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Variability of radiotherapy volume delineation: PSMA PET/MRI and MRI based clinical target volume and lymph node target volume for high-risk prostate cancer. Cancer Imaging 2023; 23:1. [PMID: 36600283 DOI: 10.1186/s40644-022-00518-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Accepted: 12/25/2022] [Indexed: 01/06/2023] Open
Abstract
PURPOSE A comparative retrospective study to assess the impact of PSMA Ligand PET/MRI ([68 Ga]-Ga-PSMA-11 and [18F]-F-PSMA-1007 PET/MRI) as a new method of target delineation compared to conventional imaging on whole-pelvis radiotherapy for high-risk prostate cancer (PCa). PATIENTS AND METHODS Forty-nine patients with primary high-risk PCa completed the whole-pelvis radiotherapy plan based on PSMA PET/MRI and MRI. The primary endpoint compared the size and overlap of clinical target volume (CTV) and nodal gross tumour volume (GTVn) based on PSMA PET/MRI and MRI. The diagnostic performance of two methods for pelvic lymph node metastasis (PLNM) was evaluated. RESULTS In the radiotherapy planning for high-risk PCa patients, there was a significant correlation between MRI-CTV and PET/MRI-CTV (P = 0.005), as well as between MRI-GTVn and PET/MRI-GTVn (P < 0.001). There are non-significant differences in the CTV and GTVn based on MRI and PET/MRI images (P = 0.660, P = 0.650, respectively). The conformity index (CI), lesion coverage factor (LCF) and Dice similarity coefficient (DSC) of CTVs were 0.999, 0.953 and 0.954. The CI, LCF and DSC of GTVns were 0.927, 0.284, and 0.32. Based on pathological lymph node analysis of 463 lymph nodes from 37 patients, the sensitivity, specificity of PET/MRI in the diagnosis of PLNM were 77.78% and 99.76%, respectively, which were higher than those of MRI (P = 0.011). Eight high-risk PCa patients who finished PSMA PET/MRI changed their N or M stage. CONCLUSION The CTV delineated based on PET/MRI and MRI differ little. The GTVn delineated based on PET/MRI encompasses metastatic pelvic lymph nodes more accurately than MRI and avoids covering pelvic lymph nodes without metastasis. We emphasize the utility of PET/MRI fusion images in GTVn delineation in whole pelvic radiotherapy for PCa. The use of PSMA PET/MRI aids in the realization of more individual and precise radiotherapy for PCa.
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Decazes P, Hinault P, Veresezan O, Thureau S, Gouel P, Vera P. Trimodality PET/CT/MRI and Radiotherapy: A Mini-Review. Front Oncol 2021; 10:614008. [PMID: 33614497 PMCID: PMC7890017 DOI: 10.3389/fonc.2020.614008] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2020] [Accepted: 12/22/2020] [Indexed: 12/12/2022] Open
Abstract
Computed tomography (CT) has revolutionized external radiotherapy by making it possible to visualize and segment the tumors and the organs at risk in a three-dimensional way. However, if CT is a now a standard, it presents some limitations, notably concerning tumor characterization and delineation. Its association with functional and anatomical images, that are positron emission tomography (PET) and magnetic resonance imaging (MRI), surpasses its limits. This association can be in the form of a trimodality PET/CT/MRI. The objective of this mini-review is to describe the process of performing this PET/CT/MRI trimodality for radiotherapy and its potential clinical applications. Trimodality can be performed in two ways, either a PET/MRI fused to a planning CT (possibly with a pseudo-CT generated from the MRI for the planning), or a PET/CT fused to an MRI and then registered to a planning CT (possibly the CT of PET/CT if calibrated for radiotherapy). These examinations should be performed in the treatment position, and in the second case, a patient transfer system can be used between the PET/CT and MRI to limit movement. If trimodality requires adapted equipment, notably compatible MRI equipment with high-performance dedicated coils, it allows the advantages of the three techniques to be combined with a synergistic effect while limiting their disadvantages when carried out separately. Trimodality is already possible in clinical routine and can have a high clinical impact and good inter-observer agreement, notably for head and neck cancers, brain tumor, prostate cancer, cervical cancer.
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Affiliation(s)
- Pierre Decazes
- Nuclear Medicine Department, Henri Becquerel Cancer Center, Rouen, France
- QuantIF-LITIS EA4108, University of Rouen, Rouen, France
| | | | - Ovidiu Veresezan
- Radiotherapy Department, Henri Becquerel Cancer Center, Rouen, France
| | - Sébastien Thureau
- Nuclear Medicine Department, Henri Becquerel Cancer Center, Rouen, France
- QuantIF-LITIS EA4108, University of Rouen, Rouen, France
- Radiotherapy Department, Henri Becquerel Cancer Center, Rouen, France
| | - Pierrick Gouel
- Nuclear Medicine Department, Henri Becquerel Cancer Center, Rouen, France
- QuantIF-LITIS EA4108, University of Rouen, Rouen, France
| | - Pierre Vera
- Nuclear Medicine Department, Henri Becquerel Cancer Center, Rouen, France
- QuantIF-LITIS EA4108, University of Rouen, Rouen, France
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Jagoda P, Fleckenstein J, Sonnhoff M, Schneider G, Ruebe C, Buecker A, Stroeder J. Diffusion-weighted MRI improves response assessment after definitive radiotherapy in patients with NSCLC. Cancer Imaging 2021; 21:15. [PMID: 33478592 PMCID: PMC7818746 DOI: 10.1186/s40644-021-00384-9] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2020] [Accepted: 01/08/2021] [Indexed: 01/15/2023] Open
Abstract
Background Computed tomography (CT) is the standard procedure for follow-up of non-small-cell lung cancer (NSCLC) after radiochemotherapy. CT has difficulties differentiating between tumor, atelectasis and radiation induced lung toxicity (RILT). Diffusion-weighted imaging (DWI) may enable a more accurate detection of vital tumor tissue. The aim of this study was to determine the diagnostic value of MRI versus CT in the follow-up of NSCLC. Methods Twelve patients with NSCLC stages I-III scheduled for radiochemotherapy were enrolled in this prospective study. CT with i.v. contrast agent and non enhanced MRI were performed before and 3, 6 and 12 months after treatment. Standardized ROIs were used to determine the apparent diffusion weighted coefficient (ADC) within the tumor. Tumor size was assessed by the longest longitudinal diameter (LD) and tumor volume on DWI and CT. RILT was assessed on a 4-point-score in breath-triggered T2-TSE and CT. Results There was no significant difference regarding LD and tumor volume between MRI and CT (p ≥ 0.6221, respectively p ≥ 0.25). Evaluation of RILT showed a very high correlation between MRI and CT at 3 (r = 0.8750) and 12 months (r = 0.903). Assessment of the ADC values suggested that patients with a good tumor response have higher ADC values than non-responders. Conclusions DWI is equivalent to CT for tumor volume determination in patients with NSCLC during follow up. The extent of RILT can be reliably determined by MRI. DWI could become a beneficial method to assess tumor response more accurately. ADC values may be useful as a prognostic marker.
