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Wang N, Dai M, Jing F, Liu Y, Zhao Y, Zhang Z, Wang J, Zhang J, Wang Y, Zhao X. Value of 18F-FDG PET/CT-based radiomics features for differentiating primary lung cancer and solitary lung metastasis in patients with colorectal adenocarcinoma. Int J Radiat Biol 2024:1-9. [PMID: 39288285 DOI: 10.1080/09553002.2024.2404465] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2024] [Revised: 08/20/2024] [Accepted: 09/03/2024] [Indexed: 09/19/2024]
Abstract
OBJECTIVE To investigate the value and applicability of 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) radiomics in differentiating primary lung cancer (PLC) from solitary lung metastasis (SLM) in patients with colorectal cancer (CRC). MATERIALS AND METHODS This retrospective study included 103 patients with CRC and solitary pulmonary nodules (SPNs). The least absolute shrinkage and selection operator (LASSO) was used to screen for optimal radiomics features and establish a PET/CT radiomics model. PET/CT Visual and complex models (combining radiomics with PET/CT visual features) were developed. The area under the receiver operating characteristic (ROC) curve (AUC) was used to determine the predictive value and diagnostic efficiency of the models. RESULTS The AUC of the PET/CT radiomics model for differentiating PLC from SLM was 0.872 (95% CI: 0.806-0.939), which was not different from that of the visual (0.829 [95% CI: 0.749-0.908; p = .352]). However, the AUC of the complex model (0.936 [95% CI:0.892-0.981]) was significantly higher than that of the PET/CT radiomics (p = .005) and visual model (p = .001). The sensitivity (SEN), specificity (SPE), accuracy (ACC), positive predictive value (PPV), and negative predictive value (NPV) of PET/CT radiomics for differentiating PLC from SLM were 0.720, 0.887, 0.806, 0.857, and 0.770, respectively. CONCLUSION PET/CT radiomics can effectively distinguish PLC and SLM in patients with CRC and SPNs and guide the implementation of personalized treatment.
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Affiliation(s)
- Na Wang
- Department of Nuclear Medicine, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei, China
- Hebei Provincial Key Laboratory of Tumor Microenvironment and Drug Resistance, Shijiazhuang, Hebei, China
| | - Meng Dai
- Department of Nuclear Medicine, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei, China
- Hebei Provincial Key Laboratory of Tumor Microenvironment and Drug Resistance, Shijiazhuang, Hebei, China
| | - Fenglian Jing
- Department of Nuclear Medicine, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei, China
| | - Yunuan Liu
- Department of Nuclear Medicine, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei, China
| | - Yan Zhao
- Department of Oncology, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei, China
| | - Zhaoqi Zhang
- Department of Nuclear Medicine, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei, China
- Hebei Provincial Key Laboratory of Tumor Microenvironment and Drug Resistance, Shijiazhuang, Hebei, China
| | - Jianfang Wang
- Department of Nuclear Medicine, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei, China
- Hebei Provincial Key Laboratory of Tumor Microenvironment and Drug Resistance, Shijiazhuang, Hebei, China
| | - Jingmian Zhang
- Department of Nuclear Medicine, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei, China
- Hebei Provincial Key Laboratory of Tumor Microenvironment and Drug Resistance, Shijiazhuang, Hebei, China
| | - Yingchen Wang
- Department of Nuclear Medicine, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei, China
| | - Xinming Zhao
- Department of Nuclear Medicine, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei, China
- Hebei Provincial Key Laboratory of Tumor Microenvironment and Drug Resistance, Shijiazhuang, Hebei, China
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Lahaye MJ, Lambregts DMJ, Aalbers AGJ, Snaebjornsson P, Beets-Tan RGH, Kok NFM. Imaging in the era of risk-adapted treatment in colon cancer. Br J Radiol 2024; 97:1214-1221. [PMID: 38648743 PMCID: PMC11186558 DOI: 10.1093/bjr/tqae061] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2022] [Revised: 02/14/2024] [Accepted: 03/14/2024] [Indexed: 04/25/2024] Open
Abstract
The treatment landscape for patients with colon cancer is continuously evolving. Risk-adapted treatment strategies, including neoadjuvant chemotherapy and immunotherapy, are slowly finding their way into clinical practice and guidelines. Radiologists are pivotal in guiding clinicians toward the most optimal treatment for each colon cancer patient. This review provides an overview of recent and upcoming advances in the diagnostic management of colon cancer and the radiologist's role in the multidisciplinary approach to treating colon cancer.
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Affiliation(s)
- Max J Lahaye
- Department of Radiology, The Netherlands Cancer Institute, 1066 CX Amsterdam, The Netherlands
- GROW School for Oncology and Reproduction, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Doenja M J Lambregts
- Department of Radiology, The Netherlands Cancer Institute, 1066 CX Amsterdam, The Netherlands
- GROW School for Oncology and Reproduction, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Arend G J Aalbers
- Department of Surgery, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Petur Snaebjornsson
- Department of Pathology, The Netherlands Cancer Institute, Amsterdam, The Netherlands
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Regina G H Beets-Tan
- Department of Radiology, The Netherlands Cancer Institute, 1066 CX Amsterdam, The Netherlands
- GROW School for Oncology and Reproduction, Maastricht University Medical Centre, Maastricht, The Netherlands
- Faculty of Health Sciences, University of Southern Denmark, Odense, Denmark
| | - Niels F M Kok
- Department of Surgery, The Netherlands Cancer Institute, Amsterdam, The Netherlands
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Nuijens BW, Lindeboom R, van den Broek JJ, Geenen RWF, Schreurs WH. A prediction model for lung metastases in patients with indeterminate pulmonary nodules in newly diagnosed colorectal cancer. EUROPEAN JOURNAL OF SURGICAL ONCOLOGY 2024; 50:108305. [PMID: 38552417 DOI: 10.1016/j.ejso.2024.108305] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2023] [Revised: 03/13/2024] [Accepted: 03/23/2024] [Indexed: 05/26/2024]
Abstract
INTRODUCTION Multidisciplinary teams treating patients with newly diagnosed Colorectal Cancer (CRC) often encounter the appearance of Indeterminate Pulmonary Nodules (IPNs) that warrants follow-up with repetitive medical imaging and anxiety for patients. We determined the incidence of IPNs in patients with newly diagnosed CRC and developed and validated a model for individualized risk prediction of IPNs being lung metastases. MATERIAL AND METHODS Newly diagnosed CRC who underwent surgery between November 2011 to June 2014 were included to create the risk model, developed using both clinical experience and statistical selection. Discrimination and calibration slopes of the risk score were evaluated in an independent temporal validation sample. A nomogram is presented to assist clinicians in estimating an individual risk score. RESULTS Out of 2111 CRC patients staged with chest CT, 204 (9.6%) had IPNs and 54/204 (26%) had lung metastases. We identified 4 predictors: "location of primary tumour", "pathological nodal stage", "size of the largest nodule" and "extrapulmonary synchronous metastases at diagnosis". Discrimination of the final model in the validation sample was demonstrated by the difference in mean predicted risk between progressed cases en non-progressed cases (49% versus 21%, p = <0.001). CONCLUSION A prediction model with 4 clinical risk factors can be used to assist multidisciplinary teams in the prediction of individualized risk of lung metastases and imaging strategy in patients with IPNs and newly diagnosed colorectal cancer. The model performed well in new patients not included in the model development.
