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Bai B, Cui L, Chu F, Wang Z, Zhao K, Wang S, Wang S, Yan X, Wang M, Kamel IR, Yang G, Qu J. Multiple diffusion models for predicting pathologic response of esophageal squamous cell carcinoma to neoadjuvant chemotherapy. Abdom Radiol (NY) 2024:10.1007/s00261-024-04474-7. [PMID: 38954001 DOI: 10.1007/s00261-024-04474-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2024] [Revised: 06/22/2024] [Accepted: 06/24/2024] [Indexed: 07/04/2024]
Abstract
BACKGROUND To assess the feasibility and diagnostic performance of the fractional order calculus (FROC), continuous-time random-walk (CTRW), diffusion kurtosis imaging (DKI), intravoxel incoherent motion (IVIM), mono-exponential (MEM) and stretched exponential models (SEM) for predicting response to neoadjuvant chemotherapy (NACT) in patients with esophageal squamous cell carcinoma (ESCC). MATERIALS AND METHODS This study prospectively included consecutive ESCC patients with baseline and follow up MR imaging and pathologically confirmed cT1-4aN + M0 or T3-4aN0M0 and underwent radical resection after neoadjuvant chemotherapy (NACT) between July 2019 and January 2023. Patients were divided into pCR (TRG 0) and non-pCR (TRG1 + 2 + 3) groups according to tumor regression grading (TRG). The Pre-, Post- and Delta-treatment models were built. 18 predictive models were generated according to different feature categories, based on six models by five-fold cross-validation. Areas under the curve (AUCs) of the models were compared by using DeLong method. RESULTS Overall, 90 patients (71 men, 19 women; mean age, 64 years ± 6 [SD]) received NACT and underwent baseline and Post-NACT esophageal MRI, with 29 patients in the pCR group and 61 patients in the non-pCR group. Among 18 predictive models, The Pre-, Post-, and Delta-CTRW model showed good predictive efficacy (AUC = 0.722, 0.833 and 0.790). Additionally, the Post-FROC model (AUC = 0.907) also exhibited good diagnostic performance. CONCLUSIONS Our study indicates that the CTRW model, along with the Post-FROC model, holds significant promise for the future of NACT efficacy prediction in ESCC patients.
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Affiliation(s)
- Bingmei Bai
- Department of Radiology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, No. 127 Dongming Road, Zhengzhou, 450008, Henan, China
| | - Long Cui
- Shanghai Key Laboratory of Magnetic Resonance, East China Normal University, Shanghai, 200062, China
| | - Funing Chu
- Department of Radiology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, No. 127 Dongming Road, Zhengzhou, 450008, Henan, China
| | - Zhaoqi Wang
- Department of Radiology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, No. 127 Dongming Road, Zhengzhou, 450008, Henan, China
| | - Keke Zhao
- Department of Radiology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, No. 127 Dongming Road, Zhengzhou, 450008, Henan, China
| | - Shuting Wang
- Department of Radiology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, No. 127 Dongming Road, Zhengzhou, 450008, Henan, China
| | - Shaoyu Wang
- MR Scientific Marketing, Siemens Healthineers, Shanghai, 201318, China
| | - Xu Yan
- MR Scientific Marketing, Siemens Healthineers, Shanghai, 201318, China
| | - Mengzhu Wang
- MR Research Collaboration, Siemens Healthineers Ltd, Beijing, 100000, China
| | - Ihab R Kamel
- Department of Radiology, Anschutz Medical Campus, University of Colorado Denver, 12401 East 17Th Avenue, Aurora, CO, 80045, USA
| | - Guang Yang
- Shanghai Key Laboratory of Magnetic Resonance, East China Normal University, Shanghai, 200062, China
| | - Jinrong Qu
- Department of Radiology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, No. 127 Dongming Road, Zhengzhou, 450008, Henan, China.
