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Ohno Y, Fujisawa Y, Yoshikawa T, Seki S, Takenaka D, Fujii K, Ito Y, Kimata H, Akino N, Nagata H, Nomura M, Ueda T, Ozawa Y. Dynamic perfusion area-detector CT in non-small cell lung cancer with progressive fibrosing interstitial lung disease. Eur Radiol 2025:10.1007/s00330-025-11653-7. [PMID: 40402289 DOI: 10.1007/s00330-025-11653-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2024] [Revised: 03/24/2025] [Accepted: 04/09/2025] [Indexed: 05/23/2025]
Abstract
OBJECTIVES To determine the capability of dynamic contrast-enhanced (CE-) perfusion area-detector CT (ADCT) for detecting pathological structural changes in stage I non-small cell lung cancer (NSCLC) patients. MATERIALS AND METHODS Sixty-three consecutive stage I NSCLC patients with progressive fibrosing interstitial lung disease (PF-ILD) underwent dynamic CE-perfusion ADCT analyzed by dual-input maximum slope (DMS) methods for total, pulmonary arterial and systemic arterial perfusion (TPDMS, PAPDMS and SAPDMS) maps, surgical treatment and pathological examination. Multicentric ROIs were then placed over sites assessed as normal lung, pulmonary emphysema, GGO or reticular pattern without traction bronchiectasis, reticular pattern with traction bronchiectasis and honeycombing in the resected lung. Next, an analysis of variance (ANOVA) followed by Tukey's honest significant difference (HSD) multiple comparison test was performed for a comparison of each of the perfusion parameters for five groups. Finally, discrimination accuracy for evaluation of lung parenchymal change was compared for all indexes and combined methods. RESULTS PAPDMSs of abnormal lungs were significantly lower than that of normal lungs (p < 0.0001). SAPDMSs of normal or emphysematous lungs were significantly lower than those of others (p < 0.0001). SAPDMS of GGO or reticular pattern without traction bronchiectasis was significantly lower than that for reticular pattern with traction bronchiectasis and honeycombing (p < 0.0001). Discrimination accuracy of combined perfusion index was significantly higher than that of each index (p < 0.0001). CONCLUSION Dynamic CE-perfusion ADCT is useful for detecting pathological structural changes in stage I NSCLC patients with PF-ILD. KEY POINTS Question Can dynamic first-pass contrast-enhanced perfusion matrices evaluate parenchymal lung changes and disease severity of parenchymal diseases in stage I non-small cell lung cancer (NSCLC) patients? Findings Perfusion indexes differentiated significantly among normal lung, emphysema, GGO or reticular pattern without traction bronchiectasis, reticular pattern with traction bronchiectasis and honeycombing and significantly improved discrimination accuracy by combined methods. Clinical relevance Dynamic first-pass contrast-enhanced perfusion area-detector CT has the potential to assess underlying pathologies and pulmonary functional changes in stage I non-small cell carcinoma patients with progressive fibrosing interstitial lung disease.
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Affiliation(s)
- Yoshiharu Ohno
- Department of Diagnostic Radiology, Fujita Health University School of Medicine, Toyoake, Japan.
- Joint Research Laboratory of Advanced Medical Imaging, Fujita Health University School of Mediciine, Toyoake, Japan.
- Division of Functional and Diagnostic Imaging Research, Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Japan.
| | | | - Takeshi Yoshikawa
- Department of Diagnostic Radiology, Fujita Health University School of Medicine, Toyoake, Japan
- Division of Functional and Diagnostic Imaging Research, Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Japan
- Division of Diagnostic Radiology, Hyogo Cancer Center, Akashi, Japan
| | - Shinichiro Seki
- Division of Functional and Diagnostic Imaging Research, Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Japan
- Division of Diagnostic Radiology, Hyogo Cancer Center, Akashi, Japan
| | - Daisuke Takenaka
- Department of Diagnostic Radiology, Fujita Health University School of Medicine, Toyoake, Japan
- Division of Functional and Diagnostic Imaging Research, Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Japan
| | - Kenji Fujii
- Canon Medical Systems Corporation, Otawara, Japan
| | - Yuya Ito
- Canon Medical Systems Corporation, Otawara, Japan
| | | | | | - Hiroyuki Nagata
- Joint Research Laboratory of Advanced Medical Imaging, Fujita Health University School of Mediciine, Toyoake, Japan
| | - Masahiko Nomura
- Department of Diagnostic Radiology, Fujita Health University School of Medicine, Toyoake, Japan
| | - Takahiro Ueda
- Department of Diagnostic Radiology, Fujita Health University School of Medicine, Toyoake, Japan
| | - Yoshiyuki Ozawa
- Department of Diagnostic Radiology, Fujita Health University School of Medicine, Toyoake, Japan
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Ohno Y, Ozawa Y, Nagata H, Bando S, Cong S, Takahashi T, Oshima Y, Hamabuchi N, Matsuyama T, Ueda T, Yoshikawa T, Takenaka D, Toyama H. Area-Detector Computed Tomography for Pulmonary Functional Imaging. Diagnostics (Basel) 2023; 13:2518. [PMID: 37568881 PMCID: PMC10416899 DOI: 10.3390/diagnostics13152518] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Revised: 07/22/2023] [Accepted: 07/25/2023] [Indexed: 08/13/2023] Open
Abstract
An area-detector CT (ADCT) has a 320-detector row and can obtain isotropic volume data without helical scanning within an area of nearly 160 mm. The actual-perfusion CT data within this area can, thus, be obtained by means of continuous dynamic scanning for the qualitative or quantitative evaluation of regional perfusion within nodules, lymph nodes, or tumors. Moreover, this system can obtain CT data with not only helical but also step-and-shoot or wide-volume scanning for body CT imaging. ADCT also has the potential to use dual-energy CT and subtraction CT to enable contrast-enhanced visualization by means of not only iodine but also xenon or krypton for functional evaluations. Therefore, systems using ADCT may be able to function as a pulmonary functional imaging tool. This review is intended to help the reader understand, with study results published during the last a few decades, the basic or clinical evidence about (1) newly applied reconstruction methods for radiation dose reduction for functional ADCT, (2) morphology-based pulmonary functional imaging, (3) pulmonary perfusion evaluation, (4) ventilation assessment, and (5) biomechanical evaluation.