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Affiliation(s)
| | - Robert Lindeboom
- Department of Epidemiology and Data Science, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | | | - Remy W F Geenen
- Department of Radiology, Northwest Clinics, Alkmaar, the Netherlands
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Kim S, Huh JW, Lee WY, Yun SH, Kim HC, Cho YB, Park Y, Shin JK. Pulmonary Metastasis as the First Site of Metastasis After Curative Surgery for Colon Cancer: Incidence and Risk Factors According to the TNM Stage. Dis Colon Rectum 2024; 67:523-530. [PMID: 38147433 DOI: 10.1097/dcr.0000000000003036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/28/2023]
Abstract
BACKGROUND The lungs are one of the most common sites for colon cancer metastasis. A few studies reported that approximately 2% to 10% of patients with colon cancer developed pulmonary metastasis. However, among these studies, patient characteristics were heterogeneous, and information on pulmonary metastasis incidence by the TNM stage was scarce. OBJECTIVE This study evaluated the incidence of pulmonary metastasis in colon cancer without synchronous metastasis treated with radical surgery and identified risk factors for pulmonary metastasis according to the TNM stage. DESIGN AND SETTINGS This retrospective study included all patients with colon cancer without metastasis who underwent radical surgery for primary tumor at Samsung Medical Center between January 2007 and December 2016. PATIENTS A total of 4889 patients who underwent radical surgery for stage I and III colon cancer were included. MAIN OUTCOME MEASURES The main outcome measures were the incidence of pulmonary metastasis and overall survival. RESULTS A total of 156 patients (3.2%) were diagnosed with pulmonary metastasis after a median of 16 months from the time of radical surgery for colon cancer to detection of pulmonary metastasis. The pulmonary metastasis incidence rate by the TNM stage was 0.5% in stage I, 1.6% in stage II, and 6% in stage III. Risk factors for pulmonary metastasis were preoperative CEA >5 ng/mL, cancer obstruction, N stage, vascular invasion, perineural invasion, and adjuvant chemotherapy for primary colon cancer in multivariable analysis. LIMITATION This was a retrospective single-center study. CONCLUSIONS Preoperative CEA >5 ng/mL, cancer obstruction, pN stage, vascular invasion, perineural invasion, and receiving adjuvant chemotherapy for primary colon cancer were risk factors for pulmonary metastasis in colon cancer. Therefore, patients with risk factors for pulmonary metastasis should be recommended for intensive follow-up to detect lung metastases. See Video Abstract . METSTASIS PULMONAR EN EL PRIMER SITIO TRAS CIRUGA CURATIVA DEL CNCER DE COLON INCIDENCIA Y FACTORES DE RIESGO SEGN ESTADIO TNM ANTECEDENTES:Los pulmones son uno de los sitios más comunes de metástasis del cáncer de colon. Algunos estudios informaron que aproximadamente entre el 2% y el 10% de los pacientes con cáncer de colon desarrollaron metástasis pulmonar. Sin embargo, entre estos estudios, las características de los pacientes fueron heterogéneas y la información sobre la incidencia de metástasis pulmonares según el estadio TNM fue escasa.OBJETIVO:Este estudio evaluó la incidencia de metástasis pulmonar en cáncer de colon sin metástasis sincrónica tratada con cirugía radical e identificó factores de riesgo para metástasis pulmonar según el estadio TNM.DISEÑO Y AJUSTES:Este estudio retrospectivo incluyó a todos los pacientes con cáncer de colon sin metástasis que se sometieron a cirugía radical por tumor primario en el Samsung Medical Center entre enero de 2007 y diciembre de 2016.PACIENTES:Se incluyó un total de 4.889 pacientes sometidos a cirugía radical por cáncer de colon en estadio I-III.PRINCIPALES MEDIDAS DE RESULTADO:Las principales medidas de resultado fueron la incidencia de metástasis pulmonar y la supervivencia general.RESULTADOS:Un total de 156 pacientes (3,2%) fueron diagnosticados con metástasis pulmonar con una duración media de 16 meses desde el momento de la cirugía radical por cáncer de colon hasta la detección de la metástasis pulmonar. La tasa de incidencia de metástasis pulmonares por estadio TNM fue del 0,5% en el estadio I, del 1,6% en el estadio II y del 6% en el estadio III. Los factores de riesgo de metástasis pulmonar fueron CEA preoperatorio superior a 5 ng/ml, obstrucción por cáncer, estadio N, invasión vascular, invasión perineural y quimioterapia adyuvante para el cáncer de colon primario en un análisis multivariable.LIMITACIÓN:Este fue un estudio retrospectivo de un solo centro.CONCLUSIÓN:CEA preoperatorio superior a 5 ng/ml, obstrucción por cáncer, estadio pN, invasión vascular, invasión perineural y recibir quimioterapia adyuvante para el cáncer de colon primario fueron factores de riesgo de metástasis pulmonar en el cáncer de colon. Por lo tanto, se debe recomendar un seguimiento intensivo a los pacientes con factores de riesgo de metástasis pulmonares para detectar metástasis pulmonares. (Traducción-Dr Yolanda Colorado ).