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Affiliation(s)
- Philippe Jagoda
- Clinic for Diagnostic and Interventional Radiology, Saarland University Medical Center, Kirrberger Str. 1, 66421, Homburg, Saar, Germany.
| | - Jochen Fleckenstein
- Department of Radiotherapy and Radiation Oncology, Saarland University Medical Center, Kirrberger Str. Geb. 6.5, 66421, Homburg, Saar, Germany
| | - Mathias Sonnhoff
- Department of Radiotherapy and Radiation Oncology, Saarland University Medical Center, Kirrberger Str. Geb. 6.5, 66421, Homburg, Saar, Germany
| | - Günther Schneider
- Clinic for Diagnostic and Interventional Radiology, Saarland University Medical Center, Kirrberger Str. 1, 66421, Homburg, Saar, Germany
| | - Christian Ruebe
- Department of Radiotherapy and Radiation Oncology, Saarland University Medical Center, Kirrberger Str. Geb. 6.5, 66421, Homburg, Saar, Germany
| | - Arno Buecker
- Clinic for Diagnostic and Interventional Radiology, Saarland University Medical Center, Kirrberger Str. 1, 66421, Homburg, Saar, Germany
| | - Jonas Stroeder
- Clinic for Diagnostic and Interventional Radiology, Saarland University Medical Center, Kirrberger Str. 1, 66421, Homburg, Saar, Germany
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Besson FL, Fernandez B, Faure S, Mercier O, Seferian A, Mignard X, Mussot S, le Pechoux C, Caramella C, Botticella A, Levy A, Parent F, Bulifon S, Montani D, Mitilian D, Fadel E, Planchard D, Besse B, Ghigna-Bellinzoni MR, Comtat C, Lebon V, Durand E. 18F-FDG PET and DCE kinetic modeling and their correlations in primary NSCLC: first voxel-wise correlative analysis of human simultaneous [18F]FDG PET-MRI data. EJNMMI Res 2020; 10:88. [PMID: 32734484 PMCID: PMC7392998 DOI: 10.1186/s13550-020-00671-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2020] [Accepted: 07/14/2020] [Indexed: 02/07/2023] Open
Abstract
OBJECTIVES To decipher the correlations between PET and DCE kinetic parameters in non-small-cell lung cancer (NSCLC), by using voxel-wise analysis of dynamic simultaneous [18F]FDG PET-MRI. MATERIAL AND METHODS Fourteen treatment-naïve patients with biopsy-proven NSCLC prospectively underwent a 1-h dynamic [18F]FDG thoracic PET-MRI scan including DCE. The PET and DCE data were normalized to their corresponding T1-weighted MR morphological space, and tumors were masked semi-automatically. Voxel-wise parametric maps of PET and DCE kinetic parameters were computed by fitting the dynamic PET and DCE tumor data to the Sokoloff and Extended Tofts models respectively, by using in-house developed procedures. Curve-fitting errors were assessed by computing the relative root mean square error (rRMSE) of the estimated PET and DCE signals at the voxel level. For each tumor, Spearman correlation coefficients (rs) between all the pairs of PET and DCE kinetic parameters were estimated on a voxel-wise basis, along with their respective bootstrapped 95% confidence intervals (n = 1000 iterations). RESULTS Curve-fitting metrics provided fit errors under 20% for almost 90% of the PET voxels (median rRMSE = 10.3, interquartile ranges IQR = 8.1; 14.3), whereas 73.3% of the DCE voxels showed fit errors under 45% (median rRMSE = 31.8%, IQR = 22.4; 46.6). The PET-PET, DCE-DCE, and PET-DCE voxel-wise correlations varied according to individual tumor behaviors. Beyond this wide variability, the PET-PET and DCE-DCE correlations were mainly high (absolute rs values > 0.7), whereas the PET-DCE correlations were mainly low to moderate (absolute rs values < 0.7). Half the tumors showed a hypometabolism with low perfused/vascularized profile, a hallmark of hypoxia, and tumor aggressiveness. CONCLUSION A dynamic "one-stop shop" procedure applied to NSCLC is technically feasible in clinical practice. PET and DCE kinetic parameters assessed simultaneously are not highly correlated in NSCLC, and these correlations showed a wide variability among tumors and patients. These results tend to suggest that PET and DCE kinetic parameters might provide complementary information. In the future, this might make PET-MRI a unique tool to characterize the individual tumor biological behavior in NSCLC.
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Affiliation(s)
- Florent L Besson
- Université Paris-Saclay, CEA, CNRS, Inserm, BioMAPs, 91401, Orsay, France.
- Department of Biophysics and Nuclear Medicine-Molecular Imaging, Hôpitaux Universitaires Paris-Saclay, Assistance Publique-Hôpitaux de Paris, CHU Bicêtre, 94270, Le Kremlin-Bicêtre, France.
- School of Medicine, Université Paris-Saclay, Le Kremlin-Bicêtre, France.