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Affiliation(s)
- Yoshiharu Ohno
- Department of Diagnostic Radiology, Fujita Health University School of Medicine, Toyoake 470-1192, Aichi, Japan
- Joint Research Laboratory of Advanced Medical Imaging, Fujita Health University School of Medicine, Toyoake 470-1192, Aichi, Japan;
| | - Yoshiyuki Ozawa
- Department of Radiology, Fujita Health University School of Medicine, Toyoake 470-1192, Aichi, Japan; (Y.O.)
| | - Hiroyuki Nagata
- Joint Research Laboratory of Advanced Medical Imaging, Fujita Health University School of Medicine, Toyoake 470-1192, Aichi, Japan;
| | - Shuji Bando
- Department of Radiology, Fujita Health University School of Medicine, Toyoake 470-1192, Aichi, Japan; (Y.O.)
| | - Shang Cong
- Department of Radiology, Fujita Health University School of Medicine, Toyoake 470-1192, Aichi, Japan; (Y.O.)
| | - Tomoki Takahashi
- Department of Radiology, Fujita Health University School of Medicine, Toyoake 470-1192, Aichi, Japan; (Y.O.)
| | - Yuka Oshima
- Department of Radiology, Fujita Health University School of Medicine, Toyoake 470-1192, Aichi, Japan; (Y.O.)
| | - Nayu Hamabuchi
- Department of Radiology, Fujita Health University School of Medicine, Toyoake 470-1192, Aichi, Japan; (Y.O.)
| | - Takahiro Matsuyama
- Department of Radiology, Fujita Health University School of Medicine, Toyoake 470-1192, Aichi, Japan; (Y.O.)
| | - Takahiro Ueda
- Department of Radiology, Fujita Health University School of Medicine, Toyoake 470-1192, Aichi, Japan; (Y.O.)
| | - Takeshi Yoshikawa
- Department of Diagnostic Radiology, Hyogo Cancer Center, Akashi 673-0021, Hyogo, Japan
| | - Daisuke Takenaka
- Department of Diagnostic Radiology, Hyogo Cancer Center, Akashi 673-0021, Hyogo, Japan
| | - Hiroshi Toyama
- Department of Radiology, Fujita Health University School of Medicine, Toyoake 470-1192, Aichi, Japan; (Y.O.)
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Ohno Y, Yui M, Yamamoto K, Takenaka D, Koyama H, Nagata H, Ueda T, Ikeda H, Ozawa Y, Toyama H, Yoshikawa T. Chemical Exchange Saturation Transfer MRI: Capability for Predicting Therapeutic Effect of Chemoradiotherapy on Non-Small Cell Lung Cancer Patients. J Magn Reson Imaging 2023; 58:174-186. [PMID: 36971493 DOI: 10.1002/jmri.28691] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2023] [Revised: 03/02/2023] [Accepted: 03/03/2023] [Indexed: 03/29/2023] Open
Abstract
BACKGROUND Amide proton transfer (APT) weighted chemical exchange saturation transfer CEST (APTw/CEST) magnetic resonance imaging (MRI) has been suggested as having the potential for assessing the therapeutic effect of brain tumors or rectal cancer. Moreover, diffusion-weighted imaging (DWI) and positron emission tomography fused with computed tomography by means of 2-[fluorine-18]-fluoro-2-deoxy-D-glucose (FDG-PET/CT) have been suggested as useful in same setting. PURPOSE To compare the capability of APTw/CEST imaging, DWI, and FDG-PET/CT for predicting therapeutic effect of chemoradiotherapy (CRT) on stage III non-small cell lung cancer (NSCLC) patients. STUDY TYPE Prospective. POPULATION Eighty-four consecutive patients with Stage III NSCLC, 45 men (age range, 62-75 years; mean age, 71 years) and 39 women (age range, 57-75 years; mean age, 70 years). All patients were then divided into two groups (Response Evaluation Criteria in Solid Tumors [RECIST] responders, consisting of the complete response and partial response groups, and RECIST non-responders, consisting of the stable disease and progressive disease groups). FIELD STRENGTH/SEQUENCE 3 T, echo planar imaging or fast advanced spin-echo (FASE) sequences for DWI and 2D half Fourier FASE sequences with magnetization transfer pulses for CEST imaging. ASSESSMENT Magnetization transfer ratio asymmetry (MTRasym ) at 3.5 ppm, apparent diffusion coefficient (ADC), and maximum standard uptake value (SUVmax, ) on PET/CT were assessed by means of region of interest (ROI) measurements at primary tumor. STATISTICAL TESTS Kaplan-Meier method followed by log-rank test and Cox proportional hazards regression analysis with multivariate analysis. A P value <0.05 was considered statistically significant. RESULTS Progression-free survival (PFS) and overall survival (OS) had significant difference between two groups. MTRasym at 3.5 ppm (hazard ratio [HR] = 0.70) and SUVmax (HR = 1.41) were identified as significant predictors for PFS. Tumor staging (HR = 0.57) was also significant predictors for OS. DATA CONCLUSION APTw/CEST imaging showed potential performance as DWI and FDG-PET/CT for predicting the therapeutic effect of CRT on stage III NSCLC patients. LEVEL OF EVIDENCE 2 TECHNICAL EFFICACY: Stage 1.
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Affiliation(s)
- Yoshiharu Ohno
- Department of Radiology, Fujita Health University School of Medicine, Toyoake, Japan
- Joint Research Laboratory of Advanced Medical Imaging, Fujita Health University School of Medicine, Toyoake, Japan
- Division of Functional and Diagnostic Imaging Research, Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Japan
| | - Masao Yui
- Canon Medical Systems Corporation, Otawara, Japan
| | | | - Daisuke Takenaka
- Department of Radiology, Fujita Health University School of Medicine, Toyoake, Japan
- Department of Diagnostic Radiology, Hyogo Cancer Center, Akashi, Japan
| | - Hisanobu Koyama
- Department of Radiology, Osaka Police Hospital, Osaka, Japan
- Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Japan
| | - Hiroyuki Nagata
- Joint Research Laboratory of Advanced Medical Imaging, Fujita Health University School of Medicine, Toyoake, Japan
| | - Takahiro Ueda
- Department of Radiology, Fujita Health University School of Medicine, Toyoake, Japan
| | - Hirotaka Ikeda
- Department of Radiology, Fujita Health University School of Medicine, Toyoake, Japan
| | - Yoshiyuki Ozawa
- Department of Radiology, Fujita Health University School of Medicine, Toyoake, Japan
- Department of Radiology, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan
| | - Hiroshi Toyama
- Department of Radiology, Fujita Health University School of Medicine, Toyoake, Japan
| | - Takeshi Yoshikawa
- Department of Radiology, Fujita Health University School of Medicine, Toyoake, Japan
- Division of Functional and Diagnostic Imaging Research, Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Japan
- Department of Diagnostic Radiology, Hyogo Cancer Center, Akashi, Japan
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Wang C, Wu N, Zhang Z, Zhang LX, Yuan XD. Evaluation of the dual vascular supply patterns in ground-glass nodules with a dynamic volume computed tomography. World J Radiol 2022; 14:155-164. [PMID: 35978977 PMCID: PMC9258305 DOI: 10.4329/wjr.v14.i6.155] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/02/2021] [Revised: 04/20/2022] [Accepted: 06/17/2022] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND In recent years, the detection rate of ground-glass nodules (GGNs) has been improved dramatically due to the popularization of low-dose computed tomography (CT) screening with high-resolution CT technique. This presents challenges for the characterization and management of the GGNs, which depends on a thorough investigation and sufficient diagnostic knowledge of the GGNs. In most diagnostic studies of the GGNs, morphological manifestations are used to differentiate benignancy and malignancy. In contrast, few studies are dedicated to the assessment of the hemodynamics, i.e., perfusion parameters of the GGNs.