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Affiliation(s)
- Seijong Kim
- Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
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Chen M, Wang H, Huang Y, Guo F, Zheng W, Chen C, Zheng B. Prediction of pulmonary metastasis in esophageal carcinoma patients with indeterminate pulmonary nodules. World J Surg Oncol 2023; 21:315. [PMID: 37814273 PMCID: PMC10561496 DOI: 10.1186/s12957-023-03211-6] [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: 07/02/2023] [Accepted: 10/03/2023] [Indexed: 10/11/2023] Open
Abstract
BACKGROUND Indeterminate pulmonary nodules (IPNs) are common after surgery for esophageal cancer. The paucity of data on postoperative IPNs for esophageal cancer causes a clinical dilemma. OBJECTIVE The aim of this study was to identify the characteristics and clinical significance of IPNs after radical esophagectomy for metastatic esophageal cancer, determine the risk factors for pulmonary metastasis, and construct a risk score model to standardize the appropriate time to either follow up or treat the patient. METHODS All consecutive patients with esophageal squamous cell carcinoma (ESCC) who underwent radical surgery between 2013 and 2016 were included in this retrospective study. Univariate and multivariate logistic regression analyses were performed to identify independent risk factors and develop risk score models. RESULTS A total of 816 patients were enrolled in the study. During a median follow-up period of 45 months, IPNs were detected in 221 (27.1%) patients, of whom 66 (29.9%) were diagnosed with pulmonary metastases. The following five variables maintained prognostic significance after multivariate analyses: the pathologic N category, number of IPNs, shape of IPNs, time of detection of IPNs, and size of IPNs. The Pulmonary Metastasis Prediction Model (PMPM) scale ranges from 0 to 15 points, and patients with higher scores have a higher probability of pulmonary metastases. The Hosmer-Lemeshow test showed a good calibration performance of the clinical prediction model (χ2 = 8.573, P = 0.380). After validation, the PMPM scale showed good discrimination with an AUC of 0.939. CONCLUSION A PMPM scale for IPNs in patients who underwent esophagectomy for ESCC may be clinically useful for diagnostic and therapeutic decision-making.
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Affiliation(s)
- Maohui Chen
- Department of Thoracic Surgery, Fujian Medical University Union Hospital, Fuzhou, China
- Key Laboratory of Cardio-Thoracic Surgery (Fujian Medical University), Fujian Province University, Fujian, China
- National Key Clinical Specialty of Thoracic Surgery, Fuzhou, China
| | - Hongjin Wang
- Key Laboratory of Cardio-Thoracic Surgery (Fujian Medical University), Fujian Province University, Fujian, China
- National Key Clinical Specialty of Thoracic Surgery, Fuzhou, China
- Department of Cardiovascular Surgery, Longyan First Affiliated Hospital of Fujian Medical University, Longyan, China
| | - Yizhou Huang
- Department of Thoracic Surgery, Fujian Medical University Union Hospital, Fuzhou, China
- Key Laboratory of Cardio-Thoracic Surgery (Fujian Medical University), Fujian Province University, Fujian, China
- National Key Clinical Specialty of Thoracic Surgery, Fuzhou, China
| | - Feilong Guo
- Department of Thoracic Surgery, Fujian Medical University Union Hospital, Fuzhou, China
- Key Laboratory of Cardio-Thoracic Surgery (Fujian Medical University), Fujian Province University, Fujian, China
- National Key Clinical Specialty of Thoracic Surgery, Fuzhou, China
| | - Wei Zheng
- Department of Thoracic Surgery, Fujian Medical University Union Hospital, Fuzhou, China
- Key Laboratory of Cardio-Thoracic Surgery (Fujian Medical University), Fujian Province University, Fujian, China
- National Key Clinical Specialty of Thoracic Surgery, Fuzhou, China
| | - Chun Chen
- Department of Thoracic Surgery, Fujian Medical University Union Hospital, Fuzhou, China.
- Key Laboratory of Cardio-Thoracic Surgery (Fujian Medical University), Fujian Province University, Fujian, China.
- National Key Clinical Specialty of Thoracic Surgery, Fuzhou, China.
| | - Bin Zheng
- Department of Thoracic Surgery, Fujian Medical University Union Hospital, Fuzhou, China.
- Key Laboratory of Cardio-Thoracic Surgery (Fujian Medical University), Fujian Province University, Fujian, China.
- National Key Clinical Specialty of Thoracic Surgery, Fuzhou, China.
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Lee S, Lee KH, Park JH, Kim HY, Choi Y, Lee KH. Staging Chest CT in Patients With Early-Stage Colon Cancer: Analysis of Impact on Survival Using Inverse Probability Weighting and Causal Diagram. AJR Am J Roentgenol 2023; 221:184-195. [PMID: 37095662 DOI: 10.2214/ajr.22.28905] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/24/2023]
Abstract
BACKGROUND. Staging chest CT has been shown to have negligible diagnostic yield for detecting lung metastases in patients with early-stage colon cancer. Nonetheless, staging chest CT may have potential survival benefits, including opportunistic screening of comorbidity and provision of a baseline examination for future comparisons. Evidence is lacking regarding the impact of staging chest CT on survival in patients with early-stage colon cancer. OBJECTIVE. The purpose of this study was to determine whether the performance of staging chest CT affects survival in patients with early-stage colon cancer. METHODS. This retrospective study included patients with early-stage colon cancer (defined as clinical stage 0 or I on staging abdominal CT) at a single tertiary hospital between January 2009 and December 2015. Patients were divided into two groups according to the presence of a staging chest CT examination. To ensure comparability between the two groups, inverse probability weighting was applied to adjust for the confounders derived from a causal diagram. The between-group differences in adjusted restricted mean survival time at 5 years were measured for overall survival, relapse-free survival, and thoracic metastasis-free survival. Sensitivity analyses were performed. RESULTS. A total of 991 patients (618 men and 373 women; median age, 64 years [IQR, 55-71 years]) were included: 606 patients (61.2%) had staging chest CT. For overall survival, the difference between groups in restricted mean survival time at 5 years was not significant (0.4 months [95% CI, -0.8 to 2.1 months]). The differences between groups in restricted mean survival at 5 years were also not significant for relapse-free survival (0.4 months [95% CI, -1.1 to 2.3 months]) and for thoracic metastasis-free survival (0.6 months [95% CI, -0.8 to 2.4 months]). Similar results were observed in sensitivity analyses that tested 3- and 10-year RMST differences, excluded patients who underwent FDG PET/CT during staging workup, and added treatment decision (surgery vs no surgery) to the causal diagram. CONCLUSION. The use of staging chest CT did not affect survival in patients with early-stage colon cancer. CLINICAL IMPACT. Staging chest CT may be omitted from the staging workup for patients with colon cancer of clinical stage 0 or I.
