1
|
Ruano CA, Veiga J, Antunes N, Carvalho VB, Fernandes O, Borba A, Oliveira FPM, Moraes-Fontes MF, Bilhim T, Irion KL. Segmentation-Based Analysis of T2- and T1-Weighted Dynamic Magnetic Resonance Images Provides Adequate Observer Agreement in the Evaluation of Interstitial Lung Disease. J Comput Assist Tomogr 2024; 48:92-97. [PMID: 37551150 DOI: 10.1097/rct.0000000000001524] [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: 08/09/2023]
Abstract
OBJECTIVE The aim of the study is to quantify observer agreement in the magnetic resonance imaging (MRI) classification of inflammatory or fibrotic interstitial lung disease (ILD). METHODS Our study is a preliminary analysis of a larger prospective cohort. The MRI images of 18 patients with ILD (13 females; mean age, 65 years) were acquired in a 1.5 T scanner and included axial fat-saturated T2-weighted (T2-WI, n = 18) and coronal fat-saturated T1-weighted images before and 1, 3, 5, and 10 minutes after gadolinium administration (n = 16). The MRI studies were evaluated with 2 different methods: a qualitative evaluation (visual assessment and measurement of few regions of interest; evaluations were performed independently by 5 radiologists and 3 times by 1 radiologist) and a segmentation-based analysis with software extraction of signal intensity values (evaluations were performed independently by 2 radiologists and twice by 1 radiologist). Interstitial lung disease was classified as inflammatory or fibrotic, based on previously described imaging criteria. RESULTS Regarding the qualitative evaluation, intraobserver agreement was excellent (κ = 0.92, P < 0.05) for T2-WI and fair (κ = 0.29, P < 0.05) for T1 dynamic study, while interobserver agreement was moderate (κ = 0.56, P < 0.05) and poor (κ = 0.11, P = 0.18), respectively. In contrast, upon segmentation-based analysis, intraobserver and interobserver agreement were excellent for T2-WI (κ = 0.886, P < 0.001; κ = 1.00, P < 0.001; respectively); for T1-WI, intraobserver agreement was excellent (κ = 0.87, P < 0.05) and interobserver agreement was good (κ = 0.75, P < 0.05). CONCLUSIONS Segmentation-based MRI analysis is more reproducible than a qualitative evaluation with visual assessment and measurement of few regions of interest.
Collapse
Affiliation(s)
| | - José Veiga
- From the Department of Radiology, Hospital de Santa Marta, Centro Hospitalar Universitário de Lisboa Central
| | | | - Vera B Carvalho
- From the Department of Radiology, Hospital de Santa Marta, Centro Hospitalar Universitário de Lisboa Central
| | | | - Alexandra Borba
- Department of Pulmonology, Hospital de Santa Marta, Centro Hospitalar Universitário de Lisboa Central
| | | | | | - Tiago Bilhim
- Interventional Radiology Unit, Hospital Curry Cabral, Centro Hospitalar Universitário de Lisboa Central, Lisboa, Portugal
| | - Klaus L Irion
- Department of Radiology, College of Medicine, University of Florida, Gainesville, FL
| |
Collapse
|
2
|
Ruano CA, Moraes-Fontes MF, Borba A, Grafino M, Veiga J, Fernandes O, Bilhim T, Irion KL. Lung Magnetic Resonance Imaging for Prediction of Progression in Patients With Nonidiopathic Pulmonary Fibrosis Interstitial Lung Disease: A Pilot Study. J Thorac Imaging 2023:00005382-990000000-00094. [PMID: 37732700 DOI: 10.1097/rti.0000000000000744] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/22/2023]
Abstract
PURPOSE Correlate magnetic resonance imaging (MRI) parameters at baseline with disease progression in nonidiopathic pulmonary fibrosis interstitial lung disease (ILD). MATERIALS AND METHODS Prospective observational cohort study, in which patients with non-idiopathic pulmonary fibrosis ILD underwent MRI at baseline (1.5 T). T2-weighted images (T2-WI) were acquired by axial free-breathing respiratory-gated fat-suppressed "periodically rotated overlapping parallel lines with enhanced reconstruction" and T1-weighted images (T1-WI) by coronal end-expiratory breath-hold fat-suppressed "volumetric interpolated breath-hold examination" sequences, before and at time points T1, T3, T5, and T10 minutes after gadolinium administration. After MRI segmentation, signal intensity values were extracted by dedicated software. Percentage of the ILD volume and a ratio between signal intensity of ILD (SIILD) and normal lung (SInormal lung) were calculated for T2-WI; percentage of signal intensity (%SI) at each time point, time to peak enhancement, and percent relative enhancement of ILD in comparison with normal lung (%SIILD/normal lung) were calculated for T1-WI. MRI parameters at baseline were correlated with diagnosis of disease progression and variation in percent predicted forced vital capacity (%FVC) and diffusing capacity of the lung for carbon monoxide after 12 months. RESULTS Comprehensive MRI evaluation (T2-WI and T1-WI) was performed in 21 of the 25 patients enrolled (68% females; mean age: 62.6 y). Three of the 24 patients who completed follow-up fulfilled criteria for disease progression. Baseline T2-WI SIILD/SInormal lung was higher for the progression group (P = 0.052). T2-WI SIILD/SInormal lung and T1-WI %SIILD/normal lung at T1 were positively correlated with the 12-month variation in %FVC (r = 0.495, P = 0.014 and r = 0.489, P= 0.034, respectively). CONCLUSIONS Baseline MRI parameters correlate with %FVC decline after 12 months.
