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Holmstrand H, Lindskog M, Sundin A, Hansen T. The value of whole-body MRI instead of only brain MRI in addition to 18 F-FDG PET/CT in the staging of advanced non-small-cell lung cancer. Cancer Imaging 2025; 25:30. [PMID: 40069778 PMCID: PMC11895332 DOI: 10.1186/s40644-025-00852-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2024] [Accepted: 02/26/2025] [Indexed: 03/15/2025] Open
Abstract
BACKGROUND Non-small cell lung cancer (NSCLC) is a common neoplasm with poor prognosis in advanced stages. The clinical work-up in patients with locally advanced NSCLC mostly includes 18F-fluorodeoxyglucose positron emission tomography computed tomography (18F-FDG PET/CT) because of its high sensitivity for malignant lesion detection; however, specificity is lower. Diverging results exist whether whole-body MRI (WB-MRI) improves the staging accuracy in advanced lung cancer. Considering WB-MRI being a more time-consuming examination compared to brain MRI, it is important to establish whether or not additional value is found in detecting and characterizing malignant lesions. The purpose of this study is to investigate the value of additional whole-body magnetic resonance imaging, instead of only brain MRI, together with 18F-FDG PET/CT in staging patients with advanced NSCLC planned for curative treatment. MATERIAL AND METHODS In a prospective single center study, 28 patients with NSCLC stage 3 or oligometastatic disease were enrolled. In addition to 18F-FDG PET/CT, they underwent WB-MRI including the thorax, abdomen, spine, pelvis, and contrast-enhanced examination of the brain and liver. 18F-FDG PET/CT and WB-MRI were separately evaluated by two blinded readers, followed by consensus reading in which the likelihood of malignancy was assessed in detected lesions. Imaging and clinical follow-up for at least 12 months was used as reference standard. Statistical analyses included Fischer's exact test and Clopped-Pearson. RESULTS 28 patients (mean age ± SD 70.5 ± 8.4 years, 19 women) were enrolled. WB-MRI and FDG-PET/CT both showed maximum sensitivity and specificity for primary tumor diagnosis and similar sensitivity (p = 1.00) and specificity (p = 0.70) for detection of distant metastases. For diagnosis of lymph node metastases, WB-MRI showed lower sensitivity, 0.65 (95% CI: 0.38-0.86) than FDG-PET/CT, 1.00 (95% CI: 0.80-1.00) (p < 0.05), but similar specificity (p = 0.59). CONCLUSIONS WB-MRI in conjunction with 18F-FDG PET/CT provides no additional value over MRI of the brain only, in staging patients with advanced NSCLC. TRIAL REGISTRATION Registered locally and approved by the Uppsala University Hospital committee, registration number ASMR020.
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Affiliation(s)
- Hanna Holmstrand
- Radiology, Department of Surgical Sciences, Uppsala University, Uppsala University Hospital, entry 70, 1st floor, Uppsala, 751 85, Sweden.
| | - M Lindskog
- Department of Immunology, Genetics and Pathology, Uppsala University, Dag Hammarskjölds väg 20, Uppsala, 751 85, Sweden
- Department of Pelvic Cancer, Section of Genitourinary Oncology, Karolinska University Hospital, Eugeniavägen 3, Solna, 171 76, Sweden
| | - A Sundin
- Radiology, Department of Surgical Sciences, Uppsala University, Uppsala University Hospital, entry 70, 1st floor, Uppsala, 751 85, Sweden
| | - T Hansen
- Radiology, Department of Surgical Sciences, Uppsala University, Uppsala University Hospital, entry 70, 1st floor, Uppsala, 751 85, Sweden
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Erasmus LT, Strange CD, Ahuja J, Agrawal R, Shroff GS, Marom EM, Truong MT. Imaging of Lung Cancer Staging: TNM 9 Updates. Semin Ultrasound CT MR 2024; 45:410-419. [PMID: 39069273 DOI: 10.1053/j.sult.2024.07.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/30/2024]
Abstract
Imaging plays a key role in clinical staging of lung cancer and guiding therapy. A thorough understanding of the staging system including the nomenclature and updates is necessary to tailor treatment plans and optimize patient care. The 9th edition of the Tumor, Node, Metastasis staging system for lung cancer has no changes for T classification and subdivides N2 and M1c categories. In nodal staging, N2 splits into N2a, ipsilateral mediastinal single station involvement and N2b, ipsilateral mediastinal multiple stations involvement. In the staging of multiple extrathoracic metastases, M1c splits into M1c1, multiple extrathoracic metastases in one organ system and M1c2, multiple extrathoracic metastases in multiple organ systems. Awareness of the proposed changes in TNM-9 staging classification is essential to provide methodical and accurate imaging interpretation.
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Affiliation(s)
- Lauren T Erasmus
- Department of Radiation Oncology, Baylor College of Medicine, Houston, TX
| | - Chad D Strange
- Department of Thoracic Imaging, University of Texas MD Anderson Cancer Center, Houston, TX
| | - Jitesh Ahuja
- Department of Thoracic Imaging, University of Texas MD Anderson Cancer Center, Houston, TX
| | - Rishi Agrawal
- Department of Thoracic Imaging, University of Texas MD Anderson Cancer Center, Houston, TX
| | - Girish S Shroff
- Department of Thoracic Imaging, University of Texas MD Anderson Cancer Center, Houston, TX
| | - Edith M Marom
- Department of Radiology, Chaim Sheba Medical Center, Tel Aviv, Israel
| | - Mylene T Truong
- Department of Thoracic Imaging, University of Texas MD Anderson Cancer Center, Houston, TX.
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Wang J, O’Dwyer E, Martinez Zuloaga J, Subramanian K, Hu JC, Jhanwar YS, Nagar H, RoyChoudhury A, Babich J, Huicochea Castellanos S, Osborne JR, Margolis DJA. Reasons for Discordance between 68Ga-PSMA-PET and Magnetic Resonance Imaging in Men with Metastatic Prostate Cancer. Cancers (Basel) 2024; 16:2056. [PMID: 38893178 PMCID: PMC11171071 DOI: 10.3390/cancers16112056] [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: 04/22/2024] [Revised: 05/22/2024] [Accepted: 05/27/2024] [Indexed: 06/21/2024] Open
Abstract
BACKGROUND PSMA PET has emerged as a "gold standard" imaging modality for assessing prostate cancer metastases. However, it is not universally available, and this limits its impact. In contrast, whole-body MRI is much more widely available but misses more lesions. This study aims to improve the interpretation of whole-body MRI by comparing false negative scans retrospectively to PSMA PET. METHODS This study was a retrospective sub-analysis of a prospectively collected database of patients who participated in a clinical trial of PSMA PET/MRI comparing PSMA PET and whole-body MRI from 2018-2021. Subjects whose separately read PSMA PET and MRI diagnostic reports showed discrepancies ("false negative" MRI cases) were selected for sub-analysis. The cases were reviewed by the same attending radiologist who originally read the scans. The radiologist noted specific features on MRI indicating metastatic disease that were initially missed. RESULTS Of 263 cases, 38 (14%) met the inclusion criteria and were reviewed. Six classes of mpMRI false negatives were identified: anatomically normal (18, 47%), atypical MRI appearance (6, 16%), mischaracterization (1, 3%), undercall (6, 16%), obscured (4, 11%), and no abnormality on MRI (3, 8%). Considering that the atypical and undercalled cases could have been adjusted in retrospect, and that 4 additional cases had positive lesions to the same extent and 11 further cases had disease confined to the pelvis, only 11 (4%) of the original 263 would have had disease outside of a conventional radiation treatment plan. CONCLUSION Notably, almost 50% of the cases, including most lymph node metastases, were anatomically normal using standard criteria. This suggests that current anatomic criteria for evaluating prostate cancer lymph node metastases are not ideal, and there is a need for improved criteria. In addition, 32% of cases involved some element of human interpretive error, and, therefore, improving reader training may lead to more accurate results.
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Affiliation(s)
- Jade Wang
- Department of Internal Medicine, New York-Presbyterian Hospital, New York, NY 10065, USA
| | - Elisabeth O’Dwyer
- Department of Radiology, Weill Cornell Medical College, New York, NY 10065, USA
| | | | - Kritika Subramanian
- Department of Radiology, Weill Cornell Medical College, New York, NY 10065, USA
| | - Jim C. Hu
- Department of Urology, Weill Cornell Medical College, New York, NY 10065, USA
| | - Yuliya S. Jhanwar
- Department of Radiology, Weill Cornell Medical College, New York, NY 10065, USA
| | - Himanshu Nagar
- Department of Radiation Oncology, Weill Cornell Medical College, New York, NY 10065, USA;
| | - Arindam RoyChoudhury
- Department of Population Health Sciences, Weill Cornell Medical College, New York, NY 10065, USA
| | - John Babich
- Ratio Therapeutics, Inc., Boston, MA 02210, USA
| | | | - Joseph R. Osborne
- Department of Radiology, Weill Cornell Medical College, New York, NY 10065, USA
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Cavion CC, Altmayer S, Forte GC, Feijó Andrade RG, Hochhegger DQDR, Zaguini Francisco M, Camargo C, Patel P, Hochhegger B. Diagnostic Performance of MRI for the Detection of Pulmonary Nodules: A Systematic Review and Meta-Analysis. Radiol Cardiothorac Imaging 2024; 6:e230241. [PMID: 38634743 PMCID: PMC11056753 DOI: 10.1148/ryct.230241] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2023] [Revised: 02/18/2024] [Accepted: 03/07/2024] [Indexed: 04/19/2024]
Abstract
Purpose To perform a meta-analysis of the diagnostic performance of MRI for the detection of pulmonary nodules, with use of CT as the reference standard. Materials and Methods PubMed, Embase, Scopus, and other databases were systematically searched for studies published from January 2000 to March 2023 evaluating the performance of MRI for diagnosis of lung nodules measuring 4 mm or larger, with CT as reference. Studies including micronodules, nodules without size stratification, or those from which data for contingency tables could not be extracted were excluded. Primary outcomes were the per-lesion sensitivity of MRI and the rate of false-positive nodules per patient (FPP). Subgroup analysis by size and meta-regression with other covariates were performed. The study protocol was registered in the International Prospective Register of Systematic Reviews, or PROSPERO (no. CRD42023437509). Results Ten studies met inclusion criteria (1354 patients and 2062 CT-detected nodules). Overall, per-lesion sensitivity of MRI for nodules measuring 4 mm or larger was 87.7% (95% CI: 81.1, 92.2), while the FPP rate was 12.4% (95% CI: 7.0, 21.1). Subgroup analyses demonstrated that MRI sensitivity was 98.5% (95% CI: 90.4, 99.8) for nodules measuring at least 8-10 mm and 80.5% (95% CI: 71.5, 87.1) for nodules less than 8 mm. Conclusion MRI demonstrated a good overall performance for detection of pulmonary nodules measuring 4 mm or larger and almost equal performance to CT for nodules measuring at least 8-10 mm, with a low rate of FPP. Systematic review registry no. CRD42023437509 Keywords: Lung Nodule, Lung Cancer, Lung Cancer Screening, MRI, CT Supplemental material is available for this article. © RSNA, 2024.