| | | | - Sylvain Faure
- Laboratoire de Mathématiques d'Orsay, CNRS, Université Paris-Saclay, 91405, Orsay, France
| | - Olaf Mercier
- Department of Thoracic and Vascular Surgery and Heart-Lung Transplantation, Marie Lannelongue Hospital, 92350, Le Plessis Robinson, France
| | - Andrei Seferian
- Service de Pneumologie, Centre de Référence de l'Hypertension Pulmonaire, Hôpitaux Universitaires Paris-Saclay, Assistance Publique-Hôpitaux de Paris, 94270, Le Kremlin-Bicêtre, France
- Inserm UMR_S999, Marie Lannelongue Hospital, 92350, Le Plessis Robinson, France
| | - Xavier Mignard
- Service de Pneumologie, Centre de Référence de l'Hypertension Pulmonaire, Hôpitaux Universitaires Paris-Saclay, Assistance Publique-Hôpitaux de Paris, 94270, Le Kremlin-Bicêtre, France
| | - Sacha Mussot
- Department of Thoracic and Vascular Surgery and Heart-Lung Transplantation, Marie Lannelongue Hospital, 92350, Le Plessis Robinson, France
| | - Cecile le Pechoux
- Department of Radiation Oncology, Institut d'Oncologie Thoracique (IOT), Gustave Roussy, Université Paris Saclay, Villejuif, France
| | - Caroline Caramella
- Department of Radiology, Institut d'Oncologie Thoracique (IOT), Gustave Roussy, Université Paris Saclay, Villejuif, France
| | - Angela Botticella
- Department of Radiation Oncology, Institut d'Oncologie Thoracique (IOT), Gustave Roussy, Université Paris Saclay, Villejuif, France
| | - Antonin Levy
- Department of Radiation Oncology, Institut d'Oncologie Thoracique (IOT), Gustave Roussy, Université Paris Saclay, Villejuif, France
| | - Florence Parent
- Service de Pneumologie, Centre de Référence de l'Hypertension Pulmonaire, Hôpitaux Universitaires Paris-Saclay, Assistance Publique-Hôpitaux de Paris, 94270, Le Kremlin-Bicêtre, France
- Inserm UMR_S999, Marie Lannelongue Hospital, 92350, Le Plessis Robinson, France
| | - Sophie Bulifon
- Service de Pneumologie, Centre de Référence de l'Hypertension Pulmonaire, Hôpitaux Universitaires Paris-Saclay, Assistance Publique-Hôpitaux de Paris, 94270, Le Kremlin-Bicêtre, France
- Inserm UMR_S999, Marie Lannelongue Hospital, 92350, Le Plessis Robinson, France
| | - David Montani
- Service de Pneumologie, Centre de Référence de l'Hypertension Pulmonaire, Hôpitaux Universitaires Paris-Saclay, Assistance Publique-Hôpitaux de Paris, 94270, Le Kremlin-Bicêtre, France
- Inserm UMR_S999, Marie Lannelongue Hospital, 92350, Le Plessis Robinson, France
| | - Delphine Mitilian
- Department of Thoracic and Vascular Surgery and Heart-Lung Transplantation, Marie Lannelongue Hospital, 92350, Le Plessis Robinson, France
| | - Elie Fadel
- Department of Thoracic and Vascular Surgery and Heart-Lung Transplantation, Marie Lannelongue Hospital, 92350, Le Plessis Robinson, France
| | - David Planchard
- Department of Oncology, Institut d'Oncologie Thoracique (IOT), Gustave Roussy, Université Paris Saclay, Villejuif, France
| | - Benjamin Besse
- Department of Oncology, Institut d'Oncologie Thoracique (IOT), Gustave Roussy, Université Paris Saclay, Villejuif, France
| | | | - Claude Comtat
- Université Paris-Saclay, CEA, CNRS, Inserm, BioMAPs, 91401, Orsay, France
- School of Medicine, Université Paris-Saclay, Le Kremlin-Bicêtre, France
| | - Vincent Lebon
- Université Paris-Saclay, CEA, CNRS, Inserm, BioMAPs, 91401, Orsay, France
- School of Medicine, Université Paris-Saclay, Le Kremlin-Bicêtre, France
| | - Emmanuel Durand
- Université Paris-Saclay, CEA, CNRS, Inserm, BioMAPs, 91401, Orsay, France
- Department of Biophysics and Nuclear Medicine-Molecular Imaging, Hôpitaux Universitaires Paris-Saclay, Assistance Publique-Hôpitaux de Paris, CHU Bicêtre, 94270, Le Kremlin-Bicêtre, France
- School of Medicine, Université Paris-Saclay, Le Kremlin-Bicêtre, France
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Seidensaal K, Harrabi SB, Debus J. Molecular Imaging for Particle Therapy: Current Approach and Future Directions. Recent Results Cancer Res 2020; 216:865-879. [PMID: 32594410 DOI: 10.1007/978-3-030-42618-7_28] [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: 06/11/2023]
Abstract
During the last decades, radiation oncology has been subject to a number of technological innovations. Particle therapy has evolved in parallel to the modern high-precision photon radiotherapy techniques and offers a superior dose distribution with decreased integral dose to healthy tissues. With advancing precision of treatment, the necessity for accurate and confident target volume delineation is rising. When morphological imaging reaches its limitations, molecular imaging can provide valuable information.
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Affiliation(s)
- Katharina Seidensaal
- Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany
| | - Semi Ben Harrabi
- Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany
| | - Jürgen Debus
- Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany.
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A Prospective Study of Magnetic Resonance Imaging Assessment of Post-radiation Changes Following Stereotactic Body Radiation Therapy for Non-small Cell Lung Cancer. Clin Oncol (R Coll Radiol) 2019; 31:720-727. [DOI: 10.1016/j.clon.2019.05.014] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2018] [Revised: 04/09/2019] [Accepted: 04/18/2019] [Indexed: 12/25/2022]
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7
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Liu J, Lv H, Dong J, Ding X, Han Z, Yang S, Ba Z. Diffusion-Weighted Magnetic Resonance Imaging for Early Detection of Chemotherapy Resistance in Non-Small Cell Lung Cancer. Med Sci Monit 2019; 25:6264-6270. [PMID: 31476196 PMCID: PMC6713033 DOI: 10.12659/msm.914236] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/30/2023] Open
Abstract
Background The aim of this study was to examine the role of magnetic resonance imaging-diffusion weighted imaging (MRI-DWI) in the early detection of chemotherapy resistance in non-small cell lung cancer (NSCLC) patients. Material/Methods MRI-DWI and computed tomography (CT) were carried out in 75 patients with newly diagnostic NSCLC before and after first, second, fourth, and sixth cycles of chemotherapy. Resistance to chemotherapy was assessed based on the change in the largest tumor diameter after chemotherapy. Diffusion of water molecule in each lesion was quantitatively measured by apparent diffusion coefficient (ADC). The diagnostic results of DWI after first and second cycle of chemotherapy were analyzed by the area under receiver operating characteristics curve (ROC). Results Among the patients, 43 patients were chemo-resistance while 32 patients were chemo-sensitive. The ADC changing rate between second and first cycle of chemotherapy was significantly higher in chemo-sensitive patients compared with chemo-resistance patients (t=3.236, P=0.002). The ROC showed cutoff values of the ADC changing rate after first and second cycles of chemotherapy for resistance/sensitive discrimination were 23.6% and 5.56%, respectively. DWI after first and second cycles of therapy showed sensitivities of 55.8% and 55.8%, specificities of 65.6% and 87.5%, and area under ROC of 0.568 and 0.733, respectively. Conclusions ADC changing rate between first and second cycles of chemotherapy could sensitively distinguish chemo-sensitive and chemo-resistant tumors at earlier stages, which may direct treatment adjustment and improve the prognosis of patients.