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van Timmeren JE, Bussink J, Koopmans P, Smeenk RJ, Monshouwer R. Longitudinal Image Data for Outcome Modeling. Clin Oncol (R Coll Radiol) 2024:S0936-6555(24)00277-2. [PMID: 39003124 DOI: 10.1016/j.clon.2024.06.053] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2023] [Revised: 04/15/2024] [Accepted: 06/24/2024] [Indexed: 07/15/2024]
Abstract
In oncology, medical imaging is crucial for diagnosis, treatment planning and therapy execution. Treatment responses can be complex and varied and are known to involve factors of treatment, patient characteristics and tumor microenvironment. Longitudinal image analysis is able to track temporal changes, aiding in disease monitoring, treatment evaluation, and outcome prediction. This allows for the enhancement of personalized medicine. However, analyzing longitudinal 2D and 3D images presents unique challenges, including image registration, reliable segmentation, dealing with variable imaging intervals, and sparse data. This review presents an overview of techniques and methodologies in longitudinal image analysis, with a primary focus on outcome modeling in radiation oncology.
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Affiliation(s)
- J E van Timmeren
- Department of Radiation Oncology, Radboud University Medical Center, Nijmegen, the Netherlands.
| | - J Bussink
- Department of Radiation Oncology, Radboud University Medical Center, Nijmegen, the Netherlands.
| | - P Koopmans
- Department of Radiation Oncology, Radboud University Medical Center, Nijmegen, the Netherlands.
| | - R J Smeenk
- Department of Radiation Oncology, Radboud University Medical Center, Nijmegen, the Netherlands.
| | - R Monshouwer
- Department of Radiation Oncology, Radboud University Medical Center, Nijmegen, the Netherlands.
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Kim JY, Tawk B, Knoll M, Hoegen-Saßmannshausen P, Liermann J, Huber PE, Lifferth M, Lang C, Häring P, Gnirs R, Jäkel O, Schlemmer HP, Debus J, Hörner-Rieber J, Weykamp F. Clinical Workflow of Cone Beam Computer Tomography-Based Daily Online Adaptive Radiotherapy with Offline Magnetic Resonance Guidance: The Modular Adaptive Radiotherapy System (MARS). Cancers (Basel) 2024; 16:1210. [PMID: 38539544 PMCID: PMC10969008 DOI: 10.3390/cancers16061210] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2024] [Revised: 03/07/2024] [Accepted: 03/15/2024] [Indexed: 05/03/2024] Open
Abstract
PURPOSE The Ethos (Varian Medical Systems) radiotherapy device combines semi-automated anatomy detection and plan generation for cone beam computer tomography (CBCT)-based daily online adaptive radiotherapy (oART). However, CBCT offers less soft tissue contrast than magnetic resonance imaging (MRI). This work aims to present the clinical workflow of CBCT-based oART with shuttle-based offline MR guidance. METHODS From February to November 2023, 31 patients underwent radiotherapy on the Ethos (Varian, Palo Alto, CA, USA) system with machine learning (ML)-supported daily oART. Moreover, patients received weekly MRI in treatment position, which was utilized for daily plan adaptation, via a shuttle-based system. Initial and adapted treatment plans were generated using the Ethos treatment planning system. Patient clinical data, fractional session times (MRI + shuttle transport + positioning, adaptation, QA, RT delivery) and plan selection were assessed for all fractions in all patients. RESULTS In total, 737 oART fractions were applied and 118 MRIs for offline MR guidance were acquired. Primary sites of tumors were prostate (n = 16), lung (n = 7), cervix (n = 5), bladder (n = 1) and endometrium (n = 2). The treatment was completed in all patients. The median MRI acquisition time including shuttle transport and positioning to initiation of the Ethos adaptive session was 53.6 min (IQR 46.5-63.4). The median total treatment time without MRI was 30.7 min (IQR 24.7-39.2). Separately, median adaptation, plan QA and RT times were 24.3 min (IQR 18.6-32.2), 0.4 min (IQR 0.3-1,0) and 5.3 min (IQR 4.5-6.7), respectively. The adapted plan was chosen over the scheduled plan in 97.7% of cases. CONCLUSION This study describes the first workflow to date of a CBCT-based oART combined with a shuttle-based offline approach for MR guidance. The oART duration times reported resemble the range shown by previous publications for first clinical experiences with the Ethos system.