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Affiliation(s)
- César Campagnolo Cavion
- From the Department of Radiology, Pontifícia Universidade
Católica do Rio Grande do Sul, Av Ipiranga, 6681 – Partenon, Porto
Alegre, Rio Grande do Sul, Brazil, 90619-900 (C.C.C., G.C.F., R.G.F.A.);
Department of Radiology, Stanford University, Stanford, Calif (S.A.); Department
of Radiology, College of Medicine, University of Florida, Gainesville, Fla
(D.Q.d.R.H., P.P., B.H.); and Universidade Federal de Ciências da
Saúde de Porto Alegre, Porto Alegre, Brazil (M.Z.F., C.C.J.)
| | - Stephan Altmayer
- From the Department of Radiology, Pontifícia Universidade
Católica do Rio Grande do Sul, Av Ipiranga, 6681 – Partenon, Porto
Alegre, Rio Grande do Sul, Brazil, 90619-900 (C.C.C., G.C.F., R.G.F.A.);
Department of Radiology, Stanford University, Stanford, Calif (S.A.); Department
of Radiology, College of Medicine, University of Florida, Gainesville, Fla
(D.Q.d.R.H., P.P., B.H.); and Universidade Federal de Ciências da
Saúde de Porto Alegre, Porto Alegre, Brazil (M.Z.F., C.C.J.)
| | - Gabriele Carra Forte
- From the Department of Radiology, Pontifícia Universidade
Católica do Rio Grande do Sul, Av Ipiranga, 6681 – Partenon, Porto
Alegre, Rio Grande do Sul, Brazil, 90619-900 (C.C.C., G.C.F., R.G.F.A.);
Department of Radiology, Stanford University, Stanford, Calif (S.A.); Department
of Radiology, College of Medicine, University of Florida, Gainesville, Fla
(D.Q.d.R.H., P.P., B.H.); and Universidade Federal de Ciências da
Saúde de Porto Alegre, Porto Alegre, Brazil (M.Z.F., C.C.J.)
| | - Rubens Gabriel Feijó Andrade
- From the Department of Radiology, Pontifícia Universidade
Católica do Rio Grande do Sul, Av Ipiranga, 6681 – Partenon, Porto
Alegre, Rio Grande do Sul, Brazil, 90619-900 (C.C.C., G.C.F., R.G.F.A.);
Department of Radiology, Stanford University, Stanford, Calif (S.A.); Department
of Radiology, College of Medicine, University of Florida, Gainesville, Fla
(D.Q.d.R.H., P.P., B.H.); and Universidade Federal de Ciências da
Saúde de Porto Alegre, Porto Alegre, Brazil (M.Z.F., C.C.J.)
| | - Daniela Quinto dos Reis Hochhegger
- From the Department of Radiology, Pontifícia Universidade
Católica do Rio Grande do Sul, Av Ipiranga, 6681 – Partenon, Porto
Alegre, Rio Grande do Sul, Brazil, 90619-900 (C.C.C., G.C.F., R.G.F.A.);
Department of Radiology, Stanford University, Stanford, Calif (S.A.); Department
of Radiology, College of Medicine, University of Florida, Gainesville, Fla
(D.Q.d.R.H., P.P., B.H.); and Universidade Federal de Ciências da
Saúde de Porto Alegre, Porto Alegre, Brazil (M.Z.F., C.C.J.)
| | - Martina Zaguini Francisco
- From the Department of Radiology, Pontifícia Universidade
Católica do Rio Grande do Sul, Av Ipiranga, 6681 – Partenon, Porto
Alegre, Rio Grande do Sul, Brazil, 90619-900 (C.C.C., G.C.F., R.G.F.A.);
Department of Radiology, Stanford University, Stanford, Calif (S.A.); Department
of Radiology, College of Medicine, University of Florida, Gainesville, Fla
(D.Q.d.R.H., P.P., B.H.); and Universidade Federal de Ciências da
Saúde de Porto Alegre, Porto Alegre, Brazil (M.Z.F., C.C.J.)
| | - Capitulino Camargo
- From the Department of Radiology, Pontifícia Universidade
Católica do Rio Grande do Sul, Av Ipiranga, 6681 – Partenon, Porto
Alegre, Rio Grande do Sul, Brazil, 90619-900 (C.C.C., G.C.F., R.G.F.A.);
Department of Radiology, Stanford University, Stanford, Calif (S.A.); Department
of Radiology, College of Medicine, University of Florida, Gainesville, Fla
(D.Q.d.R.H., P.P., B.H.); and Universidade Federal de Ciências da
Saúde de Porto Alegre, Porto Alegre, Brazil (M.Z.F., C.C.J.)
| | - Pratik Patel
- From the Department of Radiology, Pontifícia Universidade
Católica do Rio Grande do Sul, Av Ipiranga, 6681 – Partenon, Porto
Alegre, Rio Grande do Sul, Brazil, 90619-900 (C.C.C., G.C.F., R.G.F.A.);
Department of Radiology, Stanford University, Stanford, Calif (S.A.); Department
of Radiology, College of Medicine, University of Florida, Gainesville, Fla
(D.Q.d.R.H., P.P., B.H.); and Universidade Federal de Ciências da
Saúde de Porto Alegre, Porto Alegre, Brazil (M.Z.F., C.C.J.)
| | - Bruno Hochhegger
- From the Department of Radiology, Pontifícia Universidade
Católica do Rio Grande do Sul, Av Ipiranga, 6681 – Partenon, Porto
Alegre, Rio Grande do Sul, Brazil, 90619-900 (C.C.C., G.C.F., R.G.F.A.);
Department of Radiology, Stanford University, Stanford, Calif (S.A.); Department
of Radiology, College of Medicine, University of Florida, Gainesville, Fla
(D.Q.d.R.H., P.P., B.H.); and Universidade Federal de Ciências da
Saúde de Porto Alegre, Porto Alegre, Brazil (M.Z.F., C.C.J.)
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Mirshahvalad SA, Kohan A, Metser U, Hinzpeter R, Ortega C, Farag A, Veit-Haibach P. Diagnostic performance of whole-body [ 18F]FDG PET/MR in cancer M staging: A systematic review and meta-analysis. Eur Radiol 2024; 34:673-685. [PMID: 37535156 DOI: 10.1007/s00330-023-10009-3] [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: 01/17/2023] [Revised: 05/14/2023] [Accepted: 06/07/2023] [Indexed: 08/04/2023]
Abstract
OBJECTIVES To calculate the pooled diagnostic performances of whole-body [18F]FDG PET/MR in M staging of [18F]FDG-avid cancer entities. METHODS A diagnostic meta-analysis was conducted on the [18F]FDG PET/MR in M staging, including studies: (1) evaluated [18F]FDG PET/MR in detecting distant metastasis; (2) compared[ 18F]FDG PET/MR with histopathology, follow-up, or asynchronous multimodality imaging as the reference standard; (3) provided data for the whole-body evaluation; (4) provided adequate data to calculate the meta-analytic performances. Pooled performances were calculated with their confidence interval. In addition, forest plots, SROC curves, and likelihood ratio scatterplots were drawn. All analyses were performed using STATA 16. RESULTS From 52 eligible studies, 2289 patients and 2072 metastases were entered in the meta-analysis. The whole-body pooled sensitivities were 0.95 (95%CI: 0.91-0.97) and 0.97 (95%CI: 0.91-0.99) at the patient and lesion levels, respectively. The pooled specificities were 0.99 (95%CI: 0.97-1.00) and 0.97 (95%CI: 0.90-0.99), respectively. Additionally, subgroup analyses were performed. The calculated pooled sensitivities for lung, gastrointestinal, breast, and gynecological cancers were 0.90, 0.93, 1.00, and 0.97, respectively. The pooled specificities were 1.00, 0.98, 0.97, and 1.00, respectively. Furthermore, the pooled sensitivities for non-small cell lung, colorectal, and cervical cancers were 0.92, 0.96, and 0.86, respectively. The pooled specificities were 1.00, 0.95, and 1.00, respectively. CONCLUSION [18F]FDG PET/MR was a highly accurate modality in M staging in the reported [18F]FDG-avid malignancies. The results showed high sensitivity and specificity in each reviewed malignancy type. Thus, our findings may help clinicians and patients to be confident about the performance of [18F]FDG PET/MR in the clinic. CLINICAL RELEVANCE STATEMENT Although [18F]FDG PET/MR is not a routine imaging technique in current guidelines, mostly due to its availability and logistic issues, our findings might add to the limited evidence regarding its performance, showing a sensitivity of 0.95 and specificity of 0.97. KEY POINTS • The whole-body [18F]FDG PET/MR showed high accuracy in detecting distant metastases at both patient and lesion levels. • The pooled sensitivities were 95% and 97% and pooled specificities were 99% and 97% at patient and lesion levels, respectively. • The results suggested that 18F-FDG PET/MR was a strong modality in the exclusion and confirmation of distant metastases.