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Affiliation(s)
- Seungjae Lee
- Department of Applied Bioengineering, Graduate School of Convergence Science and Technology, Seoul National University, Seoul, Korea
| | - Kyung Hee Lee
- Department of Radiology, Seoul National University College of Medicine, Seoul, Korea
- Department of Medical Device Development, Seoul National University College of Medicine, Seoul, Korea
| | - Ji Hoon Park
- Department of Applied Bioengineering, Graduate School of Convergence Science and Technology, Seoul National University, Seoul, Korea
- Department of Radiology, Seoul National University College of Medicine, Seoul, Korea
- Department of Medical Device Development, Seoul National University College of Medicine, Seoul, Korea
- Department of Radiology, Seoul National University Bundang Hospital, 82, Gumi-ro 173 Beon-gil, Bundang-gu, Seongnam-si, Gyeonggi-do, 13620, Korea
| | - Hae Young Kim
- Department of Medical Device Development, Seoul National University College of Medicine, Seoul, Korea
| | - Yonghoon Choi
- Department of Internal Medicine, Seoul National University Bundang Hospital, Gyeonggi-do, Korea
| | - Kyoung Ho Lee
- Department of Applied Bioengineering, Graduate School of Convergence Science and Technology, Seoul National University, Seoul, Korea
- Department of Radiology, Seoul National University College of Medicine, Seoul, Korea
- Department of Medical Device Development, Seoul National University College of Medicine, Seoul, Korea
- Department of Radiology, Seoul National University Bundang Hospital, 82, Gumi-ro 173 Beon-gil, Bundang-gu, Seongnam-si, Gyeonggi-do, 13620, Korea
- Interdisciplinary Program in Bioengineering, Seoul National University, Seoul, Korea
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Carconi C, Cerreti M, Roberto M, Arrivi G, D'Ambrosio G, De Felice F, Di Civita MA, Iafrate F, Lucatelli P, Magliocca FM, Picchetto A, Picone V, Catalano C, Cortesi E, Tombolini V, Mazzuca F, Tomao S. The Management of Oligometastatic Disease in Colorectal Cancer: Present Strategies and Future Perspectives. Crit Rev Oncol Hematol 2023; 186:103990. [PMID: 37061075 DOI: 10.1016/j.critrevonc.2023.103990] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2022] [Revised: 03/29/2023] [Accepted: 04/11/2023] [Indexed: 04/17/2023] Open
Abstract
Oligometastatic disease has been described as an intermediate clinical state between localized cancer and systemically metastasized disease. Recent clinical studies have shown prolonged survival when aggressive locoregional approaches are added to systemic therapies in patients with oligometastases. The aim of this review is to outline the newest options to treat oligometastatic colorectal cancer (CRC), also considering its molecular patterns. We present an overview of the available local treatment strategies, including surgical procedures, stereotactic body radiation therapy (SBRT), thermal ablation, as well as trans-arterial chemoembolization (TACE) and selective internal radiotherapy (SIRT). Moreover, since imaging methods provide crucial information for the early diagnosis and management of oligometastatic CRC, we discuss the role of modern radiologic techniques in selecting patients that are amenable to potentially curative locoregional treatments.
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Affiliation(s)
- Catia Carconi
- Sant'Andrea University Hospital, Faculty of Medicine and Psychology, "Sapienza" University of Rome, Rome, Italy
| | - Micaela Cerreti
- Sant'Andrea University Hospital, Faculty of Medicine and Psychology, "Sapienza" University of Rome, Rome, Italy
| | - Michela Roberto
- UOC Oncologia A, Department of radiological, Oncological and Anathomo-patological Science, Policlinico Umberto I, "Sapienza" University of Rome, 00161 Rome, Italy.
