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Kratochvíla J, Jiřík R, Bartoš M, Standara M, Starčuk Z, Taxt T. Blind deconvolution decreases requirements on temporal resolution of DCE-MRI: Application to 2nd generation pharmacokinetic modeling. Magn Reson Imaging 2024; 109:238-248. [PMID: 38508292 DOI: 10.1016/j.mri.2024.03.019] [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: 08/07/2023] [Revised: 03/08/2024] [Accepted: 03/16/2024] [Indexed: 03/22/2024]
Abstract
PURPOSE Dynamic Contrast-Enhanced (DCE) MRI with 2nd generation pharmacokinetic models provides estimates of plasma flow and permeability surface-area product in contrast to the broadly used 1st generation models (e.g. the Tofts models). However, the use of 2nd generation models requires higher frequency with which the dynamic images are acquired (around 1.5 s per image). Blind deconvolution can decrease the demands on temporal resolution as shown previously for one of the 1st generation models. Here, the temporal-resolution requirements achievable for blind deconvolution with a 2nd generation model are studied. METHODS The 2nd generation model is formulated as the distributed-capillary adiabatic-tissue-homogeneity (DCATH) model. Blind deconvolution is based on Parker's model of the arterial input function. The accuracy and precision of the estimated arterial input functions and the perfusion parameters is evaluated on synthetic and real clinical datasets with different levels of the temporal resolution. RESULTS The estimated arterial input functions remained unchanged from their reference high-temporal-resolution estimates (obtained with the sampling interval around 1 s) when increasing the sampling interval up to about 5 s for synthetic data and up to 3.6-4.8 s for real data. Further increasing of the sampling intervals led to systematic distortions, such as lowering and broadening of the 1st pass peak. The resulting perfusion-parameter estimation error was below 10% for the sampling intervals up to 3 s (synthetic data), in line with the real data perfusion-parameter boxplots which remained unchanged up to the sampling interval 3.6 s. CONCLUSION We show that use of blind deconvolution decreases the demands on temporal resolution in DCE-MRI from about 1.5 s (in case of measured arterial input functions) to 3-4 s. This can be exploited in increased spatial resolution or larger organ coverage.
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Affiliation(s)
- Jiří Kratochvíla
- Czech Academy of Sciences, Institute of Scientific Instruments, Královopolská 147, 612 64 Brno, Czech Republic.
| | - Radovan Jiřík
- Czech Academy of Sciences, Institute of Scientific Instruments, Královopolská 147, 612 64 Brno, Czech Republic
| | - Michal Bartoš
- Czech Academy of Sciences, Institute of Information Technology and Automation, Pod Vodárenskou věží 4, 182 08 Praha 8, Czech Republic
| | - Michal Standara
- Department of Radiology, Masaryk Memorial Cancer Institute, Žlutý kopec 7, 656 53 Brno, Czech Republic
| | - Zenon Starčuk
- Czech Academy of Sciences, Institute of Scientific Instruments, Královopolská 147, 612 64 Brno, Czech Republic
| | - Torfinn Taxt
- Department of Biomedicine, University of Bergen, Jonas Lies vei 91, Bergen, Norway
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Hoffmann E, Masthoff M, Kunz WG, Seidensticker M, Bobe S, Gerwing M, Berdel WE, Schliemann C, Faber C, Wildgruber M. Multiparametric MRI for characterization of the tumour microenvironment. Nat Rev Clin Oncol 2024; 21:428-448. [PMID: 38641651 DOI: 10.1038/s41571-024-00891-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/04/2024] [Indexed: 04/21/2024]
Abstract
Our understanding of tumour biology has evolved over the past decades and cancer is now viewed as a complex ecosystem with interactions between various cellular and non-cellular components within the tumour microenvironment (TME) at multiple scales. However, morphological imaging remains the mainstay of tumour staging and assessment of response to therapy, and the characterization of the TME with non-invasive imaging has not yet entered routine clinical practice. By combining multiple MRI sequences, each providing different but complementary information about the TME, multiparametric MRI (mpMRI) enables non-invasive assessment of molecular and cellular features within the TME, including their spatial and temporal heterogeneity. With an increasing number of advanced MRI techniques bridging the gap between preclinical and clinical applications, mpMRI could ultimately guide the selection of treatment approaches, precisely tailored to each individual patient, tumour and therapeutic modality. In this Review, we describe the evolving role of mpMRI in the non-invasive characterization of the TME, outline its applications for cancer detection, staging and assessment of response to therapy, and discuss considerations and challenges for its use in future medical applications, including personalized integrated diagnostics.