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Affiliation(s)
- Seyed Ali Mirshahvalad
- Joint Department of Medical Imaging, University Medical Imaging Toronto, University Health Network, Sinai Health System, Women's College Hospital, University of Toronto, Toronto General Hospital, 585 University Avenue, Toronto, Ontario, M5G 2N2, Canada.
| | - Andres Kohan
- Joint Department of Medical Imaging, University Medical Imaging Toronto, University Health Network, Sinai Health System, Women's College Hospital, University of Toronto, Toronto General Hospital, 585 University Avenue, Toronto, Ontario, M5G 2N2, Canada
| | - Ur Metser
- Joint Department of Medical Imaging, University Medical Imaging Toronto, University Health Network, Sinai Health System, Women's College Hospital, University of Toronto, Toronto General Hospital, 585 University Avenue, Toronto, Ontario, M5G 2N2, Canada
| | - Ricarda Hinzpeter
- Joint Department of Medical Imaging, University Medical Imaging Toronto, University Health Network, Sinai Health System, Women's College Hospital, University of Toronto, Toronto General Hospital, 585 University Avenue, Toronto, Ontario, M5G 2N2, Canada
| | - Claudia Ortega
- Joint Department of Medical Imaging, University Medical Imaging Toronto, University Health Network, Sinai Health System, Women's College Hospital, University of Toronto, Toronto General Hospital, 585 University Avenue, Toronto, Ontario, M5G 2N2, Canada
| | - Adam Farag
- Joint Department of Medical Imaging, University Medical Imaging Toronto, University Health Network, Sinai Health System, Women's College Hospital, University of Toronto, Toronto General Hospital, 585 University Avenue, Toronto, Ontario, M5G 2N2, Canada
| | - Patrick Veit-Haibach
- Joint Department of Medical Imaging, University Medical Imaging Toronto, University Health Network, Sinai Health System, Women's College Hospital, University of Toronto, Toronto General Hospital, 585 University Avenue, Toronto, Ontario, M5G 2N2, Canada
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Broncano J, Steinbrecher K, Marquis KM, Raptis CA, Royuela Del Val J, Vollmer I, Bhalla S, Luna A. Diffusion-weighted Imaging of the Chest: A Primer for Radiologists. Radiographics 2023; 43:e220138. [PMID: 37347699 DOI: 10.1148/rg.220138] [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: 06/24/2023]
Abstract
Diffusion-weighted imaging (DWI) is a fundamental sequence not only in neuroimaging but also in oncologic imaging and has emerging applications for MRI evaluation of the chest. DWI can be used in clinical practice to enhance lesion conspicuity, tissue characterization, and treatment response. While the spatial resolution of DWI is in the order of millimeters, changes in diffusion can be measured on the micrometer scale. As such, DWI sequences can provide important functional information to MRI evaluation of the chest but require careful optimization of acquisition parameters, notably selection of b values, application of parallel imaging, fat saturation, and motion correction techniques. Along with assessment of morphologic and other functional features, evaluation of DWI signal attenuation and apparent diffusion coefficient maps can aid in tissue characterization. DWI is a noninvasive noncontrast acquisition with an inherent quantitative nature and excellent reproducibility. The outstanding contrast-to-noise ratio provided by DWI can be used to improve detection of pulmonary, mediastinal, and pleural lesions, to identify the benign nature of complex cysts, to characterize the solid portions of cystic lesions, and to classify chest lesions as benign or malignant. DWI has several advantages over fluorine 18 (18F)-fluorodeoxyglucose PET/CT in the assessment, TNM staging, and treatment monitoring of lung cancer and other thoracic neoplasms with conventional or more recently developed therapies. © RSNA, 2023 Quiz questions for this article are available in the supplemental material. Supplemental material and the slide presentation from the RSNA Annual Meeting are available for this article.
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Affiliation(s)
- Jordi Broncano
- From the Cardiothoracic Imaging Unit (J.B.) and Department of Radiology (J.B., J.R.d.V.), Hospital San Juan de Dios, HT-RESSALTA, HT Médica, Avenida el Brillante No. 36, 14012 Córdoba, Spain; Cardiothoracic Imaging Section, Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, Mo (K.S., K.M.M., C.A.R., S.B.); Cardiothoracic Imaging Section, Department of Radiology, Hospital Clínic de Barcelona, Barcelona, Spain (I.V.); and MRI Section, Department of Radiology, Clínica Las Nieves, HT-SERCOSA, HT Médica, Jaén, Spain (A.L.)
| | - Kacie Steinbrecher
- From the Cardiothoracic Imaging Unit (J.B.) and Department of Radiology (J.B., J.R.d.V.), Hospital San Juan de Dios, HT-RESSALTA, HT Médica, Avenida el Brillante No. 36, 14012 Córdoba, Spain; Cardiothoracic Imaging Section, Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, Mo (K.S., K.M.M., C.A.R., S.B.); Cardiothoracic Imaging Section, Department of Radiology, Hospital Clínic de Barcelona, Barcelona, Spain (I.V.); and MRI Section, Department of Radiology, Clínica Las Nieves, HT-SERCOSA, HT Médica, Jaén, Spain (A.L.)
| | - Kaitlin M Marquis
- From the Cardiothoracic Imaging Unit (J.B.) and Department of Radiology (J.B., J.R.d.V.), Hospital San Juan de Dios, HT-RESSALTA, HT Médica, Avenida el Brillante No. 36, 14012 Córdoba, Spain; Cardiothoracic Imaging Section, Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, Mo (K.S., K.M.M., C.A.R., S.B.); Cardiothoracic Imaging Section, Department of Radiology, Hospital Clínic de Barcelona, Barcelona, Spain (I.V.); and MRI Section, Department of Radiology, Clínica Las Nieves, HT-SERCOSA, HT Médica, Jaén, Spain (A.L.)
| | - Constantin A Raptis
- From the Cardiothoracic Imaging Unit (J.B.) and Department of Radiology (J.B., J.R.d.V.), Hospital San Juan de Dios, HT-RESSALTA, HT Médica, Avenida el Brillante No. 36, 14012 Córdoba, Spain; Cardiothoracic Imaging Section, Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, Mo (K.S., K.M.M., C.A.R., S.B.); Cardiothoracic Imaging Section, Department of Radiology, Hospital Clínic de Barcelona, Barcelona, Spain (I.V.); and MRI Section, Department of Radiology, Clínica Las Nieves, HT-SERCOSA, HT Médica, Jaén, Spain (A.L.)
| | - Javier Royuela Del Val
- From the Cardiothoracic Imaging Unit (J.B.) and Department of Radiology (J.B., J.R.d.V.), Hospital San Juan de Dios, HT-RESSALTA, HT Médica, Avenida el Brillante No. 36, 14012 Córdoba, Spain; Cardiothoracic Imaging Section, Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, Mo (K.S., K.M.M., C.A.R., S.B.); Cardiothoracic Imaging Section, Department of Radiology, Hospital Clínic de Barcelona, Barcelona, Spain (I.V.); and MRI Section, Department of Radiology, Clínica Las Nieves, HT-SERCOSA, HT Médica, Jaén, Spain (A.L.)
| | - Ivan Vollmer
- From the Cardiothoracic Imaging Unit (J.B.) and Department of Radiology (J.B., J.R.d.V.), Hospital San Juan de Dios, HT-RESSALTA, HT Médica, Avenida el Brillante No. 36, 14012 Córdoba, Spain; Cardiothoracic Imaging Section, Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, Mo (K.S., K.M.M., C.A.R., S.B.); Cardiothoracic Imaging Section, Department of Radiology, Hospital Clínic de Barcelona, Barcelona, Spain (I.V.); and MRI Section, Department of Radiology, Clínica Las Nieves, HT-SERCOSA, HT Médica, Jaén, Spain (A.L.)
| | - Sanjeev Bhalla
- From the Cardiothoracic Imaging Unit (J.B.) and Department of Radiology (J.B., J.R.d.V.), Hospital San Juan de Dios, HT-RESSALTA, HT Médica, Avenida el Brillante No. 36, 14012 Córdoba, Spain; Cardiothoracic Imaging Section, Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, Mo (K.S., K.M.M., C.A.R., S.B.); Cardiothoracic Imaging Section, Department of Radiology, Hospital Clínic de Barcelona, Barcelona, Spain (I.V.); and MRI Section, Department of Radiology, Clínica Las Nieves, HT-SERCOSA, HT Médica, Jaén, Spain (A.L.)
| | - Antonio Luna
- From the Cardiothoracic Imaging Unit (J.B.) and Department of Radiology (J.B., J.R.d.V.), Hospital San Juan de Dios, HT-RESSALTA, HT Médica, Avenida el Brillante No. 36, 14012 Córdoba, Spain; Cardiothoracic Imaging Section, Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, Mo (K.S., K.M.M., C.A.R., S.B.); Cardiothoracic Imaging Section, Department of Radiology, Hospital Clínic de Barcelona, Barcelona, Spain (I.V.); and MRI Section, Department of Radiology, Clínica Las Nieves, HT-SERCOSA, HT Médica, Jaén, Spain (A.L.)
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7
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State of the Art MR Imaging for Lung Cancer TNM Stage Evaluation. Cancers (Basel) 2023; 15:cancers15030950. [PMID: 36765907 PMCID: PMC9913625 DOI: 10.3390/cancers15030950] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2022] [Revised: 01/20/2023] [Accepted: 01/28/2023] [Indexed: 02/05/2023] Open
Abstract
Since the Radiology Diagnostic Oncology Group (RDOG) report had been published in 1991, magnetic resonance (MR) imaging had limited clinical availability for thoracic malignancy, as well as pulmonary diseases. However, technical advancements in MR systems, such as sequence and reconstruction methods, and adjustments in the clinical protocol for gadolinium contrast media administration have provided fruitful results and validated the utility of MR imaging (MRI) for lung cancer evaluations. These techniques include: (1) contrast-enhanced MR angiography for T-factor evaluation, (2) short-time inversion recovery turbo spin-echo sequences as well as diffusion-weighted imaging (DWI) for N-factor assessment, and (3) whole-body MRI with and without DWI and with positron emission tomography fused with MRI for M-factor or TNM stage evaluation as well as for postoperative recurrence assessment of lung cancer or other thoracic tumors using 1.5 tesla (T) or 3T systems. According to these fruitful results, the Fleischner Society has changed its position to approve of MRI for lung or thoracic diseases. The purpose of this review is to analyze recent advances in lung MRI with a particular focus on lung cancer evaluation, clinical staging, and recurrence assessment evaluation.