| | - Giulia Arrivi
- Oncology Unit, Sant' Andrea University Hospital, Department of Clinical and Molecular Medicine, Sapienza University of Rome, Rome, Italy
| | - Giancarlo D'Ambrosio
- Department of General Surgery, Surgical Specialties and Organ Transplantation, Policlinico Umberto I, "Sapienza" University of Rome, 00161 Rome, Italy
| | - Francesca De Felice
- Department of Radiotherapy, Policlinico Umberto I "Sapienza" University of Rome, Rome, Italy
| | - Mattia Alberto Di Civita
- UOC Oncologia A, Department of radiological, Oncological and Anathomo-patological Science, Policlinico Umberto I, "Sapienza" University of Rome, 00161 Rome, Italy
| | - Franco Iafrate
- Department of Radiological Sciences, Oncology and Pathology, Policlinico Umberto I, "Sapienza" University of Rome, Rome, Italy
| | - Pierleone Lucatelli
- Vascular and Interventional radiology Unit, Department of radiological, Oncological and Anathomo-patological Science, Policlinico Umberto I, "Sapienza" University of Rome, Rome, Italy
| | - Fabio Massimo Magliocca
- Vascular and Interventional radiology Unit, Department of radiological, Oncological and Anathomo-patological Science, Policlinico Umberto I, "Sapienza" University of Rome, Rome, Italy
| | - Andrea Picchetto
- Emergency Department, Policlinico Umberto I, "Sapienza" University of Rome, Rome, Italy
| | - Vincenzo Picone
- UOC Oncologia B, Department of radiological, Oncological and Anathomo-patological Science, Policlinico Umberto I, "Sapienza" University of Rome, Rome, Italy
| | - Carlo Catalano
- Vascular and Interventional radiology Unit, Department of radiological, Oncological and Anathomo-patological Science, Policlinico Umberto I, "Sapienza" University of Rome, Rome, Italy
| | - Enrico Cortesi
- UOC Oncologia B, Department of radiological, Oncological and Anathomo-patological Science, Policlinico Umberto I, "Sapienza" University of Rome, Rome, Italy
| | - Vincenzo Tombolini
- Department of Radiotherapy, Policlinico Umberto I "Sapienza" University of Rome, Rome, Italy
| | - Federica Mazzuca
- Oncology Unit, Sant' Andrea University Hospital, Department of Clinical and Molecular Medicine, Sapienza University of Rome, Rome, Italy
| | - Silverio Tomao
- Oncology Unit, Sant' Andrea University Hospital, Department of Clinical and Molecular Medicine, Sapienza University of Rome, Rome, Italy
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Lee JE, Do LN, Jeong WG, Lee HJ, Chae KJ, Kim YH, Park I. A Radiomics Approach on Chest CT Distinguishes Primary Lung Cancer from Solitary Lung Metastasis in Colorectal Cancer Patients. J Pers Med 2022; 12:jpm12111859. [PMID: 36579596 PMCID: PMC9695650 DOI: 10.3390/jpm12111859] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2022] [Revised: 10/31/2022] [Accepted: 11/01/2022] [Indexed: 11/09/2022] Open
Abstract
PURPOSE This study utilized a radiomics approach combined with a machine learning algorithm to distinguish primary lung cancer (LC) from solitary lung metastasis (LM) in colorectal cancer (CRC) patients with a solitary pulmonary nodule (SPN). MATERIALS AND METHODS In a retrospective study, 239 patients who underwent chest computerized tomography (CT) at three different institutions between 2011 and 2019 and were diagnosed as primary LC or solitary LM were included. The data from the first institution were divided into training and internal testing datasets. The data from the second and third institutions were used as an external testing dataset. Radiomic features were extracted from the intra and perinodular regions of interest (ROI). After a feature selection process, Support vector machine (SVM) was used to train models for classifying between LC and LM. The performances of the SVM classifiers were evaluated with both the internal and external testing datasets. The performances of the model were compared to those of two radiologists who reviewed the CT images of the testing datasets for the binary prediction of LC versus LM. RESULTS The SVM classifier trained with the radiomic features from the intranodular ROI and achieved the sensitivity/specificity of 0.545/0.828 in the internal test dataset, and 0.833/0.964 in the external test dataset, respectively. The SVM classifier trained with the combined radiomic features from the intra- and perinodular ROIs achieved the sensitivity/specificity of 0.545/0.966 in the internal test dataset, and 0.833/1.000 in the external test data set, respectively. Two radiologists demonstrated the sensitivity/specificity of 0.545/0.966 and 0.636/0.828 in the internal test dataset, and 0.917/0.929 and 0.833/0.929 in the external test dataset, which were comparable to the performance of the model trained with the combined radiomics features. CONCLUSION Our results suggested that the machine learning classifiers trained using radiomics features of SPN in CRC patients can be used to distinguish the primary LC and the solitary LM with a similar level of performance to radiologists.
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Affiliation(s)
- Jong Eun Lee
- Department of Radiology, Chonnam National University Hospital, Chonnam National University Medical School, Gwangju, Korea
| | - Luu Ngoc Do
- Department of Radiology, Chonnam National University, Gwangju, Korea
| | - Won Gi Jeong
- Department of Radiology, Chonnam National University Hwasun Hospital, Chonnam National University Medical School, Hwasun, Korea
| | - Hyo Jae Lee
- Department of Radiology, Chonnam National University Hwasun Hospital, Chonnam National University Medical School, Hwasun, Korea
| | - Kum Ju Chae
- Department of Radiology, Research Institute of Clinical Medicine of Jeonbuk National University-Biomedical Research Institute of Jeonbuk National University Hospital, Jeonju, Korea
| | - Yun Hyeon Kim
- Department of Radiology, Chonnam National University Hospital, Chonnam National University Medical School, Gwangju, Korea
| | - Ilwoo Park
- Department of Radiology, Chonnam National University Hospital, Chonnam National University Medical School, Gwangju, Korea
- Department of Radiology, Chonnam National University, Gwangju, Korea
- Department of Artificial Intelligence Convergence, Chonnam National University, Gwangju, Korea
- Department of Data Science, Chonnam National University, Gwangju, Korea
- Correspondence: ; Tel.: +82-62-220-5744; Fax: +82-62-226-4380
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9
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Guo R, Yan S, Wang F, Su H, Xie Q, Zhao W, Yang Z, Li N, Yu J. A novel diagnostic model for differentiation of lung metastasis from primary lung cancer in patients with colorectal cancer. Front Oncol 2022; 12:1017618. [PMID: 36353559 PMCID: PMC9639374 DOI: 10.3389/fonc.2022.1017618] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Accepted: 10/06/2022] [Indexed: 11/25/2022] Open
Abstract
Objective This study aimed to evaluate the 18F-FDG PET/CT in differentiating lung metastasis(LM) from primary lung cancer(LC) in patients with colorectal cancer (CRC). Methods A total of 120 CRC patients (80 male, 40 female) who underwent 18F-FDG PET/CT were included. The diagnosis of primary lung cancer or lung metastasis was based on histopathology The patients were divided into a training cohort and a validation cohort randomized 1:1. Independent risk factors were extracted through the clinical information and 18F-FDG PET/CT imaging characteristics of patients in the validation cohort, and then a diagnostic model was constructed and a nomograms was made. ROC curve, calibration curve, cutoff, sensitivity, specificity, and accuracy were used to evaluate the prediction performance of the diagnostic model. Results One hundred and twenty Indeterminate lung lesions (ILLs) (77 lung metastasis, 43 primary lung cancer) were analyzed. No significant difference in clinical characteristics and imaging features between the training and the validation cohorts (P > 0. 05). Using uni-/multivariate analysis, pleural tags and contour were identified as independent predictors. These independent predictors were used to establish a diagnostic model with areas under the receiver operating characteristic curves (AUCs) of 0.92 and 0.89 in the primary and validation cohorts, respectively. The accuracy rate of the diagnostic model for differentiating LM from LC were higher than that of subjective diagnosis (P < 0.05). Conclusions Pleural tags and contour were identified as independent predictors. The diagnostic model of ILLs in patients with CRC could help differentiate between LM and LC.