Collapse
Affiliation(s)
- Carina A Ruano
- Department of Radiology, Hospital de Santa Marta
- Department of Radiology
- NOVA Medical School, Universidade Nova de Lisboa
| | | | | | | | - José Veiga
- Department of Radiology, Hospital de Santa Marta
| | - Otília Fernandes
- Department of Radiology, Hospital de Santa Marta
- Department of Radiology
| | - Tiago Bilhim
- Interventional Radiology Unit, Department of Radiology, Hospital Curry Cabral, Centro Hospitalar Universitário de Lisboa Central
| | - Klaus L Irion
- Department of Radiology, College of Medicine, University of Florida, Gainesville, FL
| |
Collapse
|
3
|
Ibhagui O, Li D, Han H, Peng G, Meister ML, Gui Z, Qiao J, Salarian M, Dong B, Yuan Y, Xu Y, Yang H, Tan S, Satyanarayana G, Xue S, Turaga RC, Sharma M, Hai Y, Meng Y, Hekmatyar K, Sun P, Sica G, Ji X, Liu ZR, Yang JJ. Early Detection and Staging of Lung Fibrosis Enabled by Collagen-Targeted MRI Protein Contrast Agent. CHEMICAL & BIOMEDICAL IMAGING 2023; 1:268-285. [PMID: 37388961 PMCID: PMC10302889 DOI: 10.1021/cbmi.3c00023] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Revised: 04/17/2023] [Accepted: 04/28/2023] [Indexed: 07/01/2023]
Abstract
Chronic lung diseases, such as idiopathic pulmonary fibrosis (IPF) and chronic obstructive pulmonary disease (COPD), are major leading causes of death worldwide and are generally associated with poor prognoses. The heterogeneous distribution of collagen, mainly type I collagen associated with excessive collagen deposition, plays a pivotal role in the progressive remodeling of the lung parenchyma to chronic exertional dyspnea for both IPF and COPD. To address the pressing need for noninvasive early diagnosis and drug treatment monitoring of pulmonary fibrosis, we report the development of human collagen-targeted protein MRI contrast agent (hProCA32.collagen) to specifically bind to collagen I overexpressed in multiple lung diseases. When compared to clinically approved Gd3+ contrast agents, hProCA32.collagen exhibits significantly better r1 and r2 relaxivity values, strong metal binding affinity and selectivity, and transmetalation resistance. Here, we report the robust detection of early and late-stage lung fibrosis with stage-dependent MRI signal-to-noise ratio (SNR) increase, with good sensitivity and specificity, using a progressive bleomycin-induced IPF mouse model. Spatial heterogeneous mapping of usual interstitial pneumonia (UIP) patterns with key features closely mimicking human IPF, including cystic clustering, honeycombing, and traction bronchiectasis, were noninvasively detected by multiple MR imaging techniques and verified by histological correlation. We further report the detection of fibrosis in the lung airway of an electronic cigarette-induced COPD mouse model, using hProCA32.collagen-enabled precision MRI (pMRI), and validated by histological analysis. The developed hProCA32.collagen is expected to have strong translational potential for the noninvasive detection and staging of lung diseases, and facilitating effective treatment to halt further chronic lung disease progression.