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Affiliation(s)
- Junfeng Liu
- Department of Imaging, Laigang Hospital Affiliated to Taishan Medical University, Laiwu, Shandong, China (mainland)
| | - Hongxia Lv
- Department of Respiratory Medicine, Laigang Hospital Affiliated to Taishan Medical University, Laiwu, Shandong, China (mainland)
| | - Jiliang Dong
- Department of Infectious Diseases, Laigang Hospital Affiliated to Taishan Medical University, Laiwu, Shandong, China (mainland)
| | - Xiujing Ding
- Department of Thoracic Surgery, Laigang Hospital Affiliated to Taishan Medical University, Laiwu, Shandong, China (mainland)
| | - Zhiguang Han
- Department of Imaging, Laigang Hospital Affiliated to Taishan Medical University, Laiwu, Shandong, China (mainland)
| | - Shiqing Yang
- Department of Imaging, Laigang Hospital Affiliated to Taishan Medical University, Laiwu, Shandong, China (mainland)
| | - Zhaogui Ba
- Department of Imaging, Laigang Hospital Affiliated to Taishan Medical University, Laiwu, Shandong, China (mainland)
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8
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PET and MRI based RT treatment planning: Handling uncertainties. Cancer Radiother 2019; 23:753-760. [PMID: 31427076 DOI: 10.1016/j.canrad.2019.08.002] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2019] [Accepted: 08/03/2019] [Indexed: 12/11/2022]
Abstract
Imaging provides the basis for radiotherapy. Multi-modality images are used for target delineation (primary tumor and nodes, boost volume) and organs at risk, treatment guidance, outcome prediction, and treatment assessment. Next to anatomical information, more and more functional imaging is being used. The current paper provides a brief overview of the different applications of imaging techniques used in the radiotherapy process, focusing on uncertainties and QA. The paper mainly focuses on PET and MRI, but also provides a short discussion on DCE-CT. A close collaboration between radiology, nuclear medicine and radiotherapy departments provides the key to improve the quality of radiotherapy. Jointly developed imaging protocols (RT position setup, immobilization tools, lasers, flat table…), and QA programs are mandatory. For PET, suitable windowing in consultation with a Nuclear Medicine Physician is crucial (differentiation benign/malignant lesions, artifacts…). A basic knowledge of MRI sequences is required, in such a way that geometrical distortions are easily recognized by all members the RT and RT physics team. If this is not the case, then the radiologist should be introduced systematically in the delineation process and multidisciplinary meetings need to be organized regularly. For each image modality and each image registration process, the associated uncertainties need to be determined and integrated in the PTV margin. When using functional information for dose painting, response assessment or outcome prediction, collaboration between the different departments is even more important. Limitations of imaging based biomarkers (specificity, sensitivity) should be known.
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Basson L, Jarraya H, Escande A, Cordoba A, Daghistani R, Pasquier D, Lacornerie T, Lartigau E, Mirabel X. Chest Magnetic Resonance Imaging Decreases Inter-observer Variability of Gross Target Volume for Lung Tumors. Front Oncol 2019; 9:690. [PMID: 31456936 PMCID: PMC6700272 DOI: 10.3389/fonc.2019.00690] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2019] [Accepted: 07/12/2019] [Indexed: 12/14/2022] Open
Abstract
Purpose: PET/CT is a standard medical imaging used in the delineation of gross tumor volume (GTV) in case of radiation therapy for lung tumors. However, PET/CT could present some limitations such as resolution and standardized uptake value threshold. Moreover, chest MRI has shown good potential in diagnosis for thoracic oncology. Therefore, we investigated the influence of chest MRI on inter-observer variability of GTV delineation. Methods and Materials: Five observers contoured the GTV on CT for 14 poorly defined lung tumors during three contouring phases based on true daily clinical routine and acquisition: CT phase, with only CT images; PET phase, with PET/CT; and MRI phase, with both PET/CT and MRI. Observers waited at least 1 week between each phases to decrease memory bias. Contours were compared using descriptive statistics of volume, coefficient of variation (COV), and Dice similarity coefficient (DSC). Results: MRI phase volumes (median 4.8 cm3) were significantly smaller than PET phase volumes (median 6.4 cm3, p = 0.015), but not different from CT phase volumes (median 5.7 cm3, p = 0.30). The mean COV was improved for the MRI phase (0.38) compared to the CT (0.58, p = 0.024) and PET (0.53, p = 0.060) phases. The mean DSC of the MRI phase (0.67) was superior to those of the CT and PET phases (0.56 and 0.60, respectively; p < 0.001 for both). Conclusions: The addition of chest MRI seems to decrease inter-observer variability of GTV delineation for poorly defined lung tumors compared to PET/CT alone and should be explored in further prospective studies.
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Affiliation(s)
- Laurent Basson
- Universitary Radiation Oncology Department, Oscar Lambret Comprehensive Cancer Center, Lille, France.,University of Lille, Lille, France
| | - Hajer Jarraya
- Medical Imaging Department, Oscar Lambret Comprehensive Cancer Center, Lille, France
| | - Alexandre Escande
- Universitary Radiation Oncology Department, Oscar Lambret Comprehensive Cancer Center, Lille, France.,University of Lille, Lille, France
| | - Abel Cordoba
- Universitary Radiation Oncology Department, Oscar Lambret Comprehensive Cancer Center, Lille, France
| | - Rayyan Daghistani
- University of Lille, Lille, France.,Medical Imaging Department, Oscar Lambret Comprehensive Cancer Center, Lille, France
| | - David Pasquier
- Universitary Radiation Oncology Department, Oscar Lambret Comprehensive Cancer Center, Lille, France.,University of Lille, Lille, France
| | - Thomas Lacornerie
- Department of Medical Physics, Oscar Lambret Comprehensive Cancer Center, Lille, France
| | - Eric Lartigau
- Universitary Radiation Oncology Department, Oscar Lambret Comprehensive Cancer Center, Lille, France.,University of Lille, Lille, France
| | - Xavier Mirabel
- Universitary Radiation Oncology Department, Oscar Lambret Comprehensive Cancer Center, Lille, France
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10
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Sauter AW, Stieltjes B, Weikert T, Gatidis S, Wiese M, Klarhöfer M, Wild D, Lardinois D, Bremerich J, Sommer G. The Spatial Relationship between Apparent Diffusion Coefficient and Standardized Uptake Value of 18F-Fluorodeoxyglucose Has a Crucial Influence on the Numeric Correlation of Both Parameters in PET/MRI of Lung Tumors. CONTRAST MEDIA & MOLECULAR IMAGING 2017; 2017:8650853. [PMID: 29391862 PMCID: PMC5748125 DOI: 10.1155/2017/8650853] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/02/2017] [Revised: 09/18/2017] [Accepted: 10/02/2017] [Indexed: 11/30/2022]
Abstract
The minimum apparent diffusion coefficient (ADCmin) derived from diffusion-weighted MRI (DW-MRI) and the maximum standardized uptake value (SUVmax) of FDG-PET are markers of aggressiveness in lung cancer. The numeric correlation of the two parameters has been extensively studied, but their spatial interplay is not well understood. After FDG-PET and DW-MRI coregistration, values and location of ADCmin- and SUVmax-voxels were analyzed. The upper limit of the 95% confidence interval for registration accuracy of sequential PET/MRI was 12 mm, and the mean distance (D) between ADCmin- and SUVmax-voxels was 14.0 mm (average of two readers). Spatial mismatch (D > 12 mm) between ADCmin and SUVmax was found in 9/25 patients. A considerable number of mismatch cases (65%) was also seen in a control group that underwent simultaneous PET/MRI. In the entire patient cohort, no statistically significant correlation between SUVmax and ADCmin was seen, while a moderate negative linear relationship (r = -0.5) between SUVmax and ADCmin was observed in tumors with a spatial match (D ≤ 12 mm). In conclusion, spatial mismatch between ADCmin and SUVmax is found in a considerable percentage of patients. The spatial connection of the two parameters SUVmax and ADCmin has a crucial influence on their numeric correlation.