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Affiliation(s)
- Ji-Young Kim
- Department of Radiation Oncology, Heidelberg University Hospital, 69120 Heidelberg, Germany
- Heidelberg Institute of Radiation Oncology (HIRO), 69120 Heidelberg, Germany
- Clinical Cooperation Unit Radiation Oncology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
- National Center for Tumor Diseases (NCT), 69120 Heidelberg, Germany
| | - Bouchra Tawk
- Department of Radiation Oncology, Heidelberg University Hospital, 69120 Heidelberg, Germany
- Heidelberg Institute of Radiation Oncology (HIRO), 69120 Heidelberg, Germany
- Clinical Cooperation Unit Radiation Oncology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
- National Center for Tumor Diseases (NCT), 69120 Heidelberg, Germany
- Clinical Cooperation Unit Translational Radiation Oncology, National Center for Tumor Diseases (NCT), Heidelberg University Hospital (UKHD) and German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
| | - Maximilian Knoll
- Department of Radiation Oncology, Heidelberg University Hospital, 69120 Heidelberg, Germany
- Heidelberg Institute of Radiation Oncology (HIRO), 69120 Heidelberg, Germany
- Clinical Cooperation Unit Radiation Oncology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
- National Center for Tumor Diseases (NCT), 69120 Heidelberg, Germany
- Clinical Cooperation Unit Translational Radiation Oncology, National Center for Tumor Diseases (NCT), Heidelberg University Hospital (UKHD) and German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
- German Cancer Consortium (DKTK), Core Center Heidelberg, 69120 Heidelberg, Germany
| | - Philipp Hoegen-Saßmannshausen
- Department of Radiation Oncology, Heidelberg University Hospital, 69120 Heidelberg, Germany
- Heidelberg Institute of Radiation Oncology (HIRO), 69120 Heidelberg, Germany
- Clinical Cooperation Unit Radiation Oncology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
- National Center for Tumor Diseases (NCT), 69120 Heidelberg, Germany
| | - Jakob Liermann
- Department of Radiation Oncology, Heidelberg University Hospital, 69120 Heidelberg, Germany
- Heidelberg Institute of Radiation Oncology (HIRO), 69120 Heidelberg, Germany
- Clinical Cooperation Unit Radiation Oncology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
- National Center for Tumor Diseases (NCT), 69120 Heidelberg, Germany
| | - Peter E. Huber
- Department of Radiation Oncology, Heidelberg University Hospital, 69120 Heidelberg, Germany
- Heidelberg Institute of Radiation Oncology (HIRO), 69120 Heidelberg, Germany
- Clinical Cooperation Unit Radiation Oncology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
- National Center for Tumor Diseases (NCT), 69120 Heidelberg, Germany
- Clinical Cooperation Unit Molecular Radiooncology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
| | - Mona Lifferth
- Division of Medical Physics in Radiation Oncology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
| | - Clemens Lang
- Division of Medical Physics in Radiation Oncology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
| | - Peter Häring
- Division of Medical Physics in Radiation Oncology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
| | - Regula Gnirs
- Division of Radiology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
| | - Oliver Jäkel
- Heidelberg Institute of Radiation Oncology (HIRO), 69120 Heidelberg, Germany
- Clinical Cooperation Unit Molecular Radiooncology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
- Department of Radiation Oncology, Heidelberg Ion-Beam Therapy Center (HIT), Heidelberg University Hospital, 69120 Heidelberg, Germany
| | - Heinz-Peter Schlemmer
- Division of Radiology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
| | - Jürgen Debus
- Department of Radiation Oncology, Heidelberg University Hospital, 69120 Heidelberg, Germany
- Heidelberg Institute of Radiation Oncology (HIRO), 69120 Heidelberg, Germany
- Clinical Cooperation Unit Radiation Oncology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
- National Center for Tumor Diseases (NCT), 69120 Heidelberg, Germany
- Department of Radiation Oncology, Heidelberg Ion-Beam Therapy Center (HIT), Heidelberg University Hospital, 69120 Heidelberg, Germany
| | - Juliane Hörner-Rieber
- Department of Radiation Oncology, Heidelberg University Hospital, 69120 Heidelberg, Germany