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8
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Zhang C, Liang Z, Liu W, Zeng X, Mo Y. Comparison of whole-body 18F-FDG PET/CT and PET/MRI for distant metastases in patients with malignant tumors: a meta-analysis. BMC Cancer 2023; 23:37. [PMID: 36624425 PMCID: PMC9830828 DOI: 10.1186/s12885-022-10493-8] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2022] [Accepted: 12/28/2022] [Indexed: 01/11/2023] Open
Abstract
BACKGROUND As a first-line imaging modality, whole-body fluorine-18 fluorodeoxyglucose (18F-FDG) positron emission tomography (PET)/computed tomography (CT) and 18F-FDG PET/magnetic resonance imaging (MRI) had been widely applied in clinical practice. However, 18F-FDG PET/MRI may be superior to PET/CT for the diagnosis of distant metastases in patients with advanced-stage. Therefore, it is timely and important to systematically determine the diagnostic accuracy of 18F-FDG PET/MRI compared with that of 18F-FDG PET/CT for the diagnosis of distant metastases. METHODS This study aimed to compare the diagnostic accuracy of 18F-FDG PET/CT and PET/MRI for the diagnosis of distant metastases in patients with malignant tumors. Relevant studies using both 18F-FDG PET/CT and PET/MRI for assessment of distant metastases in patients with malignant tumors were searched in PubMed, Embase, The Cochrane Library, and Scopus from January 2010 to November 2023. Two reviewers independently selected studies according to the inclusion and exclusion criteria. A reviewer extracted relevant data and assessed the quality of the eligible studies. The pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and area under the summary receiver operating characteristic curve (AUC) for 18F-FDG PET/CT and PET/MRI were analyzed. Subgroup analysis was performed. RESULTS Across 14 studies (1042 patients), 18F-FDG PET/MRI had a higher sensitivity (0.87 versus 0.81), AUC value (0.98 versus 0.95), and similar specificity (0.97 versus 0.97), than PET/CT for detecting distant metastases. In 3 studies of breast cancer (182 patients), 18F-FDG PET/MRI had a higher sensitivity (0.95 versus 0.87) and specificity (0.96 versus 0.94) than PET/CT. In 5 studies of lung cancer (429 patients), 18F-FDG PET/CT had a higher sensitivity (0.87 versus 0.84) and a lower specificity (0.95 versus 0.96) to PET/MRI. CONCLUSIONS 18F-FDG PET/MRI and PET/CT both performed well as detectors of distant metastases in patients with malignant tumors, and the former has higher sensitivity. The subgroup analysis highlights that 18F-FDG PET/MRI and PET/CT hold different advantages for distant metastases staging in different tumors, PET/MRI has a higher accuracy in patients with breast cancer patients, while PET/CT has a higher accuracy in patients with lung cancer.
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Affiliation(s)
- Cici Zhang
- Department of Radiology, Guangzhou Red Cross Hospital, Guangzhou, China
| | - Zhishan Liang
- grid.410652.40000 0004 6003 7358Department of Cardiology, The People’s Hospital of Guangxi Zhuang Autonomous Region, Nanning, China
| | - Wei Liu
- Department of Breast, Guangzhou Red Cross Hospital, Guangzhou, China
| | - Xuwen Zeng
- Department of Radiology, Guangzhou Red Cross Hospital, Guangzhou, China
| | - Yuzhen Mo
- Department of Radiotherapy, Guangzhou Red Cross Hospital, No.396, TongFu Road, HaiZhu District, Guangzhou, 510220 Guangdong China
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9
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Saihood A, Karshenas H, Nilchi ARN. Deep fusion of gray level co-occurrence matrices for lung nodule classification. PLoS One 2022; 17:e0274516. [PMID: 36174073 PMCID: PMC9521911 DOI: 10.1371/journal.pone.0274516] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2022] [Accepted: 08/28/2022] [Indexed: 11/19/2022] Open
Abstract
Lung cancer is a serious threat to human health, with millions dying because of its late diagnosis. The computerized tomography (CT) scan of the chest is an efficient method for early detection and classification of lung nodules. The requirement for high accuracy in analyzing CT scan images is a significant challenge in detecting and classifying lung cancer. In this paper, a new deep fusion structure based on the long short-term memory (LSTM) has been introduced, which is applied to the texture features computed from lung nodules through new volumetric grey-level-co-occurrence-matrices (GLCMs), classifying the nodules into benign, malignant, and ambiguous. Also, an improved Otsu segmentation method combined with the water strider optimization algorithm (WSA) is proposed to detect the lung nodules. WSA-Otsu thresholding can overcome the fixed thresholds and time requirement restrictions in previous thresholding methods. Extended experiments are used to assess this fusion structure by considering 2D-GLCM based on 2D-slices and approximating the proposed 3D-GLCM computations based on volumetric 2.5D-GLCMs. The proposed methods are trained and assessed through the LIDC-IDRI dataset. The accuracy, sensitivity, and specificity obtained for 2D-GLCM fusion are 94.4%, 91.6%, and 95.8%, respectively. For 2.5D-GLCM fusion, the accuracy, sensitivity, and specificity are 97.33%, 96%, and 98%, respectively. For 3D-GLCM, the accuracy, sensitivity, and specificity of the proposed fusion structure reached 98.7%, 98%, and 99%, respectively, outperforming most state-of-the-art counterparts. The results and analysis also indicate that the WSA-Otsu method requires a shorter execution time and yields a more accurate thresholding process.
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Affiliation(s)
- Ahmed Saihood
- Artificial Intelligence Department, Faculty of Computer Engineering, University of Isfahan, Isfahan, Iran
- Faculty of Computer Science and Mathematics, University of Thi-Qar, Nasiriyah, Thi-Qar, Iraq
| | - Hossein Karshenas
- Artificial Intelligence Department, Faculty of Computer Engineering, University of Isfahan, Isfahan, Iran
| | - Ahmad Reza Naghsh Nilchi
- Artificial Intelligence Department, Faculty of Computer Engineering, University of Isfahan, Isfahan, Iran
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State of the Art: Lung Cancer Staging Using Updated Imaging Modalities. Bioengineering (Basel) 2022; 9:bioengineering9100493. [PMID: 36290461 PMCID: PMC9598500 DOI: 10.3390/bioengineering9100493] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2022] [Revised: 09/15/2022] [Accepted: 09/16/2022] [Indexed: 11/17/2022] Open
Abstract
Lung cancer is among the most common mortality causes worldwide. This scientific article is a comprehensive review of current knowledge regarding screening, subtyping, imaging, staging, and management of treatment response for lung cancer. The traditional imaging modality for screening and initial lung cancer diagnosis is computed tomography (CT). Recently, a dual-energy CT was proven to enhance the categorization of variable pulmonary lesions. The National Comprehensive Cancer Network (NCCN) recommends usage of fluorodeoxyglucose positron emission tomography (FDG PET) in concert with CT to properly stage lung cancer and to prevent fruitless thoracotomies. Diffusion MR is an alternative to FDG PET/CT that is radiation-free and has a comparable diagnostic performance. For response evaluation after treatment, FDG PET/CT is a potent modality which predicts survival better than CT. Updated knowledge of lung cancer genomic abnormalities and treatment regimens helps to improve the radiologists’ skills. Incorporating the radiologic experience is crucial for precise diagnosis, therapy planning, and surveillance of lung cancer.
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11
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Wu J, Deng H, Zhong H, Wang T, Rao Z, Wang Y, Chen Y, Zhang C. Comparison of 68Ga-FAPI and 18F-FDG PET/CT in the Evaluation of Patients With Newly Diagnosed Non-Small Cell Lung Cancer. Front Oncol 2022; 12:924223. [PMID: 35860594 PMCID: PMC9289292 DOI: 10.3389/fonc.2022.924223] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2022] [Accepted: 06/03/2022] [Indexed: 12/11/2022] Open
Abstract
Purpose Several studies have demonstrated that 68Ga-FAPI PET/CT shows high intratumoral tracer uptake and low normal tissue uptake, allowing for excellent visualization of cancer. The purpose of this study was to compare the ability of 68Ga-FAPI and 18F-FDG PET/CT for the evaluation of newly diagnosed NSCLC. Materials and Methods A prospective analysis of 28 individuals with histopathologically newly confirmed NSCLC that underwent 68Ga-FAPI and 18F-FDG PET/CT was conducted. The performance of two imaging modalities was compared based upon visual assessment, rates of cancer detection, and semi-quantitative parameters (target-to-background ratio [TBR], maximum standard uptake value [SUVmax]) for both primary tumors and metastases. Results In total, this study enrolled 28 participants (13 male, 15 female; median age: 60.5 years, range: 34 – 78 years. <u>For primary tumors, 68Ga-FAPI and 18F-FDG PET/CT have similar detection performance (28 vs. 27). However, 68Ga-FAPI PET/CT was found to more effectively evaluate most metastases as compared to 18F-FDG PET/CT. 68Ga-FAPI PET/CT detecting more metastases present within the lymph nodes (53 vs. 49), pleura (8 vs. 7), liver (4 vs. 1), and bone (41 vs. 35).</u> The SUVmax and TBR values for 68Ga-FAPI were substantially superior to those for 18F-FDG in lymph node, pleural, and bone metastases. While the SUVmax for these two imaging approaches was comparable for hepatic metastases, 68Ga-FAPI exhibited a significantly higher TBR in relation to that of 18F-FDG. In addition, 68Ga-FAPI PET/CT demonstrates excellent N (80% [8/10]) and M (92.9% [26/28]) staging accuracy in NSCLC patients. Conclusions 68Ga-FAPI PET/CT as an examination modality is excellent for evaluation of newly diagnosed NSCLC. 68Ga-FAPI PET/CT improves the detection rates of most metastases and facilitating the superior staging of patients with newly diagnosed NSCLC, relative to that achieved by 18F-FDG PET/CT.