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Affiliation(s)
- Emily Hoffmann
- Clinic of Radiology, University of Münster, Münster, Germany
| | - Max Masthoff
- Clinic of Radiology, University of Münster, Münster, Germany
| | - Wolfgang G Kunz
- Department of Radiology, University Hospital, LMU Munich, Munich, Germany
| | - Max Seidensticker
- Department of Radiology, University Hospital, LMU Munich, Munich, Germany
| | - Stefanie Bobe
- Gerhard Domagk Institute of Pathology, University Hospital Münster, Münster, Germany
| | - Mirjam Gerwing
- Clinic of Radiology, University of Münster, Münster, Germany
| | | | | | - Cornelius Faber
- Clinic of Radiology, University of Münster, Münster, Germany
| | - Moritz Wildgruber
- Department of Radiology, University Hospital, LMU Munich, Munich, Germany.
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Treatment Assessment of pNET and NELM after Everolimus by Quantitative MRI Parameters. Biomedicines 2022; 10:biomedicines10102618. [PMID: 36289880 PMCID: PMC9599819 DOI: 10.3390/biomedicines10102618] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2022] [Revised: 10/01/2022] [Accepted: 10/11/2022] [Indexed: 11/17/2022] Open
Abstract
Assessment of treatment response to targeted therapies such as everolimus is difficult, especially in slow-growing tumors such as NETs. In this retrospective study, 17 patients with pancreatic neuroendocrine tumors (pNETs) and hepatic metastases (NELMs) (42 target lesions) who received everolimus were analyzed. Intralesional signal intensities (SI) of non-contrast T1w, T2w and DCE imaging, and apparent diffusion coefficients (ADCmean and ADCmin) of DWI, were measured on baseline and first follow-up MRI after everolimus initiation. Response assessment was categorized according to progression-free survival (PFS), with responders (R) showing a PFS of ≥11 months. ADCmin of NELMs decreased in Rs whereas it increased in non-responders (NR). Percentual changes of ADCmin and ADCmean differed significantly between response groups (p < 0.03). By contrast, ADC of the pNETs tended to increase in Rs, while there was no change in NRs. Tumor-to-liver (T/L) ratio of T1 SI of NELMs increased in Rs and decreased in NRs, and percentual changes differed significantly between response groups (p < 0.02). T1 SI of the pNETs tended to decrease in Rs and increase in Ns. The quotient of pretherapeutic and posttherapeutic ADCmin values (DADCmin) and length of everolimus treatment showed significant association with PFS in univariable Cox analysis. In conclusion, quantitative MRI, especially DWI, seems to allow treatment assessment of pNETs with NELMs under everolimus. Interestingly, the responding NELMs showed decreasing ADC values, and there might be an opposite effect on ADC and T1 SI between NELMs and pNETs.
