun Wang Oxford University Hospitals NHS Trust, Churchill Hospital, Oxford, United Kingdom
Somnath Mukherjee Oxford Cancer Imaging Centre and NIHR Oxford Biomedical Research Centre, Department of Oncology, University of Oxford, Oxford, United Kingdom
Ewan M Anderson Oxford University Hospitals NHS Trust, Churchill Hospital, Oxford, United Kingdom
Gina Brown Radiology Department, Royal Marsden Hospital, Sutton, Surrey, United Kingdom
Susan Dutton Centre for Statistics in Medicine, Nuffield Department of Orthopaedics Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, United Kingdom
Sharon B Love Centre for Statistics in Medicine, Nuffield Department of Orthopaedics Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, United Kingdom
Julia A Schnabel Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, United Kingdom
Phil Quirke Section of Pathology and Tumour Biology, Leeds Institute of Cancer and Pathology, University of Leeds, St James's University Hospital, Leeds, United Kingdom
Ruth Muschel Oxford Cancer Imaging Centre and NIHR Oxford Biomedical Research Centre, Department of Oncology, University of Oxford, Oxford, United Kingdom
William G McKenna Oxford Cancer Imaging Centre and NIHR Oxford Biomedical Research Centre, Department of Oncology, University of Oxford, Oxford, United Kingdom
Michael Partridge Oxford Cancer Imaging Centre and NIHR Oxford Biomedical Research Centre, Department of Oncology, University of Oxford, Oxford, United Kingdom
Ricky A Sharma Oxford Cancer Imaging Centre and NIHR Oxford Biomedical Research Centre, Department of Oncology, University of Oxford, Oxford, United Kingdom.

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Kim SM, Haider MA, Jaffray DA, Yeung IWT. Improved accuracy of quantitative parameter estimates in dynamic contrast-enhanced CT study with low temporal resolution. Med Phys 2016;43:388. [PMID: 26745932 DOI: 10.1118/1.4937600] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022] Open

Abstract

PURPOSE

A previously proposed method to reduce radiation dose to patient in dynamic contrast-enhanced (DCE) CT is enhanced by principal component analysis (PCA) filtering which improves the signal-to-noise ratio (SNR) of time-concentration curves in the DCE-CT study. The efficacy of the combined method to maintain the accuracy of kinetic parameter estimates at low temporal resolution is investigated with pixel-by-pixel kinetic analysis of DCE-CT data.

METHODS

The method is based on DCE-CT scanning performed with low temporal resolution to reduce the radiation dose to the patient. The arterial input function (AIF) with high temporal resolution can be generated with a coarsely sampled AIF through a previously published method of AIF estimation. To increase the SNR of time-concentration curves (tissue curves), first, a region-of-interest is segmented into squares composed of 3 × 3 pixels in size. Subsequently, the PCA filtering combined with a fraction of residual information criterion is applied to all the segmented squares for further improvement of their SNRs. The proposed method was applied to each DCE-CT data set of a cohort of 14 patients at varying levels of down-sampling. The kinetic analyses using the modified Tofts' model and singular value decomposition method, then, were carried out for each of the down-sampling schemes between the intervals from 2 to 15 s. The results were compared with analyses done with the measured data in high temporal resolution (i.e., original scanning frequency) as the reference.

RESULTS

The patients' AIFs were estimated to high accuracy based on the 11 orthonormal bases of arterial impulse responses established in the previous paper. In addition, noise in the images was effectively reduced by using five principal components of the tissue curves for filtering. Kinetic analyses using the proposed method showed superior results compared to those with down-sampling alone; they were able to maintain the accuracy in the quantitative histogram parameters of volume transfer constant [standard deviation (SD), 98th percentile, and range], rate constant (SD), blood volume fraction (mean, SD, 98th percentile, and range), and blood flow (mean, SD, median, 98th percentile, and range) for sampling intervals between 10 and 15 s.

CONCLUSIONS

The proposed method of PCA filtering combined with the AIF estimation technique allows low frequency scanning for DCE-CT study to reduce patient radiation dose. The results indicate that the method is useful in pixel-by-pixel kinetic analysis of DCE-CT data for patients with cervical cancer.

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Xu Y, Sun H, Song A, Yang Q, Lu X, Wang W. Predictive Significance of Tumor Grade Using 256-Slice CT Whole-Tumor Perfusion Imaging in Colorectal Adenocarcinoma. Acad Radiol 2015;22:1529-35. [PMID: 26421473 DOI: 10.1016/j.acra.2015.08.023] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2014] [Revised: 08/27/2015] [Accepted: 08/31/2015] [Indexed: 12/14/2022]

Prezzi D, Khan A, Goh V. Perfusion CT imaging of treatment response in oncology. Eur J Radiol 2015;84:2380-5. [PMID: 25864440 DOI: 10.1016/j.ejrad.2015.03.022] [Citation(s) in RCA: 35] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2014] [Revised: 03/11/2015] [Accepted: 03/16/2015] [Indexed: 01/15/2023]

Dynamic volume perfusion computed tomography parameters versus RECIST for the prediction of outcome in lung cancer patients treated with conventional chemotherapy. J Thorac Oncol 2015;10:164-71. [PMID: 25247342 DOI: 10.1097/jto.0000000000000376] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]

Abstract

INTRODUCTION

To compare dynamic volume perfusion computed tomography (dVPCT) parameters with Response Evaluation Criteria in Solid Tumors (RECIST 1.1) for prediction of therapy response and overall survival (OS) in non-small-cell lung cancer (NSCLC) and small-cell lung cancer (SCLC) patients treated with conventional chemotherapy.

METHODS

A total of 173 lung cancer patients (131 men; 61 ± 10 years) undergoing dVPCT before (T1) and after chemotherapy (T2) and follow-up were prospectively included. dVPCT-derived blood flow, blood volume, mean transit time, and permeability (PERM) were assessed, compared between NSCLC and SCLC and patients' response to therapy was determined according to RECIST 1.1.

RESULTS

One hundred of one hundred and seventy-three patients underwent dVPCT at T1 and T2 within a median of 44 (range, 31-108) days. dVPCT values were differing in NSCLC and SCLC, but were not significantly differing between patients with partial response, stable, or progressive disease. Eighty-five patients (NSCLC = 72 and SCLC = 13) with a follow-up for greater than or equal to 6 months were analyzed for OS. Fifty-six of eighty-five patients died during follow-up. Receiver operating characteristic analysis determined T1/T2 with highest predictive values regarding OS for blood flow, blood volume, mean transit time, and permeability (area under the curve: 0.53, 0.61, 0.54, and 0.53, respectively, all p > 0.05). Kaplan-Meier statistics revealed OS of patient groups assigned according to dVPCT T1/T2 cutoff values was not differing for neither dVPCT parameter, whereas RECIST groups significantly differed in OS (p = 0.02). Cox proportional hazards regression determined progressive disease status to independently predict OS (p = 0.004), while none of the dVPCT parameters did so.

CONCLUSIONS

dVPCT values, differ between NSCLC and SCLC, are not related to RECIST 1.1 classification and do not improve OS prediction in lung cancer patients treated with conventional chemotherapy.

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