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Affiliation(s)
- Junhao Wu
- Department of Nuclear Medicine, The Affiliated Hospital of Southwest Medical University, Luzhou, China
- Nuclear Medicine and Molecular Imaging Key Laboratory of Sichuan Province, Luzhou, China
- Academician (Expert) Workstation of Sichuan Province, Luzhou, China
| | - Hao Deng
- Department of Nuclear Medicine, The Affiliated Hospital of Southwest Medical University, Luzhou, China
- Nuclear Medicine and Molecular Imaging Key Laboratory of Sichuan Province, Luzhou, China
- Academician (Expert) Workstation of Sichuan Province, Luzhou, China
| | - Haoshu Zhong
- Department of Hematology, Clinical Medicine, Affiliated Hospital of Southwest Medical University, Luzhou, China
- Stem Cell Laboratory, The Clinical Research Institute, Affiliated Hospital of Southwest Medical University, Luzhou, China
| | - Tao Wang
- Department of the General Surgery, The Affiliated Hospital of Southwest Medical University, Luzhou, China
| | - Zijuan Rao
- Department of Nuclear Medicine, The Affiliated Hospital of Southwest Medical University, Luzhou, China
- Nuclear Medicine and Molecular Imaging Key Laboratory of Sichuan Province, Luzhou, China
- Academician (Expert) Workstation of Sichuan Province, Luzhou, China
| | - Yingwei Wang
- Department of Nuclear Medicine, The Affiliated Hospital of Southwest Medical University, Luzhou, China
- Nuclear Medicine and Molecular Imaging Key Laboratory of Sichuan Province, Luzhou, China
- Academician (Expert) Workstation of Sichuan Province, Luzhou, China
| | - Yue Chen
- Department of Nuclear Medicine, The Affiliated Hospital of Southwest Medical University, Luzhou, China
- Nuclear Medicine and Molecular Imaging Key Laboratory of Sichuan Province, Luzhou, China
- Academician (Expert) Workstation of Sichuan Province, Luzhou, China
| | - Chunyin Zhang
- Department of Nuclear Medicine, The Affiliated Hospital of Southwest Medical University, Luzhou, China
- Nuclear Medicine and Molecular Imaging Key Laboratory of Sichuan Province, Luzhou, China
- Academician (Expert) Workstation of Sichuan Province, Luzhou, China
- *Correspondence: Chunyin Zhang,
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12
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Pituitary Metastasis of Non–Small Cell Lung Cancer With High FDG Uptake on PET/CT Pituitary Metastasis of Non–Small Cell Lung Carcinoma. Clin Nucl Med 2022; 47:e506-e508. [DOI: 10.1097/rlu.0000000000004179] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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13
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Development and Validation of a CT-Based Signature for the Prediction of Distant Metastasis Before Treatment of Non-Small Cell Lung Cancer. Acad Radiol 2022; 29 Suppl 2:S62-S72. [PMID: 33402298 DOI: 10.1016/j.acra.2020.12.007] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2020] [Revised: 12/11/2020] [Accepted: 12/11/2020] [Indexed: 01/06/2023]
Abstract
RATIONALE AND OBJECTIVES To develop and validate a radiomics model, a clinical-semantic model and a combined model by using standard methods for the pretreatment prediction of distant metastasis (DM) in patients with non-small-cell lung cancer (NSCLC) and to explore whether the combined model provides added value compared to the individual models. MATERIALS AND METHODS This retrospective study involved 356 patients with NSCLC. According to the image biomarker standardization initiative reference manual, we standardized the image processing and feature extraction using in-house software. Finally, 6692 radiomics features were extracted from each lesion based on contrast-enhanced chest CT images. The least absolute shrinkage selection operator and the recursive feature elimination algorithm were used to select features. The logistic regression classifier was used to build the model. Three models (radiomics model, clinical-semantic model and combined model) were constructed to predict DM in NSCLC. Area under the receiver operating characteristic curves were used to validate the ability of the three models to predict DM. A visual nomogram based on the combined model was developed for DM risk assessment in each patient. RESULTS The receiver operating characteristic curve showed predictive performance for DM of the radiomics model (area under the curve [AUC] values for training and validation were 0.76 [95% CI, 0.704 - 0.820] and 0.76 [95% CI, 0.653 - 0.858], respectively). The combined model had AUCs of 0.78 (95% CI, 0.723 - 0.835) and 0.77 (95% CI, 0.673 - 0.870) in the training and validation cohorts, respectively. Both the radiomics model and combined model performed better than the clinical-semantic model (0.70 [95% CI, 0.634 - 0.760] and 0.67 [95% CI, 0.554 - 0.787] in the training and validation cohorts, respectively). CONCLUSION The radiomics model and combined model may be useful for the prediction of DM in patients with NSCLC.
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Oprea-Lager DE, Cysouw MC, Boellaard R, Deroose CM, de Geus-Oei LF, Lopci E, Bidaut L, Herrmann K, Fournier LS, Bäuerle T, deSouza NM, Lecouvet FE. Bone Metastases Are Measurable: The Role of Whole-Body MRI and Positron Emission Tomography. Front Oncol 2021; 11:772530. [PMID: 34869009 PMCID: PMC8640187 DOI: 10.3389/fonc.2021.772530] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2021] [Accepted: 11/04/2021] [Indexed: 12/14/2022] Open
Abstract
Metastatic tumor deposits in bone marrow elicit differential bone responses that vary with the type of malignancy. This results in either sclerotic, lytic, or mixed bone lesions, which can change in morphology due to treatment effects and/or secondary bone remodeling. Hence, morphological imaging is regarded unsuitable for response assessment of bone metastases and in the current Response Evaluation Criteria In Solid Tumors 1.1 (RECIST1.1) guideline bone metastases are deemed unmeasurable. Nevertheless, the advent of functional and molecular imaging modalities such as whole-body magnetic resonance imaging (WB-MRI) and positron emission tomography (PET) has improved the ability for follow-up of bone metastases, regardless of their morphology. Both these modalities not only have improved sensitivity for visual detection of bone lesions, but also allow for objective measurements of bone lesion characteristics. WB-MRI provides a global assessment of skeletal metastases and for a one-step "all-organ" approach of metastatic disease. Novel MRI techniques include diffusion-weighted imaging (DWI) targeting highly cellular lesions, dynamic contrast-enhanced MRI (DCE-MRI) for quantitative assessment of bone lesion vascularization, and multiparametric MRI (mpMRI) combining anatomical and functional sequences. Recommendations for a homogenization of MRI image acquisitions and generalizable response criteria have been developed. For PET, many metabolic and molecular radiotracers are available, some targeting tumor characteristics not confined to cancer type (e.g. 18F-FDG) while other targeted radiotracers target specific molecular characteristics, such as prostate specific membrane antigen (PSMA) ligands for prostate cancer. Supporting data on quantitative PET analysis regarding repeatability, reproducibility, and harmonization of PET/CT system performance is available. Bone metastases detected on PET and MRI can be quantitatively assessed using validated methodologies, both on a whole-body and individual lesion basis. Both have the advantage of covering not only bone lesions but visceral and nodal lesions as well. Hybrid imaging, combining PET with MRI, may provide complementary parameters on the morphologic, functional, metabolic and molecular level of bone metastases in one examination. For clinical implementation of measuring bone metastases in response assessment using WB-MRI and PET, current RECIST1.1 guidelines need to be adapted. This review summarizes available data and insights into imaging of bone metastases using MRI and PET.
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Affiliation(s)
- Daniela E. Oprea-Lager
- Imaging Group, European Organisation of Research and Treatment in Cancer (EORTC), Brussels, Belgium
- Department of Radiology and Nuclear Medicine, Cancer Center Amsterdam, Amsterdam University Medical Center, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Matthijs C.F. Cysouw
- Department of Radiology and Nuclear Medicine, Cancer Center Amsterdam, Amsterdam University Medical Center, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Ronald Boellaard
- Department of Radiology and Nuclear Medicine, Cancer Center Amsterdam, Amsterdam University Medical Center, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Christophe M. Deroose
- Imaging Group, European Organisation of Research and Treatment in Cancer (EORTC), Brussels, Belgium
- Nuclear Medicine, University Hospitals Leuven, Leuven, Belgium
- Nuclear Medicine & Molecular Imaging, Department of Imaging and Pathology, KU Leuven, Leuven, Belgium
| | - Lioe-Fee de Geus-Oei
- Department of Radiology, Leiden University Medical Center, Leiden, Netherlands
- Biomedical Photonic Imaging Group, University of Twente, Enschede, Netherlands
| | - Egesta Lopci
- Nuclear Medicine Unit, IRCCS – Humanitas Research Hospital, Milan, Italy
| | - Luc Bidaut
- Imaging Group, European Organisation of Research and Treatment in Cancer (EORTC), Brussels, Belgium
- College of Science, University of Lincoln, Lincoln, United Kingdom
| | - Ken Herrmann
- Department of Nuclear Medicine, University of Duisburg-Essen, and German Cancer Consortium (DKTK)-University Hospital Essen, Essen, Germany
| | - Laure S. Fournier
- Imaging Group, European Organisation of Research and Treatment in Cancer (EORTC), Brussels, Belgium
- Paris Cardiovascular Research Center (PARCC), Institut National de la Santé et de la Recherche Médicale (INSERM), Radiology Department, Assistance Publique-Hôpitaux de Paris (AP-HP), Hopital europeen Georges Pompidou, Université de Paris, Paris, France
- European Imaging Biomarkers Alliance (EIBALL), European Society of Radiology, Vienna, Austria
| | - Tobias Bäuerle
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nürnberg, Erlangen, Germany
| | - Nandita M. deSouza
- Imaging Group, European Organisation of Research and Treatment in Cancer (EORTC), Brussels, Belgium
- European Imaging Biomarkers Alliance (EIBALL), European Society of Radiology, Vienna, Austria
- Division of Radiotherapy and Imaging, The Institute of Cancer Research and Royal Marsden NHS Foundation Trust, London, United Kingdom
| | - Frederic E. Lecouvet
- Imaging Group, European Organisation of Research and Treatment in Cancer (EORTC), Brussels, Belgium
- Department of Radiology, Institut de Recherche Expérimentale et Clinique (IREC), Cliniques Universitaires Saint Luc, Université Catholique de Louvain (UCLouvain), Brussels, Belgium
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15
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Radiomics as a New Frontier of Imaging for Cancer Prognosis: A Narrative Review. Diagnostics (Basel) 2021; 11:diagnostics11101796. [PMID: 34679494 PMCID: PMC8534713 DOI: 10.3390/diagnostics11101796] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2021] [Revised: 09/15/2021] [Accepted: 09/23/2021] [Indexed: 12/12/2022] Open
Abstract
The evaluation of the efficacy of different therapies is of paramount importance for the patients and the clinicians in oncology, and it is usually possible by performing imaging investigations that are interpreted, taking in consideration different response evaluation criteria. In the last decade, texture analysis (TA) has been developed in order to help the radiologist to quantify and identify parameters related to tumor heterogeneity, which cannot be appreciated by the naked eye, that can be correlated with different endpoints, including cancer prognosis. The aim of this work is to analyze the impact of texture in the prediction of response and in prognosis stratification in oncology, taking into consideration different pathologies (lung cancer, breast cancer, gastric cancer, hepatic cancer, rectal cancer). Key references were derived from a PubMed query. Hand searching and clinicaltrials.gov were also used. This paper contains a narrative report and a critical discussion of radiomics approaches related to cancer prognosis in different fields of diseases.