Collapse
Affiliation(s)
- Oluwatosin
Y. Ibhagui
- Department
of Chemistry, Center for Diagnostics and Therapeutics, Advanced Translational
Imaging Facility, Georgia State University, Atlanta, Georgia 30303, United States
| | - Dongjun Li
- Department
of Chemistry, Center for Diagnostics and Therapeutics, Advanced Translational
Imaging Facility, Georgia State University, Atlanta, Georgia 30303, United States
| | - Hongwei Han
- Department
of Biology, Center for Diagnostics and Therapeutics, Georgia State University, Atlanta, Georgia 30303, United States
| | - Guangda Peng
- Department
of Biology, Center for Diagnostics and Therapeutics, Georgia State University, Atlanta, Georgia 30303, United States
| | - Maureen L. Meister
- Department
of Nutrition, Georgia State University, Atlanta, Georgia 30303, United States
| | - Zongxiang Gui
- Department
of Chemistry, Center for Diagnostics and Therapeutics, Advanced Translational
Imaging Facility, Georgia State University, Atlanta, Georgia 30303, United States
| | - Jingjuan Qiao
- Department
of Chemistry, Center for Diagnostics and Therapeutics, Advanced Translational
Imaging Facility, Georgia State University, Atlanta, Georgia 30303, United States
- InLighta
Biosciences, Atlanta, Georgia 30303, United States
| | - Mani Salarian
- Department
of Chemistry, Center for Diagnostics and Therapeutics, Advanced Translational
Imaging Facility, Georgia State University, Atlanta, Georgia 30303, United States
| | - Bin Dong
- Department
of Chemistry, Center for Diagnostics and Therapeutics, Advanced Translational
Imaging Facility, Georgia State University, Atlanta, Georgia 30303, United States
| | - Yi Yuan
- Department
of Biology, Center for Diagnostics and Therapeutics, Georgia State University, Atlanta, Georgia 30303, United States
| | - Yiting Xu
- Department
of Chemistry, Center for Diagnostics and Therapeutics, Advanced Translational
Imaging Facility, Georgia State University, Atlanta, Georgia 30303, United States
| | - Hua Yang
- Department
of Ophthalmology, Emory University, Atlanta, Georgia 30322, United States
| | - Shanshan Tan
- Department
of Chemistry, Center for Diagnostics and Therapeutics, Advanced Translational
Imaging Facility, Georgia State University, Atlanta, Georgia 30303, United States
| | - Ganesh Satyanarayana
- Department
of Biology, Center for Diagnostics and Therapeutics, Georgia State University, Atlanta, Georgia 30303, United States
| | - Shenghui Xue
- InLighta
Biosciences, Atlanta, Georgia 30303, United States
| | - Ravi Chakra Turaga
- Department
of Biology, Center for Diagnostics and Therapeutics, Georgia State University, Atlanta, Georgia 30303, United States
| | - Malvika Sharma
- Department
of Biology, Center for Diagnostics and Therapeutics, Georgia State University, Atlanta, Georgia 30303, United States
| | - Yan Hai
- Department
of Statistics, Georgia State University, Atlanta, Georgia 30303, United States
| | - Yuguang Meng
- Department
of Chemistry, Center for Diagnostics and Therapeutics, Advanced Translational
Imaging Facility, Georgia State University, Atlanta, Georgia 30303, United States
- Emory
National Primate Research Center, Emory
University, Atlanta, Georgia 30329, United States
| | - Khan Hekmatyar
- Department
of Chemistry, Center for Diagnostics and Therapeutics, Advanced Translational
Imaging Facility, Georgia State University, Atlanta, Georgia 30303, United States
| | - Phillip Sun
- Emory
National Primate Research Center, Emory
University, Atlanta, Georgia 30329, United States
| | - Gabriel Sica
- Winship
Cancer Institute, Emory University, Atlanta, Georgia 30322, United States
| | - Xiangming Ji
- Department
of Biology, Center for Diagnostics and Therapeutics, Georgia State University, Atlanta, Georgia 30303, United States
| | - Zhi-ren Liu
- Department
of Nutrition, Georgia State University, Atlanta, Georgia 30303, United States
| | - Jenny J. Yang
- Department
of Chemistry, Center for Diagnostics and Therapeutics, Advanced Translational
Imaging Facility, Georgia State University, Atlanta, Georgia 30303, United States
- InLighta
Biosciences, Atlanta, Georgia 30303, United States
| |
Collapse
|
4
|
Zhou IY, Mascia M, Alba GA, Magaletta M, Ginns LC, Caravan P, Montesi SB. Dynamic Contrast-enhanced MRI Demonstrates Pulmonary Microvascular Abnormalities Months After SARS-CoV-2 Infection. Am J Respir Crit Care Med 2023; 207:1636-1639. [PMID: 37094097 PMCID: PMC10273117 DOI: 10.1164/rccm.202210-1884le] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/26/2023] Open