AIM To assess the dual vascular supply patterns of GGNs on different histopathology and opacities.
METHODS Forty-seven GGNs from 47 patients were prospectively included and underwent the dynamic volume CT. Histopathologic diagnoses were obtained within two weeks after the CT examination. Blood flow from the bronchial artery [bronchial flow (BF)] and pulmonary artery [pulmonary flow (PF)] as well as the perfusion index (PI) = [PF/(PF + BF)] were obtained using first-pass dual-input CT perfusion analysis and compared respectively between different histopathology and lesion types (pure or mixed GGNs) and correlated with the attenuation values of the lesions using one-way ANOVA, student’s t test and Pearson correlation analysis.
RESULTS Of the 47 GGNs (mean diameter, 8.17 mm; range, 5.3-12.7 mm), 30 (64%) were carcinoma, 6 (13%) were atypical adenomatous hyperplasia and 11 (23%) were organizing pneumonia. All perfusion parameters (BF, PF and PI) demonstrated no significant difference among the three conditions (all P > 0.05). The PFs were higher than the BFs in all the three conditions (all P < 0.001). Of the 30 GGN carcinomas, 14 showed mixed GGNs and 16 pure GGNs with a higher PI in the latter (P < 0.01). Of the 17 benign GGNs, 4 showed mixed GGNs and 13 pure GGNs with no significant difference of the PI between the GGN types (P = 0.21). A negative correlation (r = -0.76, P < 0.001) was demonstrated between the CT attenuation values and the PIs in the 30 GGN carcinomas.
CONCLUSION The GGNs are perfused dominantly by the PF regardless of its histopathology while the weight of the BF in the GGN carcinomas increases gradually during the progress of its opacification.
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Affiliation(s)
- Chao Wang
- Department of Graduate, Hebei North University, Zhangjiakou 075000, Hebei Province, China
| | - Ning Wu
- Department of Radiology, The Eighth Medical Center of the People's Liberation Army General Hospital, Beijing 100091, China
| | - Zhuang Zhang
- Department of Graduate, Hebei North University, Zhangjiakou 075000, Hebei Province, China
| | - Lai-Xing Zhang
- Department of Graduate, Hebei North University, Zhangjiakou 075000, Hebei Province, China
| | - Xiao-Dong Yuan
- Department of Radiology, The Eighth Medical Center of the People's Liberation Army General Hospital, Beijing 100091, China
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Guo H, Xu K, Duan G, Wen L, He Y. Progress and future prospective of FDG-PET/CT imaging combined with optimized procedures in lung cancer: toward precision medicine. Ann Nucl Med 2022; 36:1-14. [PMID: 34727331 DOI: 10.1007/s12149-021-01683-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2021] [Accepted: 09/30/2021] [Indexed: 12/19/2022]
Abstract
With a 5-year overall survival of approximately 20%, lung cancer has always been the number one cancer-specific killer all over the world. As a fusion of positron emission computed tomography (PET) and computed tomography (CT), PET/CT has revolutionized cancer imaging over the past 20 years. In this review, we focused on the optimization of the function of 18F-flurodeoxyglucose (FDG)-PET/CT in diagnosis, prognostic prediction and therapy management of lung cancers by computer programs. FDG-PET/CT has demonstrated a surprising role in development of therapeutic biomarkers, prediction of therapeutic responses and long-term survival, which could be conducive to solving existing dilemmas. Meanwhile, novel tracers and optimized procedures are also developed to control the quality and improve the effect of PET/CT. With the continuous development of some new imaging agents and their clinical applications, application value of PET/CT has broad prospects in this area.
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Affiliation(s)
- Haoyue Guo
- Department of Medical Oncology, Shanghai Pulmonary Hospital, Tongji University Medical School Cancer Institute, Tongji University School of Medicine, No. 507 Zhengmin Road, Shanghai, 200433, China
- School of Medicine, Tongji University, No. 1239 Siping Road, Shanghai, 200092, China
| | - Kandi Xu
- Department of Medical Oncology, Shanghai Pulmonary Hospital, Tongji University Medical School Cancer Institute, Tongji University School of Medicine, No. 507 Zhengmin Road, Shanghai, 200433, China
- School of Medicine, Tongji University, No. 1239 Siping Road, Shanghai, 200092, China
| | - Guangxin Duan
- State Key Laboratory of Radiation Medicine and Protection, School for Radiological and Interdisciplinary Sciences (RAD-X), Collaborative Innovation Center of Radiation Medicine of Jiangsu Higher Education Institutions, Soochow University, Suzhou, 215123, China
| | - Ling Wen
- Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, 215000, China.
| | - Yayi He
- Department of Medical Oncology, Shanghai Pulmonary Hospital, Tongji University Medical School Cancer Institute, Tongji University School of Medicine, No. 507 Zhengmin Road, Shanghai, 200433, China.
- School of Medicine, Tongji University, No. 1239 Siping Road, Shanghai, 200092, China.
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CT-based radiomics signatures can predict the tumor response of non-small cell lung cancer patients treated with first-line chemotherapy and targeted therapy. Eur Radiol 2021; 32:1538-1547. [PMID: 34564744 DOI: 10.1007/s00330-021-08277-y] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2020] [Revised: 07/20/2021] [Accepted: 08/08/2021] [Indexed: 12/29/2022]
Abstract
OBJECTIVES The goal of this study was to evaluate the effectiveness of radiomics signatures on pre-treatment computed tomography (CT) images of lungs to predict the tumor responses of non-small cell lung cancer (NSCLC) patients treated with first-line chemotherapy, targeted therapy, or a combination of both. MATERIALS AND METHODS This retrospective study included 322 NSCLC patients who were treated with first-line chemotherapy, targeted therapy, or a combination of both. Of these patients, 224 were randomly assigned to a cohort to help develop the radiomics signature. A total of 1946 radiomics features were obtained from each patient's CT scan. The top-ranked features were selected by the Minimum Redundancy Maximum Relevance (MRMR) feature-ranking method and used to build a lightweight radiomics signature with the Random Forest (RF) classifier. The independent predictive (IP) features (AUC > 0.6, p value < 0.05) were further identified from the top-ranked features and used to build a refined radiomics signature by the RF classifier. Its prediction performance was tested on the validation cohort, which consisted of the remaining 98 patients. RESULTS The initial lightweight radiomics signature constructed from 15 top-ranked features had an AUC of 0.721 (95% CI, 0.619-0.823). After six IP features were further identified and a refined radiomics signature was built, it had an AUC of 0.746 (95% CI, 0.646-0.846). CONCLUSIONS Radiomics signatures based on pre-treatment CT scans can accurately predict tumor response in NSCLC patients after first-line chemotherapy or targeted therapy treatments. Radiomics features could be used as promising prognostic imaging biomarkers in the future. KEY POINTS The radiomics signature extracted from baseline CT images in patients with NSCLC can predict response to first-line chemotherapy, targeted therapy, or both treatments with an AUC = 0.746 (95% CI, 0.646-0.846). The radiomics signature could be used as a new biomarker for quantitative analysis in radiology, which might provide value in decision-making and to define personalized treatments for cancer patients.