- Heidelberg Institute of Radiation Oncology (HIRO), 69120 Heidelberg, Germany
- Clinical Cooperation Unit Radiation Oncology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
- National Center for Tumor Diseases (NCT), 69120 Heidelberg, Germany
| | - Fabian Weykamp
- Department of Radiation Oncology, Heidelberg University Hospital, 69120 Heidelberg, Germany
- Heidelberg Institute of Radiation Oncology (HIRO), 69120 Heidelberg, Germany
- Clinical Cooperation Unit Radiation Oncology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
- National Center for Tumor Diseases (NCT), 69120 Heidelberg, Germany
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Mesny E, Leporq B, Chapet O, Beuf O. Towards tumour hypoxia imaging: Incorporating relative oxygen extraction fraction mapping of prostate with multi-parametric quantitative MRI on a 1.5T MR-linac. J Med Imaging Radiat Oncol 2024. [PMID: 38415384 DOI: 10.1111/1754-9485.13626] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Accepted: 02/03/2024] [Indexed: 02/29/2024]
Abstract
Hypoxia plays a central role in tumour radioresistance. Reliable tumour hypoxia imaging would allow the monitoring of tumour response and a more personalized adaptation of radiotherapy planning. Here, we showed a proof of concept of the feasibility and repeatability of relative oxygen extraction fraction (rOEF) mapping of prostate using multi-parametric quantitative MRI (qMRI) achieved for the first time on a 1.5T MR-linac. T2, T2* relaxation times maps, and intra-voxel incoherent motion (IVIM) parametric maps mapping were computed on a 29 years old healthy volunteer. R2' and rOEF maps were calculated based on a multi-parametric model. Long-term repeatability and repeatability coefficient (RC) were determined for each parameter according to QIBA recommendations. Mean values for the entire healthy prostate were 0.99 ± 0.14 × 10-3 mm/s2 , 81 ± 2.1 × 10-3 mm/s2 , 21.6 ± 3.6%, 92.7 ± 19.7 ms and 62.4 ± 17.3 ms for Dslow , Dfast , f, T2 and T2*, respectively. R2' and rOEF in the prostate were 6.1 ± 3.4 s-1 and 18.2 ± 10.1% respectively. The RC of rOEF was 4.43%. Long-term repeatability of quantitative parameters based on a test-retest ranged from 2 to 18%. qMRI parameters are measurable and repeatable on 1.5T MR LINAC. From T2, T2* and IVIM parameters maps, we were able to obtain a rOEF mapping of the prostate. These results are the first step to a non-invasive imaging of tumour hypoxia during radiotherapy leading to a biological image-guided adaptive radiotherapy.
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Affiliation(s)
- Emmanuel Mesny
- Univ Lyon, INSA-Lyon, Université Claude Bernard Lyon 1, CNRS, Inserm, CREATIS UMR 5220, U1294, Lyon, France
- Radiation Oncology Department, Center Hospitalier Lyon Sud, Lyon, France
| | - Benjamin Leporq
- Univ Lyon, INSA-Lyon, Université Claude Bernard Lyon 1, CNRS, Inserm, CREATIS UMR 5220, U1294, Lyon, France
| | - Olivier Chapet
- Radiation Oncology Department, Center Hospitalier Lyon Sud, Lyon, France
- Université Claude Bernard Lyon 1, Lyon, France
| | - Olivier Beuf
- Univ Lyon, INSA-Lyon, Université Claude Bernard Lyon 1, CNRS, Inserm, CREATIS UMR 5220, U1294, Lyon, France
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5
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Yuan Q, Recchimuzzi DZ, Costa DN. Magnetic Resonance Perfusion Imaging of Prostate. Magn Reson Imaging Clin N Am 2024; 32:171-179. [PMID: 38007279 DOI: 10.1016/j.mric.2023.09.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2023]
Abstract
Magnetic resonance (MR) perfusion imaging, both with and without exogenous contrast agents, has the potential to assess tissue perfusion and vascularity in prostate cancer. Dynamic contrast-enhanced (DCE) MRI is an important element of the clinical non-invasive multiparametric MRI, which can be used to differentiate benign from malignant lesions, to stage tumors, and to monitor response to therapy. The arterial spin labeled (ASL) and intravoxel incoherent motion (IVIM) diffusion-weighted MRI have the advantage of quantitative perfusion measurements without the concerns of gadolinium-based contrast agent safety and retention issues. The adoption of these non-contrast techniques in clinical practice needs more research and clinical evaluation.