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Affiliation(s)
- Alexander W. Sauter
- University Hospital Basel, University of Basel, Clinic of Radiology & Nuclear Medicine, Petersgraben 4, 4031 Basel, Switzerland
- Diagnostic and Interventional Radiology, University Hospital Tübingen, Eberhard Karls University, Hoppe-Seyler-Straße 3, 72076 Tübingen, Germany
| | - Bram Stieltjes
- University Hospital Basel, University of Basel, Clinic of Radiology & Nuclear Medicine, Petersgraben 4, 4031 Basel, Switzerland
| | - Thomas Weikert
- University Hospital Basel, University of Basel, Clinic of Radiology & Nuclear Medicine, Petersgraben 4, 4031 Basel, Switzerland
| | - Sergios Gatidis
- Diagnostic and Interventional Radiology, University Hospital Tübingen, Eberhard Karls University, Hoppe-Seyler-Straße 3, 72076 Tübingen, Germany
| | - Mark Wiese
- University Hospital Basel, University of Basel, Clinic of Thoracic Surgery, Spitalstrasse 21, 4031 Basel, Switzerland
| | - Markus Klarhöfer
- Siemens Healthineers, Freilagerstrasse 40, 8047 Zürich, Switzerland
| | - Damian Wild
- University Hospital Basel, University of Basel, Clinic of Radiology & Nuclear Medicine, Petersgraben 4, 4031 Basel, Switzerland
| | - Didier Lardinois
- University Hospital Basel, University of Basel, Clinic of Thoracic Surgery, Spitalstrasse 21, 4031 Basel, Switzerland
| | - Jens Bremerich
- University Hospital Basel, University of Basel, Clinic of Radiology & Nuclear Medicine, Petersgraben 4, 4031 Basel, Switzerland
| | - Gregor Sommer
- University Hospital Basel, University of Basel, Clinic of Radiology & Nuclear Medicine, Petersgraben 4, 4031 Basel, Switzerland
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Jiang J, Yin J, Cui L, Gu X, Cai R, Gong S, Xu Y, Ma H, Mao J. Lung Cancer: Short‐Term Reproducibility of Intravoxel Incoherent Motion Parameters and Apparent Diffusion Coefficient at 3T. J Magn Reson Imaging 2017; 47:1003-1012. [PMID: 28741732 DOI: 10.1002/jmri.25820] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2017] [Accepted: 07/06/2017] [Indexed: 12/31/2022] Open
Affiliation(s)
- Jianqin Jiang
- Department of RadiologySecond Affiliated Hospital of Nantong UniversityNantong Jiangsu PR China
- Department of RadiologyYancheng City No.1 People's HospitalYancheng Jiangsu PR China
| | - Jianbin Yin
- Department of RadiologySecond Affiliated Hospital of Nantong UniversityNantong Jiangsu PR China
| | - Lei Cui
- Department of RadiologySecond Affiliated Hospital of Nantong UniversityNantong Jiangsu PR China
| | - Xiaowen Gu
- Department of RadiologySecond Affiliated Hospital of Nantong UniversityNantong Jiangsu PR China
- Department of RadiologySuzhou Municipal HospitalSuzhou Jiangsu PR China
| | - Rongfang Cai
- Department of RadiologySecond Affiliated Hospital of Nantong UniversityNantong Jiangsu PR China
| | - Shenchu Gong
- Department of RadiologySecond Affiliated Hospital of Nantong UniversityNantong Jiangsu PR China
| | - Yiming Xu
- Department of Thoracic SurgerySecond Affiliated Hospital of Nantong UniversityNantong Jiangsu PR China
| | - Hang Ma
- Department of RespiratorySecond Affiliated Hospital of Nantong UniversityNantong Jiangsu PR China
| | - Jian Mao
- Customer ServiceHealthcare Siemens China
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12
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Assessment of treatment response after lung stereotactic body radiotherapy using diffusion weighted magnetic resonance imaging and positron emission tomography: A pilot study. Eur J Radiol 2017. [DOI: 10.1016/j.ejrad.2017.04.022] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
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13
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Huang YS, Chen JLY, Hsu FM, Huang JY, Ko WC, Chen YC, Jaw FS, Yen RF, Chang YC. Response assessment of stereotactic body radiation therapy using dynamic contrast-enhanced integrated MR-PET in non-small cell lung cancer patients. J Magn Reson Imaging 2017; 47:191-199. [DOI: 10.1002/jmri.25758] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2017] [Accepted: 04/20/2017] [Indexed: 12/21/2022] Open
Affiliation(s)
- Yu-Sen Huang
- Institute of Biomedical Engineering; College of Medicine and College of Engineering, National Taiwan University; Taipei Taiwan
- Department of Medical Imaging; National Taiwan University, Hospital and National Taiwan, University College of Medicine; Taipei Taiwan
- Department of Medical Imaging; National Taiwan University Hospital; Yun-Lin Branch Yun-Lin Taiwan
| | - Jenny Ling-Yu Chen
- Institute of Biomedical Engineering; College of Medicine and College of Engineering, National Taiwan University; Taipei Taiwan
- Department of Oncology; National Taiwan University, Hospital and National Taiwan University College of Medicine; Taipei Taiwan
- Department of Radiation Oncology; National Taiwan University Hospital; Hsin-Chu Branch Hsin-Chu Taiwan
| | - Feng-Ming Hsu
- Department of Oncology; National Taiwan University, Hospital and National Taiwan University College of Medicine; Taipei Taiwan
| | - Jei-Yie Huang
- Department of Nuclear Medicine; National Taiwan University, Hospital and National Taiwan, University College of Medicine; Taipei Taiwan
| | - Wei-Chun Ko
- Department of Medical Imaging; National Taiwan University, Hospital and National Taiwan, University College of Medicine; Taipei Taiwan
| | - Yi-Chang Chen
- Department of Medical Imaging; National Taiwan University, Hospital and National Taiwan, University College of Medicine; Taipei Taiwan
| | - Fu-Shan Jaw
- Institute of Biomedical Engineering; College of Medicine and College of Engineering, National Taiwan University; Taipei Taiwan
| | - Ruoh-Fang Yen
- Department of Nuclear Medicine; National Taiwan University, Hospital and National Taiwan, University College of Medicine; Taipei Taiwan
| | - Yeun-Chung Chang
- Department of Medical Imaging; National Taiwan University, Hospital and National Taiwan, University College of Medicine; Taipei Taiwan
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14
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Meta-Analysis of the Correlation between Apparent Diffusion Coefficient and Standardized Uptake Value in Malignant Disease. CONTRAST MEDIA & MOLECULAR IMAGING 2017; 2017:4729547. [PMID: 29097924 PMCID: PMC5612674 DOI: 10.1155/2017/4729547] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/01/2016] [Accepted: 01/15/2017] [Indexed: 12/19/2022]