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Ohno Y, Seo JB, Parraga G, Lee KS, Gefter WB, Fain SB, Schiebler ML, Hatabu H. Pulmonary Functional Imaging: Part 1-State-of-the-Art Technical and Physiologic Underpinnings. Radiology 2021; 299:508-523. [PMID: 33825513 DOI: 10.1148/radiol.2021203711] [Citation(s) in RCA: 35] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Over the past few decades, pulmonary imaging technologies have advanced from chest radiography and nuclear medicine methods to high-spatial-resolution or low-dose chest CT and MRI. It is currently possible to identify and measure pulmonary pathologic changes before these are obvious even to patients or depicted on conventional morphologic images. Here, key technological advances are described, including multiparametric CT image processing methods, inhaled hyperpolarized and fluorinated gas MRI, and four-dimensional free-breathing CT and MRI methods to measure regional ventilation, perfusion, gas exchange, and biomechanics. The basic anatomic and physiologic underpinnings of these pulmonary functional imaging techniques are explained. In addition, advances in image analysis and computational and artificial intelligence (machine learning) methods pertinent to functional lung imaging are discussed. The clinical applications of pulmonary functional imaging, including both the opportunities and challenges for clinical translation and deployment, will be discussed in part 2 of this review. Given the technical advances in these sophisticated imaging methods and the wealth of information they can provide, it is anticipated that pulmonary functional imaging will be increasingly used in the care of patients with lung disease. © RSNA, 2021 Online supplemental material is available for this article.
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Affiliation(s)
- Yoshiharu Ohno
- From the Department of Radiology, Fujita Health University School of Medicine, Toyoake, Aichi, Japan (Y.O.); Joint Research Laboratory of Advanced Medical Imaging, Fujita Health University School of Medicine, Toyoake, Aichi, Japan (Y.O.); Division of Functional and Diagnostic Imaging Research, Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Hyogo, Japan (Y.O.); Department of Radiology, Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea (J.B.S.); Department of Medicine, Robarts Research Institute, and Department of Medical Biophysics, Western University, London, Canada (G.P.); Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine (SKKU-SOM), Seoul, Korea (K.S.L.); Department of Radiology, Penn Medicine, University of Pennsylvania, Philadelphia, Pa (W.B.G.); Departments of Medical Physics and Radiology (S.B.F., M.L.S.), UW-Madison School of Medicine and Public Health, Madison, Wis; and Center for Pulmonary Functional Imaging, Brigham and Women's Hospital and Harvard Medical School, 75 Francis St, Boston, MA 02215 (H.H.)
| | - Joon Beom Seo
- From the Department of Radiology, Fujita Health University School of Medicine, Toyoake, Aichi, Japan (Y.O.); Joint Research Laboratory of Advanced Medical Imaging, Fujita Health University School of Medicine, Toyoake, Aichi, Japan (Y.O.); Division of Functional and Diagnostic Imaging Research, Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Hyogo, Japan (Y.O.); Department of Radiology, Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea (J.B.S.); Department of Medicine, Robarts Research Institute, and Department of Medical Biophysics, Western University, London, Canada (G.P.); Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine (SKKU-SOM), Seoul, Korea (K.S.L.); Department of Radiology, Penn Medicine, University of Pennsylvania, Philadelphia, Pa (W.B.G.); Departments of Medical Physics and Radiology (S.B.F., M.L.S.), UW-Madison School of Medicine and Public Health, Madison, Wis; and Center for Pulmonary Functional Imaging, Brigham and Women's Hospital and Harvard Medical School, 75 Francis St, Boston, MA 02215 (H.H.)
| | - Grace Parraga
- From the Department of Radiology, Fujita Health University School of Medicine, Toyoake, Aichi, Japan (Y.O.); Joint Research Laboratory of Advanced Medical Imaging, Fujita Health University School of Medicine, Toyoake, Aichi, Japan (Y.O.); Division of Functional and Diagnostic Imaging Research, Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Hyogo, Japan (Y.O.); Department of Radiology, Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea (J.B.S.); Department of Medicine, Robarts Research Institute, and Department of Medical Biophysics, Western University, London, Canada (G.P.); Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine (SKKU-SOM), Seoul, Korea (K.S.L.); Department of Radiology, Penn Medicine, University of Pennsylvania, Philadelphia, Pa (W.B.G.); Departments of Medical Physics and Radiology (S.B.F., M.L.S.), UW-Madison School of Medicine and Public Health, Madison, Wis; and Center for Pulmonary Functional Imaging, Brigham and Women's Hospital and Harvard Medical School, 75 Francis St, Boston, MA 02215 (H.H.)
| | - Kyung Soo Lee
- From the Department of Radiology, Fujita Health University School of Medicine, Toyoake, Aichi, Japan (Y.O.); Joint Research Laboratory of Advanced Medical Imaging, Fujita Health University School of Medicine, Toyoake, Aichi, Japan (Y.O.); Division of Functional and Diagnostic Imaging Research, Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Hyogo, Japan (Y.O.); Department of Radiology, Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea (J.B.S.); Department of Medicine, Robarts Research Institute, and Department of Medical Biophysics, Western University, London, Canada (G.P.); Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine (SKKU-SOM), Seoul, Korea (K.S.L.); Department of Radiology, Penn Medicine, University of Pennsylvania, Philadelphia, Pa (W.B.G.); Departments of Medical Physics and Radiology (S.B.F., M.L.S.), UW-Madison School of Medicine and Public Health, Madison, Wis; and Center for Pulmonary Functional Imaging, Brigham and Women's Hospital and Harvard Medical School, 75 Francis St, Boston, MA 02215 (H.H.)
| | - Warren B Gefter
- From the Department of Radiology, Fujita Health University School of Medicine, Toyoake, Aichi, Japan (Y.O.); Joint Research Laboratory of Advanced Medical Imaging, Fujita Health University School of Medicine, Toyoake, Aichi, Japan (Y.O.); Division of Functional and Diagnostic Imaging Research, Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Hyogo, Japan (Y.O.); Department of Radiology, Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea (J.B.S.); Department of Medicine, Robarts Research Institute, and Department of Medical Biophysics, Western University, London, Canada (G.P.); Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine (SKKU-SOM), Seoul, Korea (K.S.L.); Department of Radiology, Penn Medicine, University of Pennsylvania, Philadelphia, Pa (W.B.G.); Departments of Medical Physics and Radiology (S.B.F., M.L.S.), UW-Madison School of Medicine and Public Health, Madison, Wis; and Center for Pulmonary Functional Imaging, Brigham and Women's Hospital and Harvard Medical School, 75 Francis St, Boston, MA 02215 (H.H.)