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Affiliation(s)
- Qing Yuan
- Department of Radiology, University of Texas Southwestern Medical Center, 5323 Harry Hines Boulevard, Dallas, TX 75390, USA.
| | - Debora Z Recchimuzzi
- Department of Radiology, University of Texas Southwestern Medical Center, 5323 Harry Hines Boulevard, Dallas, TX 75390, USA
| | - Daniel N Costa
- Department of Radiology, University of Texas Southwestern Medical Center, 5323 Harry Hines Boulevard, Dallas, TX 75390, USA; Department of Urology, University of Texas Southwestern Medical Center, 2201 Inwood Road, TX 75390, USA
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Habrich J, Boeke S, Fritz V, Koerner E, Nikolaou K, Schick F, Gani C, Zips D, Thorwarth D. Reproducibility of diffusion-weighted magnetic resonance imaging in head and neck cancer assessed on a 1.5 T MR-Linac and comparison to parallel measurements on a 3 T diagnostic scanner. Radiother Oncol 2024; 191:110046. [PMID: 38070687 DOI: 10.1016/j.radonc.2023.110046] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Revised: 11/27/2023] [Accepted: 12/03/2023] [Indexed: 02/02/2024]
Abstract
BACKGROUND AND PURPOSE Before quantitative imaging biomarkers (QIBs) acquired with magnetic resonance imaging (MRI) can be used for interventional trials in radiotherapy (RT), technical validation of these QIBs is necessary. The aim of this study was to assess the reproducibility of apparent diffusion coefficient (ADC) values, derived from diffusion-weighted (DW) MRI, in head and neck cancer using a 1.5 T MR-Linac (MRL) by comparison to a 3 T diagnostic scanner (DS). MATERIAL AND METHODS DW-MRIs were acquired on MRL and DS for 15 head and neck cancer patients before RT and in week 2 and rigidly registered to the planning computed tomography. Mean ADC values were calculated for submandibular (SG) and parotid (PG) glands as well as target volumes (TV, gross tumor volume and lymph nodes), which were delineated based on computed tomography. Mean absolute ADC differences as well as within-subject coefficient of variation (wCV) and intraclass correlation coefficients (ICCs) were calculated for all volumes of interest. RESULTS A total of 23 datasets were analyzed. Mean ADC difference (DS-MRL) for SG, PG and TV resulted in 142, 254 and 93·10-6 mm2/s. wCVs/ICCs, comparing MRL and DS, were determined as 13.7 %/0.26, 24.4 %/0.23 and 16.1 %/0.73 for SG, PG and TV, respectively. CONCLUSION ADC values, measured on the 1.5 T MRL, showed reasonable reproducibility with an ADC underestimation in contrast to the DS. This ADC shift must be validated in further experiments and considered for future translation of QIB candidates from DS to MRL for response adaptive RT.
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Affiliation(s)
- Jonas Habrich
- Section for Biomedical Physics, Department of Radiation Oncology, University Hospital Tübingen, Tübingen, Germany.
| | - Simon Boeke
- German Cancer Consortium (DKTK), partner site Tübingen, and German Cancer Research Center (DKFZ), Heidelberg, Germany; Department of Radiation Oncology, University Hospital Tübingen, Tübingen, Germany
| | - Victor Fritz
- Section for Experimental Radiology, Department of Diagnostic and Interventional Radiology, University of Tübingen, Germany
| | - Elisa Koerner
- Section for Biomedical Physics, Department of Radiation Oncology, University Hospital Tübingen, Tübingen, Germany
| | - Konstantin Nikolaou
- Department of Diagnostic and Interventional Radiology, University of Tübingen, Germany
| | - Fritz Schick
- Section for Experimental Radiology, Department of Diagnostic and Interventional Radiology, University of Tübingen, Germany
| | - Cihan Gani
- Department of Radiation Oncology, University Hospital Tübingen, Tübingen, Germany
| | - Daniel Zips
- German Cancer Consortium (DKTK), partner site Tübingen, and German Cancer Research Center (DKFZ), Heidelberg, Germany; Department of Radiation Oncology, University Hospital Tübingen, Tübingen, Germany; Department of Radiation Oncology, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Daniela Thorwarth
- Section for Biomedical Physics, Department of Radiation Oncology, University Hospital Tübingen, Tübingen, Germany; German Cancer Consortium (DKTK), partner site Tübingen, and German Cancer Research Center (DKFZ), Heidelberg, Germany
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Abstract
Magnetic resonance imaging-guided radiation therapy (MRIgRT) has improved soft tissue contrast over computed tomography (CT) based image-guided RT. Superior visualization of the target and surrounding radiosensitive structures has the potential to improve oncological outcomes partly due to safer dose-escalation and adaptive planning. In this review, we highlight the workflow of adaptive MRIgRT planning, which includes simulation imaging, daily MRI, identifying isocenter shifts, contouring, plan optimization, quality control, and delivery. Increased utilization of MRIgRT will depend on addressing technical limitations of this technology, while addressing treatment efficacy, cost-effectiveness, and workflow training.