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Affiliation(s)
- Rui Guo
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education, Beijing), National Medical Products Administration (NPMA) Key Laboratory for Research and Evaluation of Radiopharmaceuticals (National Medical Products Administration), Department of Nuclear Medicine, Peking University Cancer Hospital & Institute, Beijing, China
| | - Shi Yan
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Thoracic Surgery II, Peking University Cancer Hospital and Institute, Beijing, China
| | - Fei Wang
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education, Beijing), National Medical Products Administration (NPMA) Key Laboratory for Research and Evaluation of Radiopharmaceuticals (National Medical Products Administration), Department of Nuclear Medicine, Peking University Cancer Hospital & Institute, Beijing, China
| | - Hua Su
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education, Beijing), National Medical Products Administration (NPMA) Key Laboratory for Research and Evaluation of Radiopharmaceuticals (National Medical Products Administration), Department of Nuclear Medicine, Peking University Cancer Hospital & Institute, Beijing, China
| | - Qing Xie
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education, Beijing), National Medical Products Administration (NPMA) Key Laboratory for Research and Evaluation of Radiopharmaceuticals (National Medical Products Administration), Department of Nuclear Medicine, Peking University Cancer Hospital & Institute, Beijing, China
| | - Wei Zhao
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education, Beijing), National Medical Products Administration (NPMA) Key Laboratory for Research and Evaluation of Radiopharmaceuticals (National Medical Products Administration), Department of Nuclear Medicine, Peking University Cancer Hospital & Institute, Beijing, China
| | - Zhi Yang
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education, Beijing), National Medical Products Administration (NPMA) Key Laboratory for Research and Evaluation of Radiopharmaceuticals (National Medical Products Administration), Department of Nuclear Medicine, Peking University Cancer Hospital & Institute, Beijing, China
- *Correspondence: Zhi Yang, ; Nan Li, ; Jiangyuan Yu,
| | - Nan Li
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education, Beijing), National Medical Products Administration (NPMA) Key Laboratory for Research and Evaluation of Radiopharmaceuticals (National Medical Products Administration), Department of Nuclear Medicine, Peking University Cancer Hospital & Institute, Beijing, China
- *Correspondence: Zhi Yang, ; Nan Li, ; Jiangyuan Yu,
| | - Jiangyuan Yu
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education, Beijing), National Medical Products Administration (NPMA) Key Laboratory for Research and Evaluation of Radiopharmaceuticals (National Medical Products Administration), Department of Nuclear Medicine, Peking University Cancer Hospital & Institute, Beijing, China
- *Correspondence: Zhi Yang, ; Nan Li, ; Jiangyuan Yu,
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10
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Liu C, Meng Q, Zeng Q, Chen H, Shen Y, Li B, Cen R, Huang J, Li G, Liao Y, Wu T. An Exploratory Study on the Stable Radiomics Features of Metastatic Small Pulmonary Nodules in Colorectal Cancer Patients. Front Oncol 2021; 11:661763. [PMID: 34336657 PMCID: PMC8322948 DOI: 10.3389/fonc.2021.661763] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2021] [Accepted: 06/17/2021] [Indexed: 12/24/2022] Open
Abstract
Objectives To identify the relatively invariable radiomics features as essential characteristics during the growth process of metastatic pulmonary nodules with a diameter of 1 cm or smaller from colorectal cancer (CRC). Methods Three hundred and twenty lung nodules were enrolled in this study (200 CRC metastatic nodules in the training cohort, 60 benign nodules in the verification cohort 1, 60 CRC metastatic nodules in the verification cohort 2). All the nodules were divided into four groups according to the maximum diameter: 0 to 0.25 cm, 0.26 to 0.50 cm, 0.51 to 0.75 cm, 0.76 to 1.0 cm. These pulmonary nodules were manually outlined in computed tomography (CT) images with ITK-SNAP software, and 1724 radiomics features were extracted. Kruskal-Wallis test was performed to compare the four different levels of nodules. Cross-validation was used to verify the results. The Spearman rank correlation coefficient is calculated to evaluate the correlation between features. Results In training cohort, 90 features remained stable during the growth process of metastasis nodules. In verification cohort 1, 293 features remained stable during the growth process of benign nodules. In verification cohort 2, 118 features remained stable during the growth process of metastasis nodules. It is concluded that 20 features remained stable in metastatic nodules (training cohort and verification cohort 2) but not stable in benign nodules (verification cohort 1). Through the cross-validation (n=100), 11 features remained stable more than 90 times. Conclusions This study suggests that a small number of radiomics features from CRC metastatic pulmonary nodules remain relatively stable from small to large, and they do not remain stable in benign nodules. These stable features may reflect the essential characteristics of metastatic nodules and become a valuable point for identifying metastatic pulmonary nodules from benign nodules.