Affiliation(s)
- Iris Y. Zhou
- Harvard Medical School, Boston, Massachusetts; and
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology
- Institute for Innovation in Imaging, and
| | - Molly Mascia
- Harvard Medical School, Boston, Massachusetts; and
- Division of Pulmonary and Critical Care Medicine, Massachusetts General Hospital, Boston, Massachusetts
| | - George A. Alba
- Harvard Medical School, Boston, Massachusetts; and
- Division of Pulmonary and Critical Care Medicine, Massachusetts General Hospital, Boston, Massachusetts
| | - Michael Magaletta
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology
| | - Leo C. Ginns
- Harvard Medical School, Boston, Massachusetts; and
- Division of Pulmonary and Critical Care Medicine, Massachusetts General Hospital, Boston, Massachusetts
| | - Peter Caravan
- Harvard Medical School, Boston, Massachusetts; and
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology
- Institute for Innovation in Imaging, and
| | - Sydney B. Montesi
- Harvard Medical School, Boston, Massachusetts; and
- Institute for Innovation in Imaging, and
- Division of Pulmonary and Critical Care Medicine, Massachusetts General Hospital, Boston, Massachusetts
| |
Collapse
|
5
|
Montesi SB, Zhou IY, Liang LL, Digumarthy SR, Mercaldo S, Mercaldo N, Seethamraju RT, Rosen BR, Caravan P. Dynamic contrast-enhanced magnetic resonance imaging of the lung reveals important pathobiology in idiopathic pulmonary fibrosis. ERJ Open Res 2021; 7:00907-2020. [PMID: 34760997 PMCID: PMC8573229 DOI: 10.1183/23120541.00907-2020] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2020] [Accepted: 07/21/2021] [Indexed: 01/02/2023] Open
Abstract
Introduction Evidence suggests that abnormalities occur in the lung microvasculature in idiopathic pulmonary fibrosis (IPF). We hypothesised that dynamic contrast-enhanced (DCE)-magnetic resonance imaging (MRI) could detect alterations in permeability, perfusion and extracellular extravascular volume in IPF, thus providing in vivo regional functional information not otherwise available. Methods Healthy controls and IPF subjects underwent DCE-MRI of the thorax using a dynamic volumetric radial sampling sequence and administration of gadoterate meglumine at a dose of 0.1 mmol·kg−1 at 2 mL·s−1. Model-free analysis of signal intensity versus time curves in regions of interest from a lower, middle and upper axial plane, a posterior coronal plane and the whole lung yielded parameters reflective of perfusion and permeability (peak enhancement and rate of contrast arrival (kwashin)) and the extracellular extravascular space (rate of contrast clearance (kwashout)). These imaging parameters were compared between IPF and healthy control subjects, and between fast/slow IPF progressors. Results IPF subjects (n=16, 56% male, age (range) 67.5 (60–79) years) had significantly reduced peak enhancement and slower kwashin in all measured lung regions compared to the healthy volunteers (n=17, 65% male, age (range) 58 (51–63) years) on unadjusted analyses consistent with microvascular alterations. kwashout, as a measure of the extravascular extracellular space, was significantly slower in the lower lung and posterior coronal regions in the IPF subjects consistent with an increased extravascular extracellular space. All estimates were attenuated after adjusting for age. Similar trends were observed, but only the associations with kwashin in certain lung regions remained statistically significant. Among IPF subjects, kwashout rates nearly perfectly discriminated between those with rapidly progressive disease versus those with stable/slowly progressive disease. Conclusions DCE-MRI detects changes in the microvasculature and extravascular extracellular space in IPF, thus providing in vivo regional functional information. Dynamic contrast-enhanced MRI demonstrates important in vivo lung regional microvascular and extravascular extracellular differences between IPF patients and healthy controls. These results signify IPF pathobiology and may have prognostic significance.https://bit.ly/3l14SWM
Collapse
Affiliation(s)
- Sydney B Montesi