| | - Sean B Fain
- From the Department of Radiology, Fujita Health University School of Medicine, Toyoake, Aichi, Japan (Y.O.); Joint Research Laboratory of Advanced Medical Imaging, Fujita Health University School of Medicine, Toyoake, Aichi, Japan (Y.O.); Division of Functional and Diagnostic Imaging Research, Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Hyogo, Japan (Y.O.); Department of Radiology, Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea (J.B.S.); Department of Medicine, Robarts Research Institute, and Department of Medical Biophysics, Western University, London, Canada (G.P.); Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine (SKKU-SOM), Seoul, Korea (K.S.L.); Department of Radiology, Penn Medicine, University of Pennsylvania, Philadelphia, Pa (W.B.G.); Departments of Medical Physics and Radiology (S.B.F., M.L.S.), UW-Madison School of Medicine and Public Health, Madison, Wis; and Center for Pulmonary Functional Imaging, Brigham and Women's Hospital and Harvard Medical School, 75 Francis St, Boston, MA 02215 (H.H.)
| | - Mark L Schiebler
- From the Department of Radiology, Fujita Health University School of Medicine, Toyoake, Aichi, Japan (Y.O.); Joint Research Laboratory of Advanced Medical Imaging, Fujita Health University School of Medicine, Toyoake, Aichi, Japan (Y.O.); Division of Functional and Diagnostic Imaging Research, Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Hyogo, Japan (Y.O.); Department of Radiology, Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea (J.B.S.); Department of Medicine, Robarts Research Institute, and Department of Medical Biophysics, Western University, London, Canada (G.P.); Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine (SKKU-SOM), Seoul, Korea (K.S.L.); Department of Radiology, Penn Medicine, University of Pennsylvania, Philadelphia, Pa (W.B.G.); Departments of Medical Physics and Radiology (S.B.F., M.L.S.), UW-Madison School of Medicine and Public Health, Madison, Wis; and Center for Pulmonary Functional Imaging, Brigham and Women's Hospital and Harvard Medical School, 75 Francis St, Boston, MA 02215 (H.H.)
| | - Hiroto Hatabu
- From the Department of Radiology, Fujita Health University School of Medicine, Toyoake, Aichi, Japan (Y.O.); Joint Research Laboratory of Advanced Medical Imaging, Fujita Health University School of Medicine, Toyoake, Aichi, Japan (Y.O.); Division of Functional and Diagnostic Imaging Research, Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Hyogo, Japan (Y.O.); Department of Radiology, Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea (J.B.S.); Department of Medicine, Robarts Research Institute, and Department of Medical Biophysics, Western University, London, Canada (G.P.); Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine (SKKU-SOM), Seoul, Korea (K.S.L.); Department of Radiology, Penn Medicine, University of Pennsylvania, Philadelphia, Pa (W.B.G.); Departments of Medical Physics and Radiology (S.B.F., M.L.S.), UW-Madison School of Medicine and Public Health, Madison, Wis; and Center for Pulmonary Functional Imaging, Brigham and Women's Hospital and Harvard Medical School, 75 Francis St, Boston, MA 02215 (H.H.)
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8
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Wu Q, Zhong L, Xie X. The value of four imaging modalities to distinguish malignant from benign solitary pulmonary nodules: a study based on 73 cohorts incorporating 7956 individuals. Clin Transl Oncol 2020; 23:296-310. [PMID: 32548796 DOI: 10.1007/s12094-020-02418-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2020] [Accepted: 06/02/2020] [Indexed: 12/19/2022]
Abstract
BACKGROUND Solitary pulmonary nodules (SPNs) frequently bother oncologists. The differentiation of malignant from benign nodules with non-invasive approach remains a tough challenge. This study was designed to assess the diagnostic accuracy of dynamic computed tomography (CT), dynamic magnetic resonance imaging (MRI), fluorine 18 fluorodeoxyglucose (18F-FDG) positron emission tomography (PET), and technetium 99 m (99mTc) depreotide single photon emission computed tomography (SPECT) for SPNs. METHODS Electronic databases of MEDLINE, PubMed, EMBASE, and Cochrane Library were searched to identify relevant trials. The primary evaluation index of diagnostic accuracy was areas under the summary receiver-operating characteristic (SROC) curve. The results were analyzed utilizing Stata 12.0 statistical software. RESULTS Seventy-three trials incorporating 7956 individuals were recruited. Sensitivities, specificities, positive likelihood ratios, negative likelihood ratios, diagnostic score, diagnostic odds ratios, and areas under the SROC curve with 95% confidence intervals were, respectively, 0.92 (0.89-0.95), 0.64 (0.54-0.74), 2.60 (1.98-3.42), 0.12 (0.08-0.17), 3.10 (2.62-3.59), 22.24 (13.67-36.17), and 0.91 (0.88-0.93) for CT; 0.92 (0.86-0.95), 0.85 (0.77-0.90), 6.01 (3.90-9.24), 0.10 (0.06-0.17), 4.12 (3.41-4.82), 61.39 (30.41-123.93), and 0.94 (0.92-0.96) for MRI; 0.90 (0.86-0.93), 0.73 (0.65-0.79), 3.28 (2.56-4.20), 0.14 (0.10-0.19), 3.16 (2.69-3.64), 23.68 (14.74-38.05), and 0.90 (0.87-0.92) for 18F-FDG PET; and 0.93 (0.88-0.96), 0.70 (0.56-0.81), 3.12 (2.03-4.81), 0.10 (0.06-0.17), 3.43 (2.63-4.22), 30.74 (13.84-68.27), and 0.93 (0.91-0.95) for 99mTc-depreotide SPECT. CONCLUSION The dynamic MRI, dynamic CT, 18F-FDG PET, and 99mTc-depreotide SPECT were favorable non-invasive approaches to distinguish malignant SPNs from benign. Moreover, from the viewpoint of cost-effectiveness and avoiding radiation, the dynamic MRI was recommendable for SPNs.
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Affiliation(s)
- Q Wu
- Department of Oncology, The First Affiliated Hospital of Fujian Medical University, Chazhong Road No 20, Fuzhou, 350005, Fujian, China
| | - L Zhong
- Department of Oncology, The First Affiliated Hospital of Fujian Medical University, Chazhong Road No 20, Fuzhou, 350005, Fujian, China.,Department of Medical Oncology, The Second Hospital of Longyan, Fujian, 364000, China
| | - X Xie
- Department of Oncology, The First Affiliated Hospital of Fujian Medical University, Chazhong Road No 20, Fuzhou, 350005, Fujian, China.