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Nardone V, Boldrini L, Grassi R, Franceschini D, Morelli I, Becherini C, Loi M, Greto D, Desideri I. Radiomics in the Setting of Neoadjuvant Radiotherapy: A New Approach for Tailored Treatment. Cancers (Basel) 2021; 13:3590. [PMID: 34298803 PMCID: PMC8303203 DOI: 10.3390/cancers13143590] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2021] [Revised: 07/12/2021] [Accepted: 07/14/2021] [Indexed: 12/11/2022] Open
Abstract
INTRODUCTION Neoadjuvant radiotherapy is currently used mainly in locally advanced rectal cancer and sarcoma and in a subset of non-small cell lung cancer and esophageal cancer, whereas in other diseases it is under investigation. The evaluation of the efficacy of the induction strategy is made possible by performing imaging investigations before and after the neoadjuvant therapy and is usually challenging. In the last decade, texture analysis (TA) has been developed to help the radiologist to quantify and identify the parameters related to tumor heterogeneity, which cannot be appreciated by the naked eye. The aim of this narrative is to review the impact of TA on the prediction of response to neoadjuvant radiotherapy and or chemoradiotherapy. MATERIALS AND METHODS Key references were derived from a PubMed query. Hand searching and ClinicalTrials.gov were also used. RESULTS This paper contains a narrative report and a critical discussion of radiomics approaches in different fields of neoadjuvant radiotherapy, including esophageal cancer, lung cancer, sarcoma, and rectal cancer. CONCLUSIONS Radiomics can shed a light on the setting of neoadjuvant therapies that can be used to tailor subsequent approaches or even to avoid surgery in the future. At the same, these results need to be validated in prospective and multicenter trials.
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Affiliation(s)
- Valerio Nardone
- Department of Precision Medicine, University of Campania “L. Vanvitelli”, 80138 Naples, Italy; (V.N.); (R.G.)
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, 20122 Milan, Italy
| | - Luca Boldrini
- Radiation Oncology Unit, Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168 Rome, Italy;
| | - Roberta Grassi
- Department of Precision Medicine, University of Campania “L. Vanvitelli”, 80138 Naples, Italy; (V.N.); (R.G.)
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, 20122 Milan, Italy
| | - Davide Franceschini
- Radiotherapy and Radiosurgery Department, IRCCS Humanitas Research Hospital, via Manzoni 56, 20089 Milan, Italy;
| | - Ilaria Morelli
- Department of Biomedical, Experimental and Clinical Sciences “Mario Serio”, University of Florence, 50134 Florence, Italy;
| | - Carlotta Becherini
- Department of Biomedical, Experimental and Clinical Sciences “Mario Serio”, University of Florence, 50134 Florence, Italy;
| | - Mauro Loi
- Radiation Oncology Unit, Azienda Ospedaliero Universitaria Careggi, 50139 Florence, Italy; (M.L.); (D.G.); (I.D.)
| | - Daniela Greto
- Radiation Oncology Unit, Azienda Ospedaliero Universitaria Careggi, 50139 Florence, Italy; (M.L.); (D.G.); (I.D.)
| | - Isacco Desideri
- Radiation Oncology Unit, Azienda Ospedaliero Universitaria Careggi, 50139 Florence, Italy; (M.L.); (D.G.); (I.D.)
- Department of Experimental and Clinical Biomedical Sciences “Mario Serio”, University of Florence, 50134 Florence, Italy
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Lapa C, Nestle U, Albert NL, Baues C, Beer A, Buck A, Budach V, Bütof R, Combs SE, Derlin T, Eiber M, Fendler WP, Furth C, Gani C, Gkika E, Grosu AL, Henkenberens C, Ilhan H, Löck S, Marnitz-Schulze S, Miederer M, Mix M, Nicolay NH, Niyazi M, Pöttgen C, Rödel CM, Schatka I, Schwarzenboeck SM, Todica AS, Weber W, Wegen S, Wiegel T, Zamboglou C, Zips D, Zöphel K, Zschaeck S, Thorwarth D, Troost EGC. Value of PET imaging for radiation therapy. Strahlenther Onkol 2021; 197:1-23. [PMID: 34259912 DOI: 10.1007/s00066-021-01812-2] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2021] [Accepted: 06/09/2021] [Indexed: 12/13/2022]
Abstract
This comprehensive review written by experts in their field gives an overview on the current status of incorporating positron emission tomography (PET) into radiation treatment planning. Moreover, it highlights ongoing studies for treatment individualisation and per-treatment tumour response monitoring for various primary tumours. Novel tracers and image analysis methods are discussed. The authors believe this contribution to be of crucial value for experts in the field as well as for policy makers deciding on the reimbursement of this powerful imaging modality.
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Affiliation(s)
- Constantin Lapa
- Nuclear Medicine, Medical Faculty, University of Augsburg, Augsburg, Germany
| | - Ursula Nestle
- Department of Radiation Oncology, Faculty of Medicine, University Medical Center Freiburg, Freiburg, Germany
- German Cancer Consortium (DKTK), Partner Site Freiburg, Freiburg, Germany
- Department of Radiation Oncology, Kliniken Maria Hilf, Mönchengladbach, Germany
| | - Nathalie L Albert
- Department of Nuclear Medicine, University Hospital, LMU Munich, Munich, Germany
| | - Christian Baues
- Department of Radiation Oncology, Cyberknife and Radiotherapy, Medical Faculty, University Hospital Cologne, Cologne, Germany
| | - Ambros Beer
- Department of Nuclear Medicine, Ulm University Hospital, Ulm, Germany
| | - Andreas Buck
- Department of Nuclear Medicine, University Hospital Würzburg, Würzburg, Germany
| | - Volker Budach
- Department of Radiation Oncology, Charité Universitätsmedizin Berlin, Campus Virchow-Klinikum, Berlin, Germany
| | - Rebecca Bütof
- 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
| | - Stephanie E Combs
- German Cancer Consortium (DKTK), Partner Site Munich, Munich, Germany
- Department of Radiation Oncology, Technical University of Munich (TUM), Klinikum rechts der Isar, Munich, Germany
- Department of Radiation Sciences (DRS), Institute of Radiation Medicine (IRM), Neuherberg, Germany
| | - Thorsten Derlin
- Department of Nuclear Medicine, Hannover Medical School, Hannover, Germany
| | - Matthias Eiber
- Department of Nuclear Medicine, Technical University of Munich (TUM), Klinikum rechts der Isar, Munich, Germany
| | - Wolfgang P Fendler
- Department of Nuclear Medicine, University of Duisburg-Essen and German Cancer Consortium (DKTK)-University Hospital Essen, Essen, Germany
| | - Christian Furth
- Department of Nuclear Medicine, Charité-Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health, Berlin, Germany
| | - Cihan Gani
- German Cancer Consortium (DKTK), Partner Site Tübingen, and German Cancer Research Center (DKFZ), Heidelberg, Germany
- Department of Radiation Oncology, University of Tübingen, Tübingen, Germany
| | - Eleni Gkika
- Department of Radiation Oncology, Faculty of Medicine, University Medical Center Freiburg, Freiburg, Germany
| | - Anca-L Grosu
- Department of Radiation Oncology, Faculty of Medicine, University Medical Center Freiburg, Freiburg, Germany
- German Cancer Consortium (DKTK), Partner Site Freiburg, Freiburg, Germany
| | - Christoph Henkenberens
- Department of Radiotherapy and Special Oncology, Medical School Hannover, Hannover, Germany
| | - Harun Ilhan
- Department of Nuclear Medicine, University Hospital, LMU Munich, Munich, Germany
| | - Steffen Löck
- 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
| | - Simone Marnitz-Schulze
- Department of Radiation Oncology, Cyberknife and Radiotherapy, Medical Faculty, University Hospital Cologne, Cologne, Germany
| | - Matthias Miederer
- Department of Nuclear Medicine, University Hospital Mainz, Mainz, Germany
| | - Michael Mix
- Department of Nuclear Medicine, Faculty of Medicine, Medical Center, University of Freiburg, Freiburg, Germany
| | - Nils H Nicolay
- Department of Radiation Oncology, Faculty of Medicine, University Medical Center Freiburg, Freiburg, Germany
- German Cancer Consortium (DKTK), Partner Site Freiburg, Freiburg, Germany
| | - Maximilian Niyazi
- Department of Nuclear Medicine, University Hospital, LMU Munich, Munich, Germany
- German Cancer Consortium (DKTK), Partner Site Munich, Munich, Germany
| | - Christoph Pöttgen
- Department of Radiation Oncology, West German Cancer Centre, University of Duisburg-Essen, Essen, Germany
| | - Claus M Rödel
- German Cancer Consortium (DKTK), Partner Site Frankfurt, and German Cancer Research Center (DKFZ), Heidelberg, Germany
- Department of Radiotherapy and Oncology, Goethe-University Frankfurt, Frankfurt, Germany
| | - Imke Schatka
- Department of Nuclear Medicine, Charité-Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health, Berlin, Germany
| | | | - Andrei S Todica
- Department of Nuclear Medicine, University Hospital, LMU Munich, Munich, Germany
| | - Wolfgang Weber
- Department of Nuclear Medicine, Technical University of Munich (TUM), Klinikum rechts der Isar, Munich, Germany
| | - Simone Wegen
- Department of Radiation Oncology, Cyberknife and Radiotherapy, Medical Faculty, University Hospital Cologne, Cologne, Germany
| | - Thomas Wiegel
- Department of Radiation Oncology, Ulm University Hospital, Ulm, Germany
| | - Constantinos Zamboglou
- Department of Radiation Oncology, Faculty of Medicine, University Medical Center Freiburg, Freiburg, Germany
- German Cancer Consortium (DKTK), Partner Site Freiburg, Freiburg, Germany
| | - Daniel Zips
- German Cancer Consortium (DKTK), Partner Site Tübingen, and German Cancer Research Center (DKFZ), Heidelberg, Germany
- Department of Radiation Oncology, University of Tübingen, Tübingen, Germany
| | - Klaus Zöphel
- 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
- National Center for Tumor Diseases (NCT), Partner Site Dresden, Germany: German Cancer Research Center (DKFZ), Heidelberg, Germany, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany, Helmholtz Association/Helmholtz-Zentrum Dresden-Rossendorf (HZDR), Dresden, Germany
- German Cancer Consortium (DKTK), Partner Site Dresden, and German Cancer Research Center (DKFZ), Heidelberg, Germany
- Department of Nuclear Medicine, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
- Department of Nuclear Medicine, Klinikum Chemnitz gGmbH, Chemnitz, Germany
| | - Sebastian Zschaeck
- Department of Radiation Oncology, Charité-Universitätsmedizin Berlin, Charité-Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health, Berlin, Germany
| | - Daniela Thorwarth
- German Cancer Consortium (DKTK), Partner Site Tübingen, and German Cancer Research Center (DKFZ), Heidelberg, Germany
- Section for Biomedical Physics, Department of Radiation Oncology, University of Tübingen, Tübingen, Germany
| | - Esther G C Troost
- 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.