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Affiliation(s)
- Cecil M Benitez
- Department of Radiation Oncology, UCLA Medical Center, Los Angeles, CA
| | - Michael D Chuong
- Department of Radiation Oncology, Miami Cancer Institute, Baptist Health South Florida; Miami, FL
| | - Luise A Künzel
- National Center for Tumor Diseases (NCT), Dresden; German Cancer Research Center (DKFZ), Heidelberg; Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden; Helmholtz-Zentrum Dresden - Rossendorf (HZDR), Dresden, Germany; Department of Radiotherapy and Radiation Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany.; OncoRay-National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden Rossendorf, Dresden, Germany
| | - Daniela Thorwarth
- Department of Radiation Oncology, Section for Biomedical Physics, University of Tübingen, Tübingen, Germany..
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van Houdt PJ, Li S, Yang Y, van der Heide UA. Quantitative MRI on MR-Linacs: Towards Biological Image-Guided Adaptive Radiotherapy. Semin Radiat Oncol 2024; 34:107-119. [PMID: 38105085 DOI: 10.1016/j.semradonc.2023.10.010] [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: 12/19/2023]
Abstract
Recognizing the potential of quantitative imaging biomarkers (QIBs) in radiotherapy, many studies have investigated the prognostic value of quantitative MRI (qMRI). With the introduction of MRI-guided radiotherapy systems, the practical challenges of repeated imaging have been substantially reduced. Since patients are treated inside an MRI scanner, acquisition of qMRI can be done during each fraction with limited or no prolongation of the fraction duration. In this review paper, we identify the steps that need been taken to move from MR as an imaging technique to a useful biomarker for MRI-guided radiotherapy (MRgRT).
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Affiliation(s)
- Petra J van Houdt
- Department of Radiation Oncology, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Shaolei Li
- SJTU-Ruijing, UIH Institute for Medical Imaging Technology, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.; Department of Radiology, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Yingli Yang
- SJTU-Ruijing, UIH Institute for Medical Imaging Technology, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.; Department of Radiology, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Uulke A van der Heide
- Department of Radiation Oncology, The Netherlands Cancer Institute, Amsterdam, The Netherlands..