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9
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Huang YS, Chen JLY, Chen JY, Lee YF, Huang JY, Kuo SH, Yen RF, Chang YC. Predicting tumor responses and patient survival in chemoradiotherapy-treated patients with non-small-cell lung cancer using dynamic contrast-enhanced integrated magnetic resonance-positron-emission tomography. Strahlenther Onkol 2019; 195:707-718. [PMID: 30610356 DOI: 10.1007/s00066-018-1418-8] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2018] [Accepted: 12/14/2018] [Indexed: 02/08/2023]
Abstract
PURPOSE We investigated whether radiologic parameters by dynamic contrast-enhanced (DCE) integrated magnetic resonance-positron-emission tomography (MR-PET) predicts tumor response to treatment and survival in non-metastatic non-small-cell lung cancer (NSCLC) patients receiving chemoradiotherapy (CRT). METHODS Patients underwent DCE integrated MR-PET imaging 1 week before CRT. The following parameters were analyzed: primary tumor size, gross tumor volume, maximal standardized uptake value (SUVmax), total lesion glycolysis (TLG), apparent diffusion coefficient (ADC), volume transfer constant (Ktrans), reverse reflux rate constant (kep), extracellular extravascular volume fraction (ve), blood plasma volume fraction (vp), and initial area under the time-concentration curve defined over the first 60 s post-enhancement (iAUC60). CRT responses were defined using the revised Response Evaluation Criteria in Solid Tumors (RECIST) guideline (version 1.1). RESULTS Thirty patients were included. Non-responders demonstrated higher baseline TLG (p = 0.012), and lower baseline Ktrans (p = 0.020) and iAUC60 (p = 0.016) compared to responders, indicating the usefulness of DCE integrated MR-PET to predict treatment responses. Receiver operating characteristic curve indicated that TLG has the best differentiation capability to predict responders. By setting the threshold of TLG to 277, the sensitivity, specificity, and accuracy were 66.7%, 83.3%, and 75.0%, respectively, with an area under the curve of 0.776. The median follow-up time was 19.6 (range 7.8-32.0) months. In univariate analyses, baseline TLG >277 (p = 0.005) and baseline Ktrans <254 (10-3 min-1; p = 0.015) correlated with poor survival after CRT. In multivariate analysis, baseline TLG >277 remained the significant factor in predicting progression (p = 0.012) and death (p = 0.031). CONCLUSIONS The radiologic parameters derived from DCE integrated MR-PET scans are useful for predicting treatment response in NSCLC patients treated with CRT; furthermore, these parameters are correlated with clinical and survival outcomes including tumor progression and death.
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Affiliation(s)
- Yu-Sen Huang
- Department of Medical Imaging, National Taiwan University Hospital, National Taiwan University College of Medicine, No.7, Chung-Shan South Road, 100, Taipei, Taiwan
- Institute of Biomedical Engineering, College of Medicine and College of Engineering, National Taiwan University, Taipei, Taiwan
- Department of Medical Imaging, National Taiwan University Hospital Yun-Lin Branch, Yun-Lin, Taiwan
| | - Jenny Ling-Yu Chen
- Institute of Biomedical Engineering, College of Medicine and College of Engineering, National Taiwan University, Taipei, Taiwan
- Department of Oncology, National Taiwan University Hospital, National Taiwan University College of Medicine, Taipei, Taiwan
| | - Jo-Yu Chen
- Department of Medical Imaging, National Taiwan University Hospital, National Taiwan University College of Medicine, No.7, Chung-Shan South Road, 100, Taipei, Taiwan
| | - Yee-Fan Lee
- Department of Medical Imaging, National Taiwan University Hospital, National Taiwan University College of Medicine, No.7, Chung-Shan South Road, 100, Taipei, Taiwan
| | - Jei-Yie Huang
- Department of Nuclear Medicine, National Taiwan University Hospital, National Taiwan University College of Medicine, Taipei, Taiwan
| | - Sung-Hsin Kuo
- Department of Oncology, National Taiwan University Hospital, National Taiwan University College of Medicine, Taipei, Taiwan
| | - Ruoh-Fang Yen
- Department of Nuclear Medicine, National Taiwan University Hospital, National Taiwan University College of Medicine, Taipei, Taiwan
| | - Yeun-Chung Chang
- Department of Medical Imaging, National Taiwan University Hospital, National Taiwan University College of Medicine, No.7, Chung-Shan South Road, 100, Taipei, Taiwan.
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10
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Ohno Y, Fujisawa Y, Yui M, Takenaka D, Koyama H, Sugihara N, Yoshikawa T. Solitary pulmonary nodule: Comparison of quantitative capability for differentiation and management among dynamic CE-perfusion MRI at 3 T system, dynamic CE-perfusion ADCT and FDG-PET/CT. Eur J Radiol 2019; 115:22-30. [PMID: 31084755 DOI: 10.1016/j.ejrad.2019.03.018] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2019] [Revised: 02/20/2019] [Accepted: 03/24/2019] [Indexed: 12/17/2022]
Abstract
PURPOSE To prospectively compare the capability of dynamic first-pass contrast-enhanced (CE) perfusion MR imaging with ultra-short TE and area-detector CT (ADCT), analyzed with the same mathematical methods, and that of FDG-PET/CT for diagnosis and management of solitary pulmonary nodules (SPNs). METHODS AND MATERIALS Our institutional review board approved this study and written informed consent was obtained from all subjects. A total 57 consecutive patients with 71 nodules prospectively underwent dynamic CE-perfusion ADCT and MR imaging with ultra-short TE, FDG-PET/CT, as well as microbacterial and/or pathological examinations. The nodules were classified into malignant nodules (n = 45) and benign nodules (n = 26). Pulmonary arterial, systemic arterial and total perfusions were determined by means of dual-input maximum slope models on ADCT and MR imaging and maximum values of standard uptake values (SUVmax) on PET/CT. Receiver operating characteristic (ROC) analysis was performed for each index, and sensitivity, specificity and accuracy were compared by McNemar's test. RESULTS Areas under the curve (Azs) of total perfusion on ADCT (Az = 0.89) and MR imaging (Az = 0.88) were significantly larger than those of systemic arterial perfusion and MR imaging (p<0.05). Accuracy of total perfusion on ADCT (87.3% [62/71]) and MR imaging (87.3% [62/71]) was significantly higher than that of systemic arterial perfusion for both methods (77.5% [55/71] p = 0.02) and SUVmax (78.9% [56/71], p = 0.03). CONCLUSION Dynamic CE-perfusion MR imaging with ultra-short TE and ADCT and have similar potential capabilities, and are superior to FDG-PET/CT in this setting.