- National Center for Tumor Diseases (NCT), Partner Site Dresden, Germany: German Cancer Research Center (DKFZ), Heidelberg, Germany, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany, Helmholtz Association/Helmholtz-Zentrum Dresden-Rossendorf (HZDR), Dresden, Germany.
- German Cancer Consortium (DKTK), Partner Site Dresden, and German Cancer Research Center (DKFZ), Heidelberg, Germany.
- Helmholtz-Zentrum Dresden-Rossendorf, Institute of Radiooncology-OncoRay, Dresden, Germany.
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18
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Lapa C, Nestle U, Albert NL, Baues C, Beer A, Buck A, Budach V, Bütof R, Combs SE, Derlin T, Eiber M, Fendler WP, Furth C, Gani C, Gkika E, Grosu AL, Henkenberens C, Ilhan H, Löck S, Marnitz-Schulze S, Miederer M, Mix M, Nicolay NH, Niyazi M, Pöttgen C, Rödel CM, Schatka I, Schwarzenboeck SM, Todica AS, Weber W, Wegen S, Wiegel T, Zamboglou C, Zips D, Zöphel K, Zschaeck S, Thorwarth D, Troost EGC. Value of PET imaging for radiation therapy. Nuklearmedizin 2021; 60:326-343. [PMID: 34261141 DOI: 10.1055/a-1525-7029] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
This comprehensive review written by experts in their field gives an overview on the current status of incorporating positron emission tomography (PET) into radiation treatment planning. Moreover, it highlights ongoing studies for treatment individualisation and per-treatment tumour response monitoring for various primary tumours. Novel tracers and image analysis methods are discussed. The authors believe this contribution to be of crucial value for experts in the field as well as for policy makers deciding on the reimbursement of this powerful imaging modality.
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Affiliation(s)
- Constantin Lapa
- Nuclear Medicine, Medical Faculty, University of Augsburg, Augsburg, Germany
| | - Ursula Nestle
- Department of Radiation Oncology, Faculty of Medicine, University Medical Center Freiburg, Freiburg, Germany.,German Cancer Consortium (DKTK), Partner Site Freiburg, Freiburg, Germany.,Department of Radiation Oncology, Kliniken Maria Hilf, Mönchengladbach, Germany
| | - Nathalie L Albert
- Department of Nuclear Medicine, University Hospital, LMU Munich, Munich, Germany
| | - Christian Baues
- Department of Radiation Oncology, Cyberknife and Radiotherapy, Medical Faculty, University Hospital Cologne, Cologne, Germany
| | - Ambros Beer
- Department of Nuclear Medicine, Ulm University Hospital, Ulm, Germany
| | - Andreas Buck
- Department of Nuclear Medicine, University Hospital Würzburg, Würzburg, Germany
| | - Volker Budach
- Department of Radiation Oncology, Charité-Universitätsmedizin Berlin, Campus Virchow-Klinikum, Berlin, Germany
| | - Rebecca Bütof
- 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
| | - Stephanie E Combs
- German Cancer Consortium (DKTK), Partner Site Munich, Munich, Germany.,Department of Radiation Oncology, Technical University of Munich (TUM), Klinikum rechts der Isar, Munich, Germany.,Department of Radiation Sciences (DRS), Institute of Radiation Medicine (IRM), Neuherberg, Germany
| | - Thorsten Derlin
- Department of Nuclear Medicine, Hannover Medical School, Germany
| | - Matthias Eiber
- Department of Nuclear Medicine, Technical University of Munich (TUM), Klinikum rechts der Isar, Munich, Germany
| | - Wolfgang P Fendler
- Department of Nuclear Medicine, University of Duisburg-Essen and German Cancer Consortium (DKTK)-University Hospital Essen, Essen, Germany
| | - Christian Furth
- Department of Nuclear Medicine, Charité-Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health, Berlin, Germany
| | - Cihan Gani
- German Cancer Consortium (DKTK), Partner Site Tübingen, and German Cancer Research Center (DKFZ), Heidelberg, Germany.,Department of Radiation Oncology, University of Tübingen, Tübingen, Germany
| | - Eleni Gkika
- Department of Radiation Oncology, Faculty of Medicine, University Medical Center Freiburg, Freiburg, Germany
| | - Anca L Grosu
- Department of Radiation Oncology, Faculty of Medicine, University Medical Center Freiburg, Freiburg, Germany.,German Cancer Consortium (DKTK), Partner Site Freiburg, Freiburg, Germany
| | | | - Harun Ilhan
- Department of Nuclear Medicine, University Hospital, LMU Munich, Munich, Germany
| | - Steffen Löck
- 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
| | - Simone Marnitz-Schulze
- Department of Radiation Oncology, Cyberknife and Radiotherapy, Medical Faculty, University Hospital Cologne, Cologne, Germany
| | - Matthias Miederer
- Department of Nuclear Medicine, University Hospital Mainz, Mainz, Germany
| | - Michael Mix
- Department of Nuclear Medicine, Faculty of Medicine, Medical Center, University of Freiburg, Freiburg, Germany
| | - Nils H Nicolay
- Department of Radiation Oncology, Faculty of Medicine, University Medical Center Freiburg, Freiburg, Germany.,German Cancer Consortium (DKTK), Partner Site Freiburg, Freiburg, Germany
| | - Maximilian Niyazi
- Department of Nuclear Medicine, University Hospital, LMU Munich, Munich, Germany.,German Cancer Consortium (DKTK), Partner Site Munich, Munich, Germany
| | - Christoph Pöttgen
- Department of Radiation Oncology, West German Cancer Centre, University of Duisburg-Essen, Essen, Germany
| | - Claus M Rödel
- German Cancer Consortium (DKTK), Partner Site Frankfurt, and German Cancer Research Center (DKFZ), Heidelberg, Germany.,Department of Radiotherapy and Oncology, Goethe University Frankfurt, Frankfurt, Germany
| | - Imke Schatka
- Department of Nuclear Medicine, Charité-Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health, Berlin, Germany
| | | | - Andrei S Todica
- Department of Nuclear Medicine, University Hospital, LMU Munich, Munich, Germany
| | - Wolfgang Weber
- Department of Nuclear Medicine, Technical University of Munich (TUM), Klinikum rechts der Isar, Munich, Germany
| | - Simone Wegen
- Department of Radiation Oncology, Cyberknife and Radiotherapy, Medical Faculty, University Hospital Cologne, Cologne, Germany
| | - Thomas Wiegel
- Department of Radiation Oncology, Ulm University Hospital, Ulm, Germany
| | - Constantinos Zamboglou
- Department of Radiation Oncology, Faculty of Medicine, University Medical Center Freiburg, Freiburg, Germany.,German Cancer Consortium (DKTK), Partner Site Freiburg, Freiburg, Germany
| | - Daniel Zips
- German Cancer Consortium (DKTK), Partner Site Tübingen, and German Cancer Research Center (DKFZ), Heidelberg, Germany.,Department of Radiation Oncology, University of Tübingen, Tübingen, Germany
| | - Klaus Zöphel
- 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.,National Center for Tumor Diseases (NCT), Partner Site Dresden, Germany: German Cancer Research Center (DKFZ), Heidelberg, Germany; Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany; Helmholtz Association/Helmholtz-Zentrum Dresden-Rossendorf (HZDR), Dresden, Germany.,German Cancer Consortium (DKTK), Partner Site Dresden, and German Cancer Research Center (DKFZ), Heidelberg, Germany.,Department of Nuclear Medicine, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany.,Department of Nuclear Medicine, Klinikum Chemnitz gGmbH, Chemnitz, Germany
| | - Sebastian Zschaeck
- Department of Radiation Oncology, Charité-Universitätsmedizin Berlin, Charité-Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health, Berlin, Germany
| | - Daniela Thorwarth
- German Cancer Consortium (DKTK), Partner Site Tübingen, and German Cancer Research Center (DKFZ), Heidelberg, Germany.,Section for Biomedical Physics, Department of Radiation Oncology, University of Tübingen, Tübingen, Germany
| | - Esther G C Troost
- 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.,National Center for Tumor Diseases (NCT), Partner Site Dresden, Germany: German Cancer Research Center (DKFZ), Heidelberg, Germany; Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany; Helmholtz Association/Helmholtz-Zentrum Dresden-Rossendorf (HZDR), Dresden, Germany.,German Cancer Consortium (DKTK), Partner Site Dresden, and German Cancer Research Center (DKFZ), Heidelberg, Germany.,Helmholtz-Zentrum Dresden-Rossendorf, Institute of Radiooncology - OncoRay, Dresden, Germany
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19
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Du B, Wang S, Cui Y, Liu G, Li X, Li Y. Can 18F-FDG PET/CT predict EGFR status in patients with non-small cell lung cancer? A systematic review and meta-analysis. BMJ Open 2021; 11:e044313. [PMID: 34103313 PMCID: PMC8190055 DOI: 10.1136/bmjopen-2020-044313] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/20/2023] Open
Abstract
OBJECTIVES This study aimed to explore the diagnostic significance of 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography (PET)/CT for predicting the presence of epidermal growth factor receptor (EGFR) mutations in patients with non-small cell lung cancer (NSCLC). DESIGN A systematic review and meta-analysis. DATA SOURCES The PubMed, EMBASE and Cochrane library databases were searched from the earliest available date to December 2020. ELIGIBILITY CRITERIA FOR SELECTING STUDIES The review included primary studies that compared the mean maximum of standard uptake value (SUVmax) between wild-type and mutant EGFR, and evaluated the diagnostic value of 18F-FDG PET/CT using SUVmax for prediction of EGFR status in patients with NSCLC. DATA EXTRACTION AND SYNTHESIS The main analysis was to assess the sensitivity and specificity, the positive diagnostic likelihood ratio (DLR+) and DLR-, as well as the diagnostic OR (DOR) of SUVmax in prediction of EGFR mutations. Each data point of the summary receiver operator characteristic (SROC) graph was derived from a separate study. A random effects model was used for statistical analysis of the data, and then diagnostic performance for prediction was further assessed. RESULTS Across 15 studies (3574 patients), the pooled sensitivity for 18F-FDG PET/CT was 0.70 (95% CI 0.60 to 0.79) with a pooled specificity of 0.59 (95% CI 0.52 to 0.66). The overall DLR+ was 1.74 (95% CI 1.49 to 2.03) and DLR- was 0.50 (95% CI 0.38 to 0.65). The pooled DOR was 3.50 (95% CI 2.37 to 5.17). The area under the SROC curve was 0.68 (95% CI 0.64 to 0.72). The likelihood ratio scatter plot based on average sensitivity and specificity was in the lower right quadrant. CONCLUSION Meta-analysis results showed 18F-FDG PET/CT had low pooled sensitivity and specificity. The low DOR and the likelihood ratio scatter plot indicated that 18F-FDG PET/CT should be used with caution when predicting EGFR mutations in patients with NSCLC.