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Stewart GD, Welsh SJ, Ursprung S, Gallagher FA, Jones JO, Shields J, Smith CG, Mitchell TJ, Warren AY, Bex A, Boleti E, Carruthers J, Eisen T, Fife K, Hamid A, Laird A, Leung S, Malik J, Mendichovszky IA, Mumtaz F, Oades G, Priest AN, Riddick ACP, Venugopal B, Welsh M, Riddle K, Hopcroft LEM, Jones RJ. A Phase II study of neoadjuvant axitinib for reducing the extent of venous tumour thrombus in clear cell renal cell cancer with venous invasion (NAXIVA). Br J Cancer 2022; 127:1051-1060. [PMID: 35739300 PMCID: PMC9470559 DOI: 10.1038/s41416-022-01883-7] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Revised: 05/25/2022] [Accepted: 06/01/2022] [Indexed: 11/08/2022] Open
Abstract
BACKGROUND Surgery for renal cell carcinoma (RCC) with venous tumour thrombus (VTT) extension into the renal vein (RV) and/or inferior vena cava (IVC) has high peri-surgical morbidity/mortality. NAXIVA assessed the response of VTT to axitinib, a potent tyrosine kinase inhibitor. METHODS NAXIVA was a single-arm, multi-centre, Phase 2 study. In total, 20 patients with resectable clear cell RCC and VTT received upto 8 weeks of pre-surgical axitinib. The primary endpoint was percentage of evaluable patients with VTT improvement by Mayo level on MRI. Secondary endpoints were percentage change in surgical approach and VTT length, response rate (RECISTv1.1) and surgical morbidity. RESULTS In all, 35% (7/20) patients with VTT had a reduction in Mayo level with axitinib: 37.5% (6/16) with IVC VTT and 25% (1/4) with RV-only VTT. No patients had an increase in Mayo level. In total, 75% (15/20) of patients had a reduction in VTT length. Overall, 41.2% (7/17) of patients who underwent surgery had less invasive surgery than originally planned. Non-responders exhibited lower baseline microvessel density (CD31), higher Ki67 and exhausted or regulatory T-cell phenotype. CONCLUSIONS NAXIVA provides the first Level II evidence that axitinib downstages VTT in a significant proportion of patients leading to reduction in the extent of surgery. CLINICAL TRIAL REGISTRATION NCT03494816.
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Affiliation(s)
- Grant D Stewart
- University of Cambridge, Cambridge, UK.
- Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK.
| | - Sarah J Welsh
- University of Cambridge, Cambridge, UK
- Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | | | - Ferdia A Gallagher
- University of Cambridge, Cambridge, UK
- Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - James O Jones
- University of Cambridge, Cambridge, UK
- Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
- MRC Cancer Unit, University of Cambridge, Cambridge, UK
| | - Jacqui Shields
- MRC Cancer Unit, University of Cambridge, Cambridge, UK
- School of Cancer and Pharmaceutical Sciences, King's College London, London, UK
| | | | - Thomas J Mitchell
- University of Cambridge, Cambridge, UK
- Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
- Wellcome Sanger Institute, Cambridge, UK
| | - Anne Y Warren
- University of Cambridge, Cambridge, UK
- Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Axel Bex
- Royal Free London NHS Foundation Trust, London, UK
| | | | - Jade Carruthers
- Scottish Clinical Trials Research Unit, Public Health Scotland, Edinburgh, UK
| | - Tim Eisen
- University of Cambridge, Cambridge, UK
- Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Kate Fife
- Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | | | - Alexander Laird
- Western General Hospital, Edinburgh, UK
- Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | | | | | - Iosif A Mendichovszky
- University of Cambridge, Cambridge, UK
- Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Faiz Mumtaz
- Royal Free London NHS Foundation Trust, London, UK
| | | | - Andrew N Priest
- University of Cambridge, Cambridge, UK
- Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | | | - Balaji Venugopal
- NHS Greater Glasgow and Clyde, Glasgow, UK
- University of Glasgow, Glasgow, UK
| | - Michelle Welsh
- Scottish Clinical Trials Research Unit, Public Health Scotland, Edinburgh, UK