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Affiliation(s)
- Yoshiharu Ohno
- Division of Functional and Diagnostic Imaging Research, Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Japan; Advanced Biomedical Imaging Research Center, Kobe University Graduate School of Medicine, Kobe, Japan; Department of Radiology, Fujita Health University School of Medicine.
| | | | - Masao Yui
- Canon Medical Systems Corporation, Otawara, Japan
| | | | - Hisanobu Koyama
- Department of Radiology, Osaka Police Hospital, Osaka, Japan
| | | | - Takeshi Yoshikawa
- Division of Functional and Diagnostic Imaging Research, Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Japan; Advanced Biomedical Imaging Research Center, Kobe University Graduate School of Medicine, Kobe, Japan
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11
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Seki S, Fujisawa Y, Yui M, Kishida Y, Koyama H, Ohyu S, Sugihara N, Yoshikawa T, Ohno Y. Dynamic Contrast-enhanced Area-detector CT vs Dynamic Contrast-enhanced Perfusion MRI vs FDG-PET/CT: Comparison of Utility for Quantitative Therapeutic Outcome Prediction for NSCLC Patients Undergoing Chemoradiotherapy. Magn Reson Med Sci 2019; 19:29-39. [PMID: 30880291 PMCID: PMC7067914 DOI: 10.2463/mrms.mp.2018-0158] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022] Open
Abstract
PURPOSE To directly compare the utility for therapeutic outcome prediction of dynamic first-pass contrast-enhanced (CE)-perfusion area-detector computed tomography (ADCT), MR imaging assessed with the same mathematical method and 2-[fluorine-18]-fluoro-2-deoxy-d-glucose-positron emission tomography combined with CT (PET/CT) for non-small cell lung cancer (NSCLC) patients treated with chemoradiotherapy. MATERIALS AND METHODS Forty-three consecutive stage IIIB NSCLC patients, consisting of 25 males (mean age ± standard deviation: 66.6 ± 8.7 years) and 18 females (66.4 ± 8.2 years) underwent PET/CT, dynamic CE-perfusion ADCT and MR imaging, chemoradiotherapy, and follow-up examination. In each patient, total, pulmonary arterial, and systemic arterial perfusions were calculated from both perfusion data and SUVmax on PET/CT, assessed for each targeted lesion, and averaged to determine final values. Receiver operating characteristics analyses were performed to compare the utility for distinguishing responders from non-responders using Response Evaluation Criteria in Solid Tumor (RECIST) 1.1 criteria. Overall survival (OS) assessed with each index were compared between two groups by means of the Kaplan-Meier method followed by the log-rank test. RESULTS Area under the curve (Az) for total perfusion on ADCT was significantly larger than that of pulmonary arterial perfusion (P < 0.05). Az of total perfusion on MR imaging was significantly larger than that of pulmonary arterial perfusion (P < 0.05). Mean OS of responder and non-responder groups were significantly different for total and systemic arterial (P < 0.05) perfusion. CONCLUSION Dynamic first-pass CE-perfusion ADCT and MR imaging as well as PET/CT are useful for early prediction of treatment response by NSCLC patients treated with chemoradiotherapy.
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Affiliation(s)
- Shinichiro Seki
- Division of Functional and Diagnostic Imaging Research, Department of Radiology, Kobe University Graduate School of Medicine.,Advanced Biomedical Imaging Research Center, Kobe University Graduate School of Medicine
| | | | | | - Yuji Kishida
- Division of Radiology, Department of Radiology, Kobe University Graduate School of Medicine
| | - Hisanobu Koyama
- Division of Radiology, Department of Radiology, Kobe University Graduate School of Medicine
| | | | | | - Takeshi Yoshikawa
- Division of Functional and Diagnostic Imaging Research, Department of Radiology, Kobe University Graduate School of Medicine.,Advanced Biomedical Imaging Research Center, Kobe University Graduate School of Medicine
| | - Yoshiharu Ohno
- Division of Functional and Diagnostic Imaging Research, Department of Radiology, Kobe University Graduate School of Medicine.,Advanced Biomedical Imaging Research Center, Kobe University Graduate School of Medicine
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12
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Wei H, Yang F, Liu Z, Sun S, Xu F, Liu P, Li H, Liu Q, Qiao X, Wang X. Application of computed tomography-based radiomics signature analysis in the prediction of the response of small cell lung cancer patients to first-line chemotherapy. Exp Ther Med 2019; 17:3621-3629. [PMID: 30988745 PMCID: PMC6447792 DOI: 10.3892/etm.2019.7357] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2018] [Accepted: 01/16/2019] [Indexed: 02/06/2023] Open
Abstract
The aim of the present study was to investigate the utility of a computed tomography (CT)-based radiomics signature for the early prediction of the tumor response of small cell lung cancer (SCLC) patients to chemotherapy. A dataset including 92 patients from a clinical trial was retrospectively assembled. All of the patients received the standard first-line regimen of etoposide and cisplatin. According to the Response Evaluation Criteria in Solid Tumors 1.1, the patients were divided into two groups: Response and no response groups. A total of 21 radiomics features were extracted from CT images prior to and after two cycles of chemotherapy and a radiomics signature was constructed via a binary logistic regression model. The area under the receiver operating characteristics curve (AUC) was determined to evaluate the performance of the radiomics signature to predict the response to chemotherapy. The clinicopathological factors associated with chemotherapy in patients with SCLC were also evaluated, and a predictive model was established using a binary logistic regression analysis. The 21 radiological features were used to establish a radiomics signature that was significantly associated with the efficacy of SCLC chemotherapy (P<0.05). The performance of the radiomics signature to predict the chemotherapy efficacy (AUC=0.797) was better than that of the model using clinicopathological parameters (AUC=0.670). Therefore, the present study demonstrated that radiomics features may be promising prognostic imaging biomarkers to predict the response of SCLC patients to chemotherapy and may thus be utilized to guide appropriate treatment planning.
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Affiliation(s)
- Haifeng Wei
- Diagnostic Room of Computer Tomography, Shandong Medical Imaging Research Institute, Shandong Provincial Key Laboratory of Diagnosis and Treatment of Cardio-Cerebral Vascular Disease, Shandong University, Jinan, Shandong 250021, P.R. China.,Department of Radiology, Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan, Shandong 250012, P.R. China
| | - Fengchang Yang
- Department of Radiology, Shandong Cancer Hospital Affiliated to Shandong University, Jinan, Shandong 250117, P.R. China.,Department of Radiology, Shandong Academy of Medical Sciences, Jinan, Shandong 250117, P.R. China
| | - Zhe Liu
- Department of Pharmacy, Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan, Shandong 250012, P.R. China
| | - Shuna Sun
- Department of Dermatology, Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan, Shandong 250012, P.R. China
| | - Fangwei Xu
- Department of Radiology, Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan, Shandong 250012, P.R. China
| | - Peng Liu
- Department of Radiology, Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan, Shandong 250012, P.R. China
| | - Huifen Li
- Department of Natural Drugs, School of Pharmacy, Shandong University of Traditional Chinese Medicine, Jinan, Shandong 250355, P.R. China
| | - Qiao Liu
- Key Laboratory of Experimental Teratology, Ministry of Education and Department of Molecular Medicine and Genetics, Shandong University School of Medicine, Jinan, Shandong 250012, P.R. China
| | - Xu Qiao
- Department of Biomedical Engineering, Shandong University, Jinan, Shandong 250061, P.R. China
| | - Ximing Wang
- Diagnostic Room of Computer Tomography, Shandong Medical Imaging Research Institute, Shandong Provincial Key Laboratory of Diagnosis and Treatment of Cardio-Cerebral Vascular Disease, Shandong University, Jinan, Shandong 250021, P.R. China
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13
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Ohno Y, Koyama H, Seki S, Kishida Y, Yoshikawa T. Radiation dose reduction techniques for chest CT: Principles and clinical results. Eur J Radiol 2018; 111:93-103. [PMID: 30691672 DOI: 10.1016/j.ejrad.2018.12.017] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2018] [Revised: 12/06/2018] [Accepted: 12/16/2018] [Indexed: 11/19/2022]
Abstract
Computer tomography plays a major role in the evaluation of thoracic diseases, especially since the advent of the multidetector-row CT (MDCT) technology. However, the increase use of this technique has raised some concerns about the resulting radiation dose. In this review, we will present the various methods allowing limiting the radiation dose exposure resulting from chest CT acquisitions, including the options of image filtering and iterative reconstruction (IR) algorithms. The clinical applications of reduced dose protocols will be reviewed, especially for lung nodule detection and diagnosis of pulmonary thromboembolism. The performance of reduced dose protocols for infiltrative lung disease assessment will also be discussed. Lastly, the influence of using IR algorithms on computer-aided detection and volumetry of lung nodules, as well as on quantitative and functional assessment of chest diseases will be presented and discussed.