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Affiliation(s)
- Caiyin Liu
- Department of Radiology, First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Qiuhua Meng
- Department of Radiology, First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Qingsi Zeng
- Department of Radiology, First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Huai Chen
- Department of Radiology, First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Yilian Shen
- Department of Radiology, First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Biaoda Li
- Department of Radiology, Shenzhen Hospital, University of Hong Kong, Shenzhen, China
| | - Renli Cen
- Department of Radiology, First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Jiongqiang Huang
- Department of Gastrointestinal Surgery, First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Guangqiu Li
- Department of Pathology, First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Yuting Liao
- Department of Pharmaceutical Diagnostics, GE Healthcare (China), Shanghai, China
| | - Tingfan Wu
- Department of Pharmaceutical Diagnostics, GE Healthcare (China), Shanghai, China
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11
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van den Broek JJ, van Gestel T, Kol SQ, van Geel AM, Geenen RWF, Schreurs WH. Dealing with indeterminate pulmonary nodules in colorectal cancer patients; a systematic review. Eur J Surg Oncol 2021; 47:2749-2756. [PMID: 34119380 DOI: 10.1016/j.ejso.2021.05.043] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2021] [Revised: 04/29/2021] [Accepted: 05/28/2021] [Indexed: 02/07/2023] Open
Abstract
INTRODUCTION Indeterminate pulmonary nodules (IPNs) are frequently encountered on staging computed tomography (CT) in colorectal cancer (CRC) patients and they create diagnostic dilemmas. This systematic review and pooled analysis aims to estimate the incidence and risk of malignancy of IPNs and provide an overview of the existing literature on IPNs in CRC patients. MATERIALS AND METHODS EMBASE, Pubmed and the Cochrane database were searched for papers published between January 2005 and April 2020. Studies describing the incidence of IPNs and the risk of malignancy in CRC patients and where the full text was available in the English language were considered for inclusion. Exclusion criteria included studies that used chest X-ray instead of CT, liver metastasis cohorts, studies with less than 60 CRC patients and reviews. RESULTS A total of 18 studies met the inclusion criteria, involving 8637 patients. Pooled analysis revealed IPNs on staging chest CT in 1327 (15%) of the CRC patients. IPNs appeared to be metastatic disease during follow up in 16% of these patients. Regional lymph node metastases, liver metastases, location of the primary tumour in the rectum, larger IPN size and multiple IPNs are the five most frequently reported parameters predicting the risk of malignancy of IPNs. CONCLUSION A risk stratification model for CRC patients with IPNs is warranted to enable an adequate selection of high risk patients for IPN follow up and to diminish the use of unnecessary repetitive chest CT-scans in the many low risk patients.
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Affiliation(s)
- Joris J van den Broek
- Department of Surgery, Northwest Clinics, PO Box 501, 1815 JD, Alkmaar, the Netherlands.
| | - Tess van Gestel
- Department of Surgery, Northwest Clinics, PO Box 501, 1815 JD, Alkmaar, the Netherlands
| | - Sabrine Q Kol
- Department of Radiology, AUMC, De Boelelaan 1117, 1081 HV, Amsterdam, the Netherlands
| | - Anne M van Geel
- Department of Radiology, Northwest Clinics, PO Box 501, 1815 JD, Alkmaar, the Netherlands
| | - Remy W F Geenen
- Department of Radiology, Northwest Clinics, PO Box 501, 1815 JD, Alkmaar, the Netherlands
| | - Wilhelmina H Schreurs
- Department of Surgery, Northwest Clinics, PO Box 501, 1815 JD, Alkmaar, the Netherlands
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12
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Lee JE, Jeong WG, Kim YH. Differentiation of primary lung cancer from solitary lung metastasis in patients with colorectal cancer: a retrospective cohort study. World J Surg Oncol 2021; 19:28. [PMID: 33487164 PMCID: PMC7831192 DOI: 10.1186/s12957-021-02131-7] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2020] [Accepted: 01/12/2021] [Indexed: 02/08/2023] Open
Abstract
Background This study aimed to evaluate the computed tomography (CT) features of solitary pulmonary nodule (SPN), which can be a non-invasive diagnostic tool to differentiate between primary lung cancer (LC) and solitary lung metastasis (LM) in patients with colorectal cancer (CRC). Methods This retrospective study included SPNs resected in CRC patients between January 2011 and December 2019. The diagnosis of primary LC or solitary LM was based on histopathologic report by thoracoscopic wedge resection. Chest CT images were assessed by two thoracic radiologists, and CT features were identified by consensus. Predictive parameters for the discrimination of primary LC from solitary LM were evaluated using multivariate logistic regression analysis. Results We analyzed CT data of 199 patients (mean age, 65.95 years; 131 men and 68 women). The clinical characteristic of SPNs suggestive of primary LC rather than solitary LM was clinical stages I–II CRC (P < 0.001, odds ratio [OR] 21.70). The CT features of SPNs indicative of primary LC rather than solitary LM were spiculated margin (quantitative) (P = 0.020, OR 8.34), sub-solid density (quantitative) (P < 0.001, OR 115.56), and presence of an air bronchogram (quantitative) (P = 0.032, OR 5.32). Conclusions Quantitative CT features and clinical characteristics of SPNs in patients with CRC could help differentiate between primary LC and solitary LM. Supplementary Information The online version contains supplementary material available at 10.1186/s12957-021-02131-7.
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Affiliation(s)
- Jong Eun Lee
- Department of Radiology, Chonnam National University Hospital, Chonnam National University Medical School, 42 Jebong-ro, Dong-gu, Gwangju, 61469, Republic of Korea
| | - Won Gi Jeong
- Department of Radiology, Chonnam National University Hwasun Hospital, Hwasun-gun, Jeollanam-do, Republic of Korea
| | - Yun-Hyeon Kim
- Department of Radiology, Chonnam National University Hospital, Chonnam National University Medical School, 42 Jebong-ro, Dong-gu, Gwangju, 61469, Republic of Korea.