| | - Kathleen Riddle
- Scottish Clinical Trials Research Unit, Public Health Scotland, Edinburgh, UK
| | - Lisa E M Hopcroft
- Scottish Clinical Trials Research Unit, Public Health Scotland, Edinburgh, UK
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Robert J Jones
- NHS Greater Glasgow and Clyde, Glasgow, UK
- University of Glasgow, Glasgow, UK
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Bhaduri S, Lesbats C, Sharkey J, Kelly CL, Mukherjee S, Taylor A, Delikatny EJ, Kim SG, Poptani H. Assessing Tumour Haemodynamic Heterogeneity and Response to Choline Kinase Inhibition Using Clustered Dynamic Contrast Enhanced MRI Parameters in Rodent Models of Glioblastoma. Cancers (Basel) 2022; 14:cancers14051223. [PMID: 35267531 PMCID: PMC8909848 DOI: 10.3390/cancers14051223] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2021] [Revised: 02/16/2022] [Accepted: 02/23/2022] [Indexed: 12/04/2022] Open
Abstract
To investigate the utility of DCE-MRI derived pharmacokinetic parameters in evaluating tumour haemodynamic heterogeneity and treatment response in rodent models of glioblastoma, imaging was performed on intracranial F98 and GL261 glioblastoma bearing rodents. Clustering of the DCE-MRI-based parametric maps (using Tofts, extended Tofts, shutter speed, two-compartment, and the second generation shutter speed models) was performed using a hierarchical clustering algorithm, resulting in areas with poor fit (reflecting necrosis), low, medium, and high valued pixels representing parameters Ktrans, ve, Kep, vp, τi and Fp. There was a significant increase in the number of necrotic pixels with increasing tumour volume and a significant correlation between ve and tumour volume suggesting increased extracellular volume in larger tumours. In terms of therapeutic response in F98 rat GBMs, a sustained decrease in permeability and perfusion and a reduced cell density was observed during treatment with JAS239 based on Ktrans, Fp and ve as compared to control animals. No significant differences in these parameters were found for the GL261 tumour, indicating that this model may be less sensitive to JAS239 treatment regarding changes in vascular parameters. This study demonstrates that region-based clustered pharmacokinetic parameters derived from DCE-MRI may be useful in assessing tumour haemodynamic heterogeneity with the potential for assessing therapeutic response.
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Affiliation(s)
- Sourav Bhaduri
- Centre for Preclinical Imaging, Department of Molecular and Clinical Cancer Medicine, University of Liverpool, Liverpool L69 3BX, UK; (S.B.); (C.L.); (J.S.); (C.L.K.); (S.M.)
| | - Clémentine Lesbats
- Centre for Preclinical Imaging, Department of Molecular and Clinical Cancer Medicine, University of Liverpool, Liverpool L69 3BX, UK; (S.B.); (C.L.); (J.S.); (C.L.K.); (S.M.)
- Division of Radiotherapy and Imaging, The Institute of Cancer Research, London SM2 5NG, UK
| | - Jack Sharkey
- Centre for Preclinical Imaging, Department of Molecular and Clinical Cancer Medicine, University of Liverpool, Liverpool L69 3BX, UK; (S.B.); (C.L.); (J.S.); (C.L.K.); (S.M.)
| | - Claire Louise Kelly
- Centre for Preclinical Imaging, Department of Molecular and Clinical Cancer Medicine, University of Liverpool, Liverpool L69 3BX, UK; (S.B.); (C.L.); (J.S.); (C.L.K.); (S.M.)
| | - Soham Mukherjee
- Centre for Preclinical Imaging, Department of Molecular and Clinical Cancer Medicine, University of Liverpool, Liverpool L69 3BX, UK; (S.B.); (C.L.); (J.S.); (C.L.K.); (S.M.)
| | - Arthur Taylor
- Department of Molecular Physiology & Cell Signalling, University of Liverpool, Liverpool L69 3BX, UK;
| | - Edward J. Delikatny
- Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA;
| | - Sungheon G. Kim
- Department of Radiology, Weill Cornell Medical College, New York, NY 10021, USA;
| | - Harish Poptani
- Centre for Preclinical Imaging, Department of Molecular and Clinical Cancer Medicine, University of Liverpool, Liverpool L69 3BX, UK; (S.B.); (C.L.); (J.S.); (C.L.K.); (S.M.)
- Correspondence:
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