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Affiliation(s)
- Bulin Du
- Department of Nuclear Medicine, The First Hospital of China Medical University, Shenyang, China
| | - Shu Wang
- Department of Nuclear Medicine, The First Hospital of China Medical University, Shenyang, China
| | - Yan Cui
- Department of Nuclear Medicine, The First Hospital of China Medical University, Shenyang, China
| | - Guanghui Liu
- Department of Nuclear Medicine, The First Hospital of China Medical University, Shenyang, China
| | - Xuena Li
- Department of Nuclear Medicine, The First Hospital of China Medical University, Shenyang, China
| | - Yaming Li
- Department of Nuclear Medicine, The First Hospital of China Medical University, Shenyang, China
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20
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Zhan Y, Zhang G, Li M, Zhou X. Whole-Body MRI vs. PET/CT for the Detection of Bone Metastases in Patients With Prostate Cancer: A Systematic Review and Meta-Analysis. Front Oncol 2021; 11:633833. [PMID: 34017680 PMCID: PMC8130579 DOI: 10.3389/fonc.2021.633833] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2020] [Accepted: 02/19/2021] [Indexed: 02/05/2023] Open
Abstract
Purpose: A recent meta-analysis in patients with non-small cell lung cancer showed no difference between whole-body magnetic resonance imaging (WBMRI) and positron emission tomography/computed tomography (PET/CT), but no such study is available for prostate cancer (PCa). This study aimed to compare WBMRI and PET/CT for bone metastasis detection in patients with PCa. Materials and Methods: PubMed, Embase, and the Cochrane library were searched for papers published up to April 2020. The population was the patients with untreated prostate cancer diagnosed by WBMRI or PET/CT. The outcomes were the true positive and negative and false positive and negative rates for WBMRI and PET/CT. The summarized sensitivity, specificity, positive likelihood ratios (PLR), negative likelihood ratios (NLR), and diagnostic odds ratios (DOR) were calculated with their 95% confidence intervals (CIs). Results: Four prospective and one retrospective study are included (657 patients). Significant differences are observed between WBMRI and PET/CT for sensitivity (WBMRI/PET/CT: 0.896; 95% CI: 0.813-0.987; P = 0.025) and NLR (WBMRI/PET/CT: 2.38; 95% CI: 1.13-5.01; P = 0.023), but not for specificity (WBMRI/PET/CT: 0.939; 95% CI: 0.855-1.031; P = 0.184) and PLR (WBMRI/PET/CT: 0.42; 95% CI: 0.08-2.22; P = 0.305). WBMRI has a similar a DOR compared with PET/CT (WBMRI/PET/CT: 0.13; 95% CI: 0.02-1.11; P = 0.062). The summary area under the receiver operating characteristic curves for WBMRI is 0.88 (standard error: 0.032) and 0.98 (standard error: 0.013) for PET/CT for diagnosing bone metastases in PCa. Conclusion: PET/CT presents a higher sensitivity and NLR for the bone metastasis detection from PCa, whereas no differences are found for specificity and PLR, compared with WBMRI.
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Affiliation(s)
- Yuefu Zhan
- West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China
- Department of Radiology, Hainan Women and Children's Medical Center, Hainan, China
| | - Guangming Zhang
- West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China
| | - Mingliang Li
- West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China
| | - Xiaobo Zhou
- School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, United States
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21
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Michoux NF, Ceranka JW, Vandemeulebroucke J, Peeters F, Lu P, Absil J, Triqueneaux P, Liu Y, Collette L, Willekens I, Brussaard C, Debeir O, Hahn S, Raeymaekers H, de Mey J, Metens T, Lecouvet FE. Repeatability and reproducibility of ADC measurements: a prospective multicenter whole-body-MRI study. Eur Radiol 2021; 31:4514-4527. [PMID: 33409773 DOI: 10.1007/s00330-020-07522-0] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2020] [Revised: 08/31/2020] [Accepted: 11/13/2020] [Indexed: 12/13/2022]
Abstract
OBJECTIVES Multicenter oncology trials increasingly include MRI examinations with apparent diffusion coefficient (ADC) quantification for lesion characterization and follow-up. However, the repeatability and reproducibility (R&R) limits above which a true change in ADC can be considered relevant are poorly defined. This study assessed these limits in a standardized whole-body (WB)-MRI protocol. METHODS A prospective, multicenter study was performed at three centers equipped with the same 3.0-T scanners to test a WB-MRI protocol including diffusion-weighted imaging (DWI). Eight healthy volunteers per center were enrolled to undergo test and retest examinations in the same center and a third examination in another center. ADC variability was assessed in multiple organs by two readers using two-way mixed ANOVA, Bland-Altman plots, coefficient of variation (CoV), and the upper limit of the 95% CI on repeatability (RC) and reproducibility (RDC) coefficients. RESULTS CoV of ADC was not influenced by other factors (center, reader) than the organ. Based on the upper limit of the 95% CI on RC and RDC (from both readers), a change in ADC in an individual patient must be superior to 12% (cerebrum white matter), 16% (paraspinal muscle), 22% (renal cortex), 26% (central and peripheral zones of the prostate), 29% (renal medulla), 35% (liver), 45% (spleen), 50% (posterior iliac crest), 66% (L5 vertebra), 68% (femur), and 94% (acetabulum) to be significant. CONCLUSIONS This study proposes R&R limits above which ADC changes can be considered as a reliable quantitative endpoint to assess disease or treatment-related changes in the tissue microstructure in the setting of multicenter WB-MRI trials. KEY POINTS • The present study showed the range of R&R of ADC in WB-MRI that may be achieved in a multicenter framework when a standardized protocol is deployed. • R&R was not influenced by the site of acquisition of DW images. • Clinically significant changes in ADC measured in a multicenter WB-MRI protocol performed with the same type of MRI scanner must be superior to 12% (cerebrum white matter), 16% (paraspinal muscle), 22% (renal cortex), 26% (central zone and peripheral zone of prostate), 29% (renal medulla), 35% (liver), 45% (spleen), 50% (posterior iliac crest), 66% (L5 vertebra), 68% (femur), and 94% (acetabulum) to be detected with a 95% confidence level.
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Affiliation(s)
- Nicolas F Michoux
- Institut de Recherche Expérimentale & Clinique (IREC) - Radiology Department, Université Catholique de Louvain (UCLouvain) - Cliniques Universitaires Saint Luc, Avenue Hippocrate 10, B-1200, Brussels, Belgium.
| | - Jakub W Ceranka
- Department of Electronics and Informatics (ETRO), Vrije Universiteit Brussel (VUB), Brussels, Belgium
| | - Jef Vandemeulebroucke
- Department of Electronics and Informatics (ETRO), Vrije Universiteit Brussel (VUB), Brussels, Belgium
| | - Frank Peeters
- Institut de Recherche Expérimentale & Clinique (IREC) - Radiology Department, Université Catholique de Louvain (UCLouvain) - Cliniques Universitaires Saint Luc, Avenue Hippocrate 10, B-1200, Brussels, Belgium
| | - Pierre Lu
- Institut de Recherche Expérimentale & Clinique (IREC) - Radiology Department, Université Catholique de Louvain (UCLouvain) - Cliniques Universitaires Saint Luc, Avenue Hippocrate 10, B-1200, Brussels, Belgium
| | - Julie Absil
- Radiology Department, Université libre de Bruxelles, Hôpital Erasme, Brussels, Belgium
| | - Perrine Triqueneaux
- Institut de Recherche Expérimentale & Clinique (IREC) - Radiology Department, Université Catholique de Louvain (UCLouvain) - Cliniques Universitaires Saint Luc, Avenue Hippocrate 10, B-1200, Brussels, Belgium
| | - Yan Liu
- European Organisation for Research and Treatment of Cancer, Brussels, Belgium
| | - Laurence Collette
- European Organisation for Research and Treatment of Cancer, Brussels, Belgium
| | | | | | - Olivier Debeir
- LISA (Laboratories of Image Synthesis and Analysis), Ecole Polytechnique de Bruxelles, Université libre de Bruxelles, Brussels, Belgium
| | - Stephan Hahn
- LISA (Laboratories of Image Synthesis and Analysis), Ecole Polytechnique de Bruxelles, Université libre de Bruxelles, Brussels, Belgium
| | | | | | - Thierry Metens
- Radiology Department, Université libre de Bruxelles, Hôpital Erasme, Brussels, Belgium
| | - Frédéric E Lecouvet
- Institut de Recherche Expérimentale & Clinique (IREC) - Radiology Department, Université Catholique de Louvain (UCLouvain) - Cliniques Universitaires Saint Luc, Avenue Hippocrate 10, B-1200, Brussels, Belgium
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