Abstract
The objective of this meta-analysis is to explore the correlation between the apparent diffusion coefficient (ADC) on diffusion-weighted MR and the standard uptake value (SUV) of 18F-FDG on PET/CT in patients with cancer. Databases such as PubMed (MEDLINE included), EMBASE, and Cochrane Database of Systematic Review were searched for relevant original articles that explored the correlation between SUV and ADC in English. After applying Fisher's r-to-z transformation, correlation coefficient (r) values were extracted from each study and 95% confidence intervals (CIs) were calculated. Sensitivity and subgroup analyses based on tumor type were performed to investigate the potential heterogeneity. Forty-nine studies were eligible for the meta-analysis, comprising 1927 patients. Pooled r for all studies was −0.35 (95% CI: −0.42–0.28) and exhibited a notable heterogeneity (I2 = 78.4%; P < 0.01). In terms of the cancer type subgroup analysis, combined correlation coefficients of ADC/SUV range from −0.12 (lymphoma, n = 5) to −0.59 (pancreatic cancer, n = 2). We concluded that there is an average negative correlation between ADC and SUV in patients with cancer. Higher correlations were found in the brain tumor, cervix carcinoma, and pancreas cancer. However, a larger, prospective study is warranted to validate these findings in different cancer types.
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15
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Zhan S, Yang X. MR image bias field harmonic approximation with histogram statistical analysis. Pattern Recognit Lett 2016. [DOI: 10.1016/j.patrec.2016.02.009] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
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16
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Ghaye B, Wanet M, El Hajjam M. Imaging after radiation therapy of thoracic tumors. Diagn Interv Imaging 2016; 97:1037-1052. [PMID: 27567554 DOI: 10.1016/j.diii.2016.06.019] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2016] [Revised: 06/02/2016] [Accepted: 06/02/2016] [Indexed: 12/25/2022]
Abstract
Radiation-induced lung disease (RILD) is frequent after therapeutic irradiation of thoracic malignancies. Many technique-, treatment-, tumor- and patient-related factors influence the degree of injury sustained by the lung after irradiation. Based on the time interval after the completion of the treatment RILD presents as early and late features characterized by inflammatory and fibrotic changes, respectively. They are usually confined to the radiation port. Though the typical pattern of RILD is easily recognized after conventional two-dimensional radiation therapy (RT), RILD may present with atypical patterns after more recent types of three- or four-dimensional RT treatment. Three atypical patterns are reported: the modified conventional, the mass-like and the scar-like patterns. Knowledge of the various features and patterns of RILD is important for correct diagnosis and appropriate treatment. RILD should be differentiated from recurrent tumoral disease, infection and radiation-induced tumors. Due to RILD, the follow-up after RT may be difficult as response evaluation criteria in solid tumours (RECIST) criteria may be unreliable to assess tumor control particularly after stereotactic ablation RT (SABR). Long-term follow-up should be based on clinical examination and morphological and/or functional investigations including CT, PET-CT, pulmonary functional tests, MRI and PET-MRI.
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Affiliation(s)
- B Ghaye
- Service de radiologie, secteur cardiothoracique, cliniques universitaires St-Luc, université catholique de Louvain, avenue Hippocrate 10, 1200 Bruxelles, Belgium.
| | - M Wanet
- Service de radiothérapie, oncologique, CHU UCL Namur, site clinique et maternité Sainte-Elisabeth, 5000 Namur, Belgium
| | - M El Hajjam
- Service de radiologie, hôpital Ambroise-Paré, 92100 Boulogne-Billancourt, France
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17
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Weiss E, Ford JC, Olsen KM, Karki K, Saraiya S, Groves R, Hugo GD. Apparent diffusion coefficient (ADC) change on repeated diffusion-weighted magnetic resonance imaging during radiochemotherapy for non-small cell lung cancer: A pilot study. Lung Cancer 2016; 96:113-9. [DOI: 10.1016/j.lungcan.2016.04.001] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2016] [Revised: 02/11/2016] [Accepted: 04/03/2016] [Indexed: 12/12/2022]
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18
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Kumar S, Liney G, Rai R, Holloway L, Moses D, Vinod SK. Magnetic resonance imaging in lung: a review of its potential for radiotherapy. Br J Radiol 2016; 89:20150431. [PMID: 26838950 DOI: 10.1259/bjr.20150431] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022] Open
Abstract
MRI has superior soft-tissue definition compared with existing imaging modalities in radiation oncology; this has the added benefit of functional as well as anatomical imaging. This review aimed to evaluate the current use of MRI for lung cancer and identify the potential of a MRI protocol for lung radiotherapy (RT). 30 relevant studies were identified. Improvements in MRI technology have overcome some of the initial limitations of utilizing MRI for lung imaging. A number of commercially available and novel sequences have shown image quality to be adequate for the detection of pulmonary nodules with the potential for tumour delineation. Quantifying tumour motion is also feasible and may be more representative than that seen on four-dimensional CT. Functional MRI sequences have shown correlation with flu-deoxy-glucose positron emission tomography (FDG-PET) in identifying malignant involvement and treatment response. MRI can also be used as a measure of pulmonary function. While there are some limitations for the adoption of MRI in RT-planning process for lung cancer, MRI has shown the potential to compete with both CT and PET for tumour delineation and motion definition, with the added benefit of functional information. MRI is well placed to become a significant imaging modality in RT for lung cancer.