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Almansour H, Schick F, Nachbar M, Afat S, Fritz V, Thorwarth D, Zips D, Bertram F, Müller AC, Nikolaou K, Othman AE, Wegener D. Longitudinal monitoring of Apparent Diffusion Coefficient (ADC) in patients with prostate cancer undergoing MR-guided radiotherapy on an MR-Linac at 1.5 T: a prospective feasibility study. Radiol Oncol 2023; 57:184-190. [PMID: 37341194 DOI: 10.2478/raon-2023-0020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Accepted: 03/30/2023] [Indexed: 06/22/2023] Open
Abstract
BACKGROUND Hybrid MRI linear accelerators (MR-Linac) might enable individualized online adaptation of radiotherapy using quantitative MRI sequences as diffusion-weighted imaging (DWI). The purpose of this study was to investigate the dynamics of lesion apparent diffusion coefficient (ADC) in patients with prostate cancer undergoing MR-guided radiation therapy (MRgRT) on a 1.5T MR-Linac. The ADC values at a diagnostic 3T MRI scanner were used as the reference standard. PATIENTS AND AND METHODS In this prospective single-center study, patients with biopsy-confirmed prostate cancer who underwent both an MRI exam at a 3T scanner (MRI3T) and an exam at a 1.5T MR-Linac (MRL) at baseline and during radiotherapy were included. Lesion ADC values were measured by a radiologist and a radiation oncologist on the slice with the largest lesion. ADC values were compared before vs. during radiotherapy (during the second week) on both systems via paired t-tests. Furthermore, Pearson correlation coefficient and inter-reader agreement were computed. RESULTS A total of nine male patients aged 67 ± 6 years [range 60 - 67 years] were included. In seven patients, the cancerous lesion was in the peripheral zone, and in two patients the lesion was in the transition zone. Inter-reader reliability regarding lesion ADC measurement was excellent with an intraclass correlation coefficient of (ICC) > 0.90 both at baseline and during radiotherapy. Thus, the results of the first reader will be reported. In both systems, there was a statistically significant elevation of lesion ADC during radiotherapy (mean MRL-ADC at baseline was 0.97 ± 0.18 × 10-3 mm2/s vs. mean MRL-ADC during radiotherapy 1.38 ± 0.3 × 10-3 mm2/s, yielding a mean lesion ADC elevation of 0.41 ± 0.20 × 10-3 mm2/s, p < 0.001). Mean MRI3T-ADC at baseline was 0.78 ± 0.165 × 10-3 mm2/s vs. mean MRI3T-ADC during radiotherapy 0.99 ± 0.175 × 10-3 mm2/s, yielding a mean lesion ADC elevation of 0.21 ± 0.96 × 10-3 mm2/s p < 0.001). The absolute ADC values from MRL were consistently significantly higher than those from MRI3T at baseline and during radiotherapy (p < = 0.001). However, there was a strong positive correlation between MRL-ADC and MRI3T-ADC at baseline (r = 0.798, p = 0.01) and during radiotherapy (r = 0.863, p = 0.003). CONCLUSIONS Lesion ADC as measured on MRL increased significantly during radiotherapy and ADC measurements of lesions on both systems showed similar dynamics. This indicates that lesion ADC as measured on the MRL may be used as a biomarker for evaluation of treatment response. In contrast, absolute ADC values as calculated by the algorithm of the manufacturer of the MRL showed systematic deviations from values obtained on a diagnostic 3T MRI system. These preliminary findings are promising but need large-scale validation. Once validated, lesion ADC on MRL might be used for real-time assessment of tumor response in patients with prostate cancer undergoing MR-guided radiation therapy.
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Affiliation(s)
- Haidara Almansour
- Department of Diagnostic and Interventional Radiology, Eberhard-Karls University, Tuebingen, Germany
| | - Fritz Schick
- Section for Experimental Radiology, Department of Radiology, Eberhard-Karls University, Tuebingen, Germany
| | - Marcel Nachbar
- Department of Radiation Oncology, Charité University Medicine Berlin, Berlin, Germany
- Section for Biomedical Physics, Department of Radiation Oncology, Eberhard-Karls University, Tuebingen, Germany
| | - Saif Afat
- Department of Diagnostic and Interventional Radiology, Eberhard-Karls University, Tuebingen, Germany
| | - Victor Fritz
- Section for Experimental Radiology, Department of Radiology, Eberhard-Karls University, Tuebingen, Germany
| | - Daniela Thorwarth
- Section for Biomedical Physics, Department of Radiation Oncology, Eberhard-Karls University, Tuebingen, Germany
- German Cancer Consortium (DKTK), Partner Site Tuebingen and German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Daniel Zips
- Department of Radiation Oncology, Charité University Medicine Berlin, Berlin, Germany