- Division of Pulmonary and Critical Care Medicine, Massachusetts General Hospital, Boston, MA, USA.,Institute for Innovation in Imaging, Massachusetts General Hospital, Boston, MA, USA.,Harvard Medical School, Boston, MA, USA.,These authors contributed equally
| | - Iris Y Zhou
- Institute for Innovation in Imaging, Massachusetts General Hospital, Boston, MA, USA.,Harvard Medical School, Boston, MA, USA.,Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, USA.,Dept of Radiology, Massachusetts General Hospital, Boston, MA, USA.,These authors contributed equally
| | - Lloyd L Liang
- Division of Pulmonary and Critical Care Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Subba R Digumarthy
- Harvard Medical School, Boston, MA, USA.,Dept of Radiology, Massachusetts General Hospital, Boston, MA, USA
| | - Sarah Mercaldo
- Dept of Radiology, Massachusetts General Hospital, Boston, MA, USA
| | | | | | - Bruce R Rosen
- Harvard Medical School, Boston, MA, USA.,Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, USA.,Dept of Radiology, Massachusetts General Hospital, Boston, MA, USA
| | - Peter Caravan
- Institute for Innovation in Imaging, Massachusetts General Hospital, Boston, MA, USA.,Harvard Medical School, Boston, MA, USA.,Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, USA.,Dept of Radiology, Massachusetts General Hospital, Boston, MA, USA
| |
Collapse
|
6
|
Vermersch M, Emsen B, Monnet A, Chalaye J, Galletto Pregliasco A, Baranes L, Rahmouni A, Luciani A, Itti E, Mulé S. Chest PET/MRI in Solid Cancers: Comparing the Diagnostic Performance of a Free-Breathing 3D-T1-GRE Stack-of-Stars Volume Interpolated Breath-Hold Examination (StarVIBE) Acquisition With That of a 3D-T1-GRE Volume Interpolated Breath-Hold Examination (VIBE) for Chest Staging During Whole-Body PET/MRI. J Magn Reson Imaging 2021; 55:1683-1693. [PMID: 34730867 DOI: 10.1002/jmri.27981] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2021] [Revised: 10/20/2021] [Accepted: 10/21/2021] [Indexed: 11/07/2022] Open
Abstract
BACKGROUND Whole-body positron emission tomography/magnetic resonance imaging (WB-PET/MRI) is increasingly used in oncology. However, chest staging remains challenging. PURPOSE To compare the diagnostic performance of a free-breathing 3D-T1-GRE stack-of-stars volume interpolated breath-hold examination (StarVIBE) with that of a 3D-T1-GRE volume interpolated breath-hold examination (VIBE) during WB-PET/MRI for chest staging. STUDY TYPE Retrospective, cohort study. POPULATION One hundred and twenty-three patients were referred for initial staging of solid cancer, 46 of whom had pulmonary nodules and 14 had pulmonary metastasis. FIELD STRENGTH/SEQUENCE Free-breathing 3D-T1-GRE stack-of-stars (StarVIBE) and Cartesian 3D-T1-GRE VIBE at 3.0 T. ASSESSMENT Image quality was assessed using a 4-point scale and using the signal-to-noise ratio (SNR) of lung parenchyma and contrast-to-noise ratio (CNR) of pulmonary nodules. Diagnostic performances of both sequences were determined by three independent radiologists for detection of pulmonary nodules, lymph node involvement, and bone metastases using chest CT, pathology, and follow-up as reference standards. STATISTICAL TESTS Paired Student's t-test; chi-squared; Fisher's exact test. A P value <0.05 was considered statistically significant. RESULTS StarVIBE quality was judged as better in 34% of cases and at least equivalent to VIBE in 89% of cases, with significantly higher quality scores (4 [4-4] vs. 3 [3-4], respectively). SNR and CNR values were significantly higher with StarVIBE (8 ± 1.3 and 9.7 ± 4.6, respectively) than with VIBE (1.8 ± 0.2 and 5.5 ± 3.3, respectively). Compared to VIBE, StarVIBE showed significantly higher sensitivity (73% [95% CI 62-82] vs. 44% [95% CI 33-55], respectively) and specificity (95% [95% CI 88-99] vs. 67% [95% CI 56-77]) for pulmonary nodules detection and significantly higher sensitivity (100% [95% CI 89-100] vs. 67% [95% CI 48-82], respectively) for detection of lymph node involvement. Sensitivities for bone metastases detection were not significantly different (100% [95% CI 88-100] vs. 82% [95% CI 63-94], P = 0.054). DATA CONCLUSION Owing to improved SNR and CNR and spatial resolution, a free-breathing 3D stack-of-stars T1-GRE sequence improves chest staging in comparison with standard 3D-T1-GRE VIBE and may be integrated in WB-PET/MRI acquisitions for initial staging of solid cancer. LEVEL OF EVIDENCE 3 TECHNICAL EFFICACY: Stage 2.