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Affiliation(s)
- Shivani Kumar
- 1 South Western Clinical School, School of Medicine, University of New South Wales, Liverpool, NSW, Australia.,2 Liverpool and Macarthur Cancer Therapy Centres, Liverpool Hospital, Liverpool, NSW, Australia.,3 Ingham Institute of Applied Medical Research, Liverpool, NSW, Australia
| | - Gary Liney
- 1 South Western Clinical School, School of Medicine, University of New South Wales, Liverpool, NSW, Australia.,2 Liverpool and Macarthur Cancer Therapy Centres, Liverpool Hospital, Liverpool, NSW, Australia.,3 Ingham Institute of Applied Medical Research, Liverpool, NSW, Australia.,4 Centre for Medical Radiation Physics, University of Wollongong, Liverpool, NSW, Australia
| | - Robba Rai
- 2 Liverpool and Macarthur Cancer Therapy Centres, Liverpool Hospital, Liverpool, NSW, Australia.,3 Ingham Institute of Applied Medical Research, Liverpool, NSW, Australia
| | - Lois Holloway
- 1 South Western Clinical School, School of Medicine, University of New South Wales, Liverpool, NSW, Australia.,2 Liverpool and Macarthur Cancer Therapy Centres, Liverpool Hospital, Liverpool, NSW, Australia.,3 Ingham Institute of Applied Medical Research, Liverpool, NSW, Australia.,4 Centre for Medical Radiation Physics, University of Wollongong, Liverpool, NSW, Australia.,5 Institute of Medical Physics, School of Physics, University of Sydney, Sydney, NSW, Australia
| | - Daniel Moses
- 1 South Western Clinical School, School of Medicine, University of New South Wales, Liverpool, NSW, Australia.,6 Department of Medical Imaging, Northern Hospital Network, Sydney, NSW, Australia.,7 Western Sydney University, Penrith, NSW, Australia
| | - Shalini K Vinod
- 1 South Western Clinical School, School of Medicine, University of New South Wales, Liverpool, NSW, Australia.,2 Liverpool and Macarthur Cancer Therapy Centres, Liverpool Hospital, Liverpool, NSW, Australia.,7 Western Sydney University, Penrith, NSW, Australia
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19
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Gladwish A, Milosevic M, Fyles A, Xie J, Halankar J, Metser U, Jiang H, Becker N, Levin W, Manchul L, Foltz W, Han K. Association of Apparent Diffusion Coefficient with Disease Recurrence in Patients with Locally Advanced Cervical Cancer Treated with Radical Chemotherapy and Radiation Therapy. Radiology 2015; 279:158-66. [PMID: 26505922 DOI: 10.1148/radiol.2015150400] [Citation(s) in RCA: 50] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
PURPOSE To investigate whether volumetrically derived apparent diffusion coefficient (ADC) from pretreatment diffusion-weighted (DW) magnetic resonance (MR) imaging is associated with disease recurrence in women with locally advanced cervical cancer treated with chemotherapy and radiation therapy. MATERIALS AND METHODS An ethics board-approved, retrospective study was conducted in 85 women with stage IB-IVA cervical cancer treated with chemo- and radiation therapy in 2009-2013. All patients underwent MR imaging for staging, including T2-weighted and DW MR imaging series, by using a 1.5- or 3.0-T imager. The mean, median, 75th, 90th, and 95th percentile ADCs (ADCmean, ADC50, ADC75, ADC90, and ADC95, respectively) of all voxels that comprised each tumor were extracted and normalized to the mean urine ADC (nADCmean, nADC50, nADC75, nADC90, and nADC95, respectively) to reduce variability. The primary outcome was disease-free survival (DFS). Uni- and multivariable Cox regression analyses were used to evaluate the association of ADC parameters and relevant clinical variables with DFS. RESULTS Of the 85 women included, 62 were free of disease at last follow-up. Median follow-up was 37 months (range, 5-68 months). Significant variables at univariable analysis included T2-weighted derived tumor diameter, para-aortic nodal involvement, advanced stage, ADC90 and ADC95, nADC75, nADC90, and nADC95. Normalized parameters were more highly associated (hazard ratio per 0.01 increase in normalized ADC, 0.91-0.94; P < .04). Because nADC75, nADC90, and nADC95 were highly correlated, only nADC95 (which had the lowest P value) was included in multivariable analysis. At multivariable analysis, absolute and normalized ADC95 remained associated with DFS (hazard ratio, 0.90-0.98; P < .05). CONCLUSION The volumetric ADC95 may be a useful imaging metric to predict treatment failure in patients with locally advanced cervical cancer treated with chemo- and radiation therapy.
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Affiliation(s)
- Adam Gladwish
- From the Radiation Medicine Program, Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada (A.G., M.M., A.F., J.X., N.B., W.L., L.M., W.F., K.H.); Departments of Radiation Oncology (A.G., M.M., A.F., J.X., N.B., W.L., L.M., W.F., K.H.) and Biostatistics (H.J.), University of Toronto, 610 University Ave, Toronto, ON, Canada M5G 2M9; and Department of Medical Imaging, University Health Network, Toronto, ON, Canada (J.H., U.R.)
| | - Michael Milosevic
- From the Radiation Medicine Program, Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada (A.G., M.M., A.F., J.X., N.B., W.L., L.M., W.F., K.H.); Departments of Radiation Oncology (A.G., M.M., A.F., J.X., N.B., W.L., L.M., W.F., K.H.) and Biostatistics (H.J.), University of Toronto, 610 University Ave, Toronto, ON, Canada M5G 2M9; and Department of Medical Imaging, University Health Network, Toronto, ON, Canada (J.H., U.R.)
| | - Anthony Fyles
- From the Radiation Medicine Program, Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada (A.G., M.M., A.F., J.X., N.B., W.L., L.M., W.F., K.H.); Departments of Radiation Oncology (A.G., M.M., A.F., J.X., N.B., W.L., L.M., W.F., K.H.) and Biostatistics (H.J.), University of Toronto, 610 University Ave, Toronto, ON, Canada M5G 2M9; and Department of Medical Imaging, University Health Network, Toronto, ON, Canada (J.H., U.R.)
| | - Jason Xie
- From the Radiation Medicine Program, Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada (A.G., M.M., A.F., J.X., N.B., W.L., L.M., W.F., K.H.); Departments of Radiation Oncology (A.G., M.M., A.F., J.X., N.B., W.L., L.M., W.F., K.H.) and Biostatistics (H.J.), University of Toronto, 610 University Ave, Toronto, ON, Canada M5G 2M9; and Department of Medical Imaging, University Health Network, Toronto, ON, Canada (J.H., U.R.)