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Affiliation(s)
- Yoshiharu Ohno
- Division of Functional and Diagnostic Imaging Research, Department of Radiology, Kobe University Graduate School of Medicine, Japan; Advanced Biomedical Imaging Research Center, Kobe University Graduate School of Medicine, Japan.
| | | | - Shinichiro Seki
- Division of Functional and Diagnostic Imaging Research, Department of Radiology, Kobe University Graduate School of Medicine, Japan; Advanced Biomedical Imaging Research Center, Kobe University Graduate School of Medicine, Japan
| | - Yuji Kishida
- Division of Radiology, Department of Radiology, Kobe University Graduate School of Medicine, Japan
| | - Takeshi Yoshikawa
- Division of Functional and Diagnostic Imaging Research, Department of Radiology, Kobe University Graduate School of Medicine, Japan; Advanced Biomedical Imaging Research Center, Kobe University Graduate School of Medicine, Japan
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14
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CT Perfusion in Patients with Lung Cancer: Squamous Cell Carcinoma and Adenocarcinoma Show a Different Blood Flow. BIOMED RESEARCH INTERNATIONAL 2018; 2018:6942131. [PMID: 30255097 PMCID: PMC6140241 DOI: 10.1155/2018/6942131] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/19/2018] [Revised: 07/04/2018] [Accepted: 08/16/2018] [Indexed: 01/27/2023]
Abstract
Objectives To characterize tumour baseline blood flow (BF) in two lung cancer subtypes, adenocarcinoma (AC) and squamous cell carcinoma (SCC), also investigating those “borderline” cases whose perfusion value is closer to the group mean of the other histotype. Materials and Methods 26 patients (age range 36-81 years) with primary Non-Small Cell Lung Cancer (NSCLC), subdivided into 19 AC and 7 SCC, were enrolled in this study and underwent a CT perfusion, at diagnosis. BF values were computed according to the maximum-slope method and unreliable values (e.g., arising from artefacts or vessels) were automatically removed. The one-tail Welch's t-test (p-value <0.05) was employed for statistical assessment. Results At diagnosis, mean BF values (in [mL/min/100g]) of AC group [(83.5 ± 29.4)] are significantly greater than those of SCC subtype [(57.0 ± 27.2)] (p-value = 0.02). However, two central SCCs undergoing artefacts from vena cava and pulmonary artery have an artificially increased mean BF. Conclusions The different hemodynamic behaviour of AC and SCC should be considered as a biomarker supporting treatment planning to select the patients, mainly with AC, that would most benefit from antiangiogenic therapies. The significance of results was achieved by automatically detecting and excluding artefactual BF values.
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SEOM-SERAM-SEMNIM guidelines on the use of functional and molecular imaging techniques in advanced non-small-cell lung cancer. RADIOLOGIA 2018; 60:332-346. [PMID: 29807678 DOI: 10.1016/j.rx.2018.01.007] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2018] [Accepted: 01/18/2018] [Indexed: 12/11/2022]
Abstract
Imaging in oncology is an essential tool for patient management but its potential is being profoundly underutilized. Each of the techniques used in the diagnostic process also conveys functional information that can be relevant in treatment decision making. New imaging algorithms and techniques enhance our knowledge about the phenotype of the tumor and its potential response to different therapies. Functional imaging can be defined as the one that provides information beyond the purely morphological data, and include all the techniques that make it possible to measure specific physiological functions of the tumor, whereas molecular imaging would include techniques that allow us to measure metabolic changes. Functional and molecular techniques included in this document are based on multi-detector computed tomography (CT), 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET), magnetic resonance imaging (MRI), and hybrid equipments, integrating PET with CT (PET/CT) or MRI (PET-MRI). Lung cancer is one of the most frequent and deadly tumors although survival is increasing thanks to advances in diagnostic methods and new treatments. This increased survival poises challenges in terms of proper follow-up and definitions of response and progression, as exemplified by immune therapy-related pseudoprogression. In this consensus document, the use of functional and molecular imaging techniques will be addressed to exploit their current potential and explore future applications in the diagnosis, evaluation of response and detection of recurrence of advanced NSCLC.
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SEOM-SERAM-SEMNIM guidelines on the use of functional and molecular imaging techniques in advanced non-small-cell lung cancer. Clin Transl Oncol 2017; 20:837-852. [PMID: 29256154 PMCID: PMC5996017 DOI: 10.1007/s12094-017-1795-y] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2017] [Accepted: 11/04/2017] [Indexed: 12/17/2022]
Abstract
Imaging in oncology is an essential tool for patient management but its potential is being profoundly underutilized. Each of the techniques used in the diagnostic process also conveys functional information that can be relevant in treatment decision-making. New imaging algorithms and techniques enhance our knowledge about the phenotype of the tumor and its potential response to different therapies. Functional imaging can be defined as the one that provides information beyond the purely morphological data, and include all the techniques that make it possible to measure specific physiological functions of the tumor, whereas molecular imaging would include techniques that allow us to measure metabolic changes. Functional and molecular techniques included in this document are based on multi-detector computed tomography (CT), 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET), magnetic resonance imaging (MRI), and hybrid equipments, integrating PET with CT (PET/CT) or MRI (PET-MRI). Lung cancer is one of the most frequent and deadly tumors although survival is increasing thanks to advances in diagnostic methods and new treatments. This increased survival poises challenges in terms of proper follow-up and definitions of response and progression, as exemplified by immune therapy-related pseudoprogression. In this consensus document, the use of functional and molecular imaging techniques will be addressed to exploit their current potential and explore future applications in the diagnosis, evaluation of response and detection of recurrence of advanced NSCLC.
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