- German Cancer Consortium (DKTK), Partner Site Tuebingen and German Cancer Research Center (DKFZ), Heidelberg, Germany
- Department of Radiation Oncology, Eberhard-Karls University, Tuebingen, Germany
| | - Felix Bertram
- Department of Radiation Oncology, Eberhard-Karls University, Tuebingen, Germany
| | - Arndt-Christian Müller
- Department of Radiation Oncology, Eberhard-Karls University, Tuebingen, Germany
- Department of Radiation Oncology, RKH Klinikum Ludwigsburg, Ludwigsburg, Germany
| | - Konstantin Nikolaou
- Department of Diagnostic and Interventional Radiology, Eberhard-Karls University, Tuebingen, Germany
- Cluster of Excellence iFIT (EXC 2180) "Image Guided and Functionally Instructed Tumor Therapies", University of Tuebingen, Tuebingen, Germany
| | - Ahmed E Othman
- Department of Diagnostic and Interventional Radiology, Eberhard-Karls University, Tuebingen, Germany
- Department of Neuroradiology, University Medical Center Mainz, Mainz, Germany
| | - Daniel Wegener
- Department of Radiation Oncology, Eberhard-Karls University, Tuebingen, Germany
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Hu W, Chen L, Lin L, Wang J, Wang N, Liu A. Three-dimensional amide proton transfer-weighted and intravoxel incoherent motion imaging for predicting bone metastasis in patients with prostate cancer: A pilot study. Magn Reson Imaging 2023; 96:8-16. [PMID: 36375760 DOI: 10.1016/j.mri.2022.11.004] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2022] [Revised: 10/25/2022] [Accepted: 11/07/2022] [Indexed: 11/13/2022]
Abstract
PURPOSE To explore the value of 3-dimensional amide proton transfer-weighted (APTw) and intravoxel incoherent motion (IVIM) imaging in predicting bone metastasis (BM) of prostate cancer (PCa) in addition to routine diffusion-weighted imaging (DWI). METHODS The clinical and imaging data of 39 PCa patients who were pathologically confirmed in our hospital from March 2019 to February 2022 were retrospectively analyzed, and they were divided into BM-negative (27 patients) and BM-positive (12 patients) groups. MR examination included APTw, DWI and IVIM imaging. The IVIM data was fitted by single-exponential IVIM model (IVIMmono) and double-exponential IVIM model (IVIMbi), respectively. The APTw, ADC, IVIMmono (Dmono, D*mono, and fmono), and IVIMbi (Dbi, D*bi, and fbi) parameters were independently measured by two radiologists. The synthetic minority oversampling technique (SMOTE) was conducted to balance the minority group. Mann-Whitney U test or Student's t-test was used to compare above values between the BM-negative and BM-positive groups. The diagnostic performance was evaluated with receiver operating characteristic (ROC) analysis of each parameter and their combination. The Delong test was used for ROC curve comparison.The relationship between APTw and IVIM was explored through Spearman's rank correlation analysis. RESULTS The APTw and D*mono values were higher, and the ADC, fmono, and fbi values were lower in the BM-positive group than in the BM-negative group (all P < 0.05). Among the individual parameters, the AUC of fmono was the highest (AUC = 0.865), and AUC (fmono) was significantly higher than AUC (fbi), AUC (D*mono), and AUC (ADC) (all P < 0.05). The AUC (IVIMmono) was higher than the AUC (IVIMbi) (P = 0.0068). The combination of APTw and IVIMmono further improved diagnostic capability, and the AUC of APTw+IVIMmono was significantly higher than those of APTw and DWI (all P < 0.05). No correlation was found between IVIM-derived parameters and APTw value. CONCLUSION Both 3D APTw and IVIM imaging could predict BM of PCa. IVIM showed better performance than APTw and DWI, and the single-exponential IVIM model was superior to the double-exponential IVIM model. The combination of APTw and IVIM could further improve diagnostic performance.
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Affiliation(s)
- Wenjun Hu
- Department of Radiology, First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, 116011, PR China
| | - Lihua Chen
- Department of Radiology, First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, 116011, PR China; Dalian Engineering Research Center for Artificial Intelligence in Medical Imaging, Dalian, Liaoning, 116011, PR China
| | | | | | - Nan Wang
- Department of Radiology, First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, 116011, PR China; Dalian Engineering Research Center for Artificial Intelligence in Medical Imaging, Dalian, Liaoning, 116011, PR China
| | - Ailian Liu
- Department of Radiology, First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, 116011, PR China; Dalian Engineering Research Center for Artificial Intelligence in Medical Imaging, Dalian, Liaoning, 116011, PR China.
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