Collapse
Affiliation(s)
- Mathilde Vermersch
- Medical Imaging Department, Henri Mondor University Hospital, Créteil, France.,INSERM Equipes 8 & 18, IMRB, University Paris Est Creteil, Créteil, France.,Department of Gastrointestinal Imaging, Lille University Hospital, Lille, France
| | - Berivan Emsen
- Nuclear Medicine Department, Henri Mondor University Hospital, Créteil, France
| | | | - Julia Chalaye
- Nuclear Medicine Department, Henri Mondor University Hospital, Créteil, France
| | | | - Laurence Baranes
- Medical Imaging Department, Henri Mondor University Hospital, Créteil, France
| | - Alain Rahmouni
- Medical Imaging Department, Henri Mondor University Hospital, Créteil, France
| | - Alain Luciani
- Medical Imaging Department, Henri Mondor University Hospital, Créteil, France.,INSERM Equipes 8 & 18, IMRB, University Paris Est Creteil, Créteil, France
| | - Emmanuel Itti
- INSERM Equipes 8 & 18, IMRB, University Paris Est Creteil, Créteil, France.,Nuclear Medicine Department, Henri Mondor University Hospital, Créteil, France
| | - Sébastien Mulé
- Medical Imaging Department, Henri Mondor University Hospital, Créteil, France.,INSERM Equipes 8 & 18, IMRB, University Paris Est Creteil, Créteil, France
| |
Collapse
|
7
|
Biondetti P, Vangel MG, Lahoud RM, Furtado FS, Rosen BR, Groshar D, Canamaque LG, Umutlu L, Zhang EW, Mahmood U, Digumarthy SR, Shepard JAO, Catalano OA. PET/MRI assessment of lung nodules in primary abdominal malignancies: sensitivity and outcome analysis. Eur J Nucl Med Mol Imaging 2021; 48:1976-1986. [PMID: 33415433 DOI: 10.1007/s00259-020-05113-1] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2020] [Accepted: 11/08/2020] [Indexed: 12/19/2022]
Abstract
PURPOSE To evaluate PET/MR lung nodule detection compared to PET/CT or CT, to determine growth of nodules missed by PET/MR, and to investigate the impact of missed nodules on clinical management in primary abdominal malignancies. METHODS This retrospective IRB-approved study included [18F]-FDG PET/MR in 126 patients. All had standard of care chest imaging (SCI) with diagnostic chest CT or PET/CT within 6 weeks of PET/MR that served as standard of reference. Two radiologists assessed lung nodules (size, location, consistency, position, and [18F]-FDG avidity) on SCI and PET/MR. A side-by-side analysis of nodules on SCI and PET/MR was performed. The nodules missed on PET/MR were assessed on follow-up SCI to ascertain their growth (≥ 2 mm); their impact on management was also investigated. RESULTS A total of 505 nodules (mean 4 mm, range 1-23 mm) were detected by SCI in 89/126 patients (66M:60F, mean age 60 years). PET/MR detected 61 nodules for a sensitivity of 28.1% for patient and 12.1% for nodule, with higher sensitivity for > 7 mm nodules (< 30% and > 70% respectively, p < 0.05). 75/337 (22.3%) of the nodules missed on PET/MR (follow-up mean 736 days) demonstrated growth. In patients positive for nodules at SCI and negative at PET/MR, missed nodules did not influence patients' management. CONCLUSIONS Sensitivity of lung nodule detection on PET/MR is affected by nodule size and is lower than SCI. 22.3% of missed nodules increased on follow-up likely representing metastases. Although this did not impact clinical management in study group with primary abdominal malignancy, largely composed of extra-thoracic advanced stage cancers, with possible different implications in patients without extra-thoracic spread.