| | - Jaydeep Halankar
- From the Radiation Medicine Program, Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada (A.G., M.M., A.F., J.X., N.B., W.L., L.M., W.F., K.H.); Departments of Radiation Oncology (A.G., M.M., A.F., J.X., N.B., W.L., L.M., W.F., K.H.) and Biostatistics (H.J.), University of Toronto, 610 University Ave, Toronto, ON, Canada M5G 2M9; and Department of Medical Imaging, University Health Network, Toronto, ON, Canada (J.H., U.R.)
| | - Ur Metser
- From the Radiation Medicine Program, Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada (A.G., M.M., A.F., J.X., N.B., W.L., L.M., W.F., K.H.); Departments of Radiation Oncology (A.G., M.M., A.F., J.X., N.B., W.L., L.M., W.F., K.H.) and Biostatistics (H.J.), University of Toronto, 610 University Ave, Toronto, ON, Canada M5G 2M9; and Department of Medical Imaging, University Health Network, Toronto, ON, Canada (J.H., U.R.)
| | - Haiyan Jiang
- From the Radiation Medicine Program, Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada (A.G., M.M., A.F., J.X., N.B., W.L., L.M., W.F., K.H.); Departments of Radiation Oncology (A.G., M.M., A.F., J.X., N.B., W.L., L.M., W.F., K.H.) and Biostatistics (H.J.), University of Toronto, 610 University Ave, Toronto, ON, Canada M5G 2M9; and Department of Medical Imaging, University Health Network, Toronto, ON, Canada (J.H., U.R.)
| | - Nathan Becker
- From the Radiation Medicine Program, Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada (A.G., M.M., A.F., J.X., N.B., W.L., L.M., W.F., K.H.); Departments of Radiation Oncology (A.G., M.M., A.F., J.X., N.B., W.L., L.M., W.F., K.H.) and Biostatistics (H.J.), University of Toronto, 610 University Ave, Toronto, ON, Canada M5G 2M9; and Department of Medical Imaging, University Health Network, Toronto, ON, Canada (J.H., U.R.)
| | - Wilfred Levin
- From the Radiation Medicine Program, Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada (A.G., M.M., A.F., J.X., N.B., W.L., L.M., W.F., K.H.); Departments of Radiation Oncology (A.G., M.M., A.F., J.X., N.B., W.L., L.M., W.F., K.H.) and Biostatistics (H.J.), University of Toronto, 610 University Ave, Toronto, ON, Canada M5G 2M9; and Department of Medical Imaging, University Health Network, Toronto, ON, Canada (J.H., U.R.)
| | - Lee Manchul
- From the Radiation Medicine Program, Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada (A.G., M.M., A.F., J.X., N.B., W.L., L.M., W.F., K.H.); Departments of Radiation Oncology (A.G., M.M., A.F., J.X., N.B., W.L., L.M., W.F., K.H.) and Biostatistics (H.J.), University of Toronto, 610 University Ave, Toronto, ON, Canada M5G 2M9; and Department of Medical Imaging, University Health Network, Toronto, ON, Canada (J.H., U.R.)
| | - Warren Foltz
- From the Radiation Medicine Program, Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada (A.G., M.M., A.F., J.X., N.B., W.L., L.M., W.F., K.H.); Departments of Radiation Oncology (A.G., M.M., A.F., J.X., N.B., W.L., L.M., W.F., K.H.) and Biostatistics (H.J.), University of Toronto, 610 University Ave, Toronto, ON, Canada M5G 2M9; and Department of Medical Imaging, University Health Network, Toronto, ON, Canada (J.H., U.R.)
| | - Kathy Han
- From the Radiation Medicine Program, Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada (A.G., M.M., A.F., J.X., N.B., W.L., L.M., W.F., K.H.); Departments of Radiation Oncology (A.G., M.M., A.F., J.X., N.B., W.L., L.M., W.F., K.H.) and Biostatistics (H.J.), University of Toronto, 610 University Ave, Toronto, ON, Canada M5G 2M9; and Department of Medical Imaging, University Health Network, Toronto, ON, Canada (J.H., U.R.)
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20
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[Positron emission tomography and stereotactic body radiation therapy for lung cancer: From treatment planning to response evaluation]. Cancer Radiother 2015; 19:790-4; quiz 795-9. [PMID: 26476702 DOI: 10.1016/j.canrad.2015.05.027] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2014] [Revised: 05/01/2015] [Accepted: 05/12/2015] [Indexed: 11/21/2022]
Abstract
Stereotactic body radiation therapy is the standard treatment for inoperable patients with early-stage lung cancer. Local control rates range from 80 to 90 % 2 years after treatment. The role of positron emission tomography in patient selection is well known, but its use for target definition or therapeutic response evaluation is less clear. We reviewed the literature in order to assess the current state of knowledge in this area.
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21
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Hagen JA. Diffusion-weighted magnetic resonance imaging may identify candidates for alternatives to lobectomy for early stage lung cancer. J Thorac Cardiovasc Surg 2015; 149:997. [PMID: 25906714 DOI: 10.1016/j.jtcvs.2015.02.051] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/10/2015] [Accepted: 02/12/2015] [Indexed: 10/23/2022]
Affiliation(s)
- Jeffrey A Hagen
- Division of Thoracic Surgery, Keck School of Medicine, University of Southern California, Los Angeles, Calif.
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22
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Thorwarth D. Functional imaging for radiotherapy treatment planning: current status and future directions-a review. Br J Radiol 2015; 88:20150056. [PMID: 25827209 PMCID: PMC4628531 DOI: 10.1259/bjr.20150056] [Citation(s) in RCA: 48] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Abstract
In recent years, radiotherapy (RT) has been subject to a number of technological innovations. Today, RT is extremely flexible, allowing irradiation of tumours with high doses, whilst also sparing normal tissues from doses. To make use of these additional degrees of freedom, integration of functional image information may play a key role (i) for better staging and tumour detection, (ii) for more accurate RT target volume delineation, (iii) to assess functional information about biological characteristics and individual radiation resistance and (iv) to apply personalized dose prescriptions. In this article, we discuss the current status and future directions of different clinically available functional imaging modalities; CT, MRI, positron emission tomography (PET) as well as the hybrid imaging techniques PET/CT and PET/MRI and their potential for individualized RT.
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Affiliation(s)
- D Thorwarth
- Section for Biomedical Physics, Department of Radiation Oncology, Eberhard Karls University Tübingen, Tübingen, Germany
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