Collapse
Affiliation(s)
- Pierpaolo Biondetti
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street, White 270, Boston, MA, 02114, USA
| | - Mark G Vangel
- Biostatistics Center, Massachusetts General Hospital, Harvard Medical School, 60 Staniford St, Boston, MA, USA
| | - Rita M Lahoud
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street, White 270, Boston, MA, 02114, USA
| | - Felipe S Furtado
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street, White 270, Boston, MA, 02114, USA
| | - Bruce R Rosen
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street, White 270, Boston, MA, 02114, USA.,Athinoula A Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - David Groshar
- Department of Nuclear Medicine, Assuta Medical Centers, Tel Aviv, Israel.,Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Lina G Canamaque
- Department of Nuclear Medicine. Grupo HM Hospitales, Madrid, Spain
| | - Lale Umutlu
- Department of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Essen, Germany
| | - Eric W Zhang
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street, White 270, Boston, MA, 02114, USA
| | - Umar Mahmood
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street, White 270, Boston, MA, 02114, USA.,Athinoula A Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Subba R Digumarthy
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street, White 270, Boston, MA, 02114, USA
| | - Jo-Anne O Shepard
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street, White 270, Boston, MA, 02114, USA
| | - Onofrio A Catalano
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street, White 270, Boston, MA, 02114, USA. .,Athinoula A Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
| |
Collapse
|
8
|
New Insight into Laboratory Tests and Imaging Modalities for Fast and Accurate Diagnosis of COVID-19: Alternative Suggestions for Routine RT-PCR and CT-A Literature Review. Can Respir J 2020; 2020:4648307. [PMID: 33354252 PMCID: PMC7737466 DOI: 10.1155/2020/4648307] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2020] [Accepted: 11/11/2020] [Indexed: 02/07/2023] Open
Abstract
The globally inimitable and unremitting outbreak of COVID-19 infection confirmed the emergency need for critical detection of human coronavirus infections. Laboratory diagnostic tests and imaging modalities are two test groups used for the detection of COVID-19. Nowadays, real-time polymerase chain reaction (RT-PCR) and computed tomography (CT) have been frequently utilized in the clinic. Some limitations that confront with these tests are false-negative results, tests redone for follow-up procedure, high cost, and unable to do for all patients. To overcome these limitations, modified and alternative tests must be considered. Among these tests, RdRp/Hel RT-PCR assay had the lowest diagnostic limitation and highest sensitivity and specificity for the detection of SARS-CoV-2 RNA in both respiratory tract and nonrespiratory tract clinical specimens. On the other hand, lung ultrasound (LUS) and magnetic resonance imaging (MRI) are CT-alternative imaging modalities for the management, screening, and follow-up of COVID-19 patients.
Collapse
|
9
|
Wolf M, Montesi SB. Novel Imaging Strategies in Systemic Sclerosis. Curr Rheumatol Rep 2020; 22:57. [PMID: 32785794 DOI: 10.1007/s11926-020-00926-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
Abstract
PURPOSE OF REVIEW Imaging modalities such as computed tomography, ultrasound, magnetic resonance imaging, and molecular imaging are being used to evaluate for disease in systemic sclerosis (SSc) patients. Here, we review novel imaging strategies to detect organ and vascular complications of SSc and novel imaging techniques for assessing interstitial lung disease and pulmonary hypertension in other conditions that may have further applicability to SSc. RECENT FINDINGS Imaging techniques can be used to identify disease in the lungs, pulmonary vascular system, heart, skin, vascular tissue, and gastrointestinal tract of SSc patients. These show promise in detecting early disease, many without the use of ionizing radiation. Novel imaging techniques in patients with SSc can be used to detect disease in multiple susceptible organs. These imaging strategies have potential for early disease detection, as well as potential for incorporation into clinical trials to accelerate the development of SSc therapies.
Collapse
Affiliation(s)
- Molly Wolf
- Division of Pulmonary and Critical Care Medicine, Massachusetts General Hospital, 55 Fruit Street, BUL-148, Boston, MA, 02116, USA.,Harvard Medical School, Boston, MA, USA
| | - Sydney B Montesi
- Division of Pulmonary and Critical Care Medicine, Massachusetts General Hospital, 55 Fruit Street, BUL-148, Boston, MA, 02116, USA. .,Harvard Medical School, Boston, MA, USA.
| |
Collapse
|