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13
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Lung visualisation on PET/MRI: implementing a protocol with a short echo-time and low flip-angle volumetric interpolated breath-hold examination sequence. Clin Radiol 2019; 75:239.e15-239.e21. [PMID: 31801658 DOI: 10.1016/j.crad.2019.10.024] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2019] [Accepted: 10/30/2019] [Indexed: 12/29/2022]
Abstract
AIM To assess the diagnostic performance in detecting lung lesions of a short echo-time (TE) and low flip-angle (FA) volumetric interpolated breath-hold examination (VIBE) sequence included in the integrated positron-emission tomography (PET)/magnetic resonance imaging (MRI) protocol. METHOD AND MATERIALS Thirty-seven oncological patients who underwent computed tomography (CT) and PET/MRI, including both a dedicated short TE, low FA VIBE (modified VIBE) and a standard VIBE of the lung, were enrolled. Modified VIBE images were reviewed retrospectively and independently by three raters, to detect pulmonary nodules, parenchymal consolidation, and bands. Three other groups examined standard VIBE, PET, and CT images. MRI and PET findings were compared to CT using Krippendorff's alpha using patient-based and a lesion-based analysis. Krippendorff's alpha was calculated to assess the interobserver agreement among the three raters of the modified VIBE. RESULTS In the patient-based analysis (positivity ≥1 lesion), the comparison of modified VIBE with CT showed an alpha of 0.54 for nodules <6 mm (versus 0.41 for standard VIBE and 0.09 for PET) and an alpha of 0.88 for nodules ≥6 mm (versus 0.74 for standard VIBE and 0.42 for PET). On a lesion-based analysis (presence/absence of each lesion), modified VIBE compared to CT showed an alpha of0.58 for nodules <6 mm (versus 0.44 for standard VIBE and 0.09 for PET) and an alpha of 0.90 for nodules ≥6 mm (versus 0.79 for standard VIBE and 0.50 for PET). The alpha value for the interobserver agreement was 0.90 for nodules <6 mm, 0.91 for nodules ≥6 mm, 1.00 for consolidations, and 0.95 for bands in the patient-based analysis and 0.89, 0.93, 1.00, and 0.95 in the lesion-based analysis. CONCLUSIONS Modified VIBE proved to be reproducible, showed better accuracy than standard VIBE and PET, and very good concordance with CT in assessing lung nodules ≥6 mm, whereas the agreement was less satisfactory for smaller nodules.
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14
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Hu T, Wang S, E X, Yuan Y, Huang L, Wang J, Shi D, Li Y, Peng W, Tong T. CT Morphological Features Integrated With Whole-Lesion Histogram Parameters to Predict Lung Metastasis for Colorectal Cancer Patients With Pulmonary Nodules. Front Oncol 2019; 9:1241. [PMID: 31803619 PMCID: PMC6877751 DOI: 10.3389/fonc.2019.01241] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2019] [Accepted: 10/29/2019] [Indexed: 12/23/2022] Open
Abstract
Purpose: To retrospectively identify the relationships between both CT morphological features and histogram parameters with pulmonary metastasis in patients with colorectal cancer (CRC) and compare the efficacy of single-slice and whole-lesion histogram analysis. Methods: Our study enrolled 196 CRC patients with pulmonary nodules (136 in the training dataset and 60 in the validation dataset). Twenty morphological features of contrast-enhanced chest CT were evaluated. The regions of interests were delineated in single-slice and whole-tumor lesions, and 22 histogram parameters were extracted. Stepwise logistic regression analyses were applied to choose the independent factors of lung metastasis in the morphological features model, the single-slice histogram model and whole-lesion histogram model. The areas under the curve (AUC) was applied to quantify the predictive accuracy of each model. Finally, we built a morphological-histogram nomogram for pulmonary metastasis prediction. Results: The whole-lesion histogram analysis (AUC of 0.888 and 0.865 in the training and validation datasets, respectively) outperformed the single-slice histogram analysis (AUC of 0.872 and 0.819 in the training and validation datasets, respectively) and the CT morphological features model (AUC of 0.869 and 0.845 in the training and validation datasets, respectively). The morphological-histogram model, developed with significant morphological features and whole-lesion histogram parameters, achieved favorable discrimination in both the training dataset (AUC = 0.919) and validation dataset (AUC = 0.895), and good calibration. Conclusions: CT morphological features in combination with whole-lesion histogram parameters can be used to prognosticate pulmonary metastasis for patients with colorectal cancer.
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Affiliation(s)
- TingDan Hu
- Department of Radiology, Fudan University Shanghai Cancer Center, Shanghai, China.,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - ShengPing Wang
- Department of Radiology, Fudan University Shanghai Cancer Center, Shanghai, China.,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Xiangyu E
- Department of Radiotherapy, Fudan University Shanghai Cancer Center, Fudan University, Shanghai, China
| | - Ye Yuan
- Department of Radiotherapy, Fudan University Shanghai Cancer Center, Fudan University, Shanghai, China
| | - Lv Huang
- Department of Radiotherapy, Fudan University Shanghai Cancer Center, Fudan University, Shanghai, China
| | - JiaZhou Wang
- Department of Radiotherapy, Fudan University Shanghai Cancer Center, Fudan University, Shanghai, China
| | - DeBing Shi
- Department of Colorectal Surgery, Fudan University Shanghai Cancer Center, Fudan University, Shanghai, China
| | - Yuan Li
- Department of Pathology, Fudan University Shanghai Cancer Center, Fudan University, Shanghai, China
| | - WeiJun Peng
- Department of Radiology, Fudan University Shanghai Cancer Center, Shanghai, China.,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Tong Tong
- Department of Radiology, Fudan University Shanghai Cancer Center, Shanghai, China.,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
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Kim CH, Yeom SS, Kwak HD, Lee SY, Ju JK, Kim YJ, Kim HR. Clinical Outcomes of Patients With Locally Advanced Rectal Cancer With Persistent Circumferential Resection Margin Invasion After Preoperative Chemoradiotherapy. Ann Coloproctol 2019; 35:72-82. [PMID: 31113172 PMCID: PMC6529752 DOI: 10.3393/ac.2019.04.22] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/11/2019] [Accepted: 04/22/2019] [Indexed: 12/17/2022] Open
Abstract
Purpose Treatment after failure of circumferential resection margin (CRM) conversion after preoperative chemoradiotherapy (pCRT) for locally advanced rectal cancer (LARC) has not been evaluated well. We conducted a single‐center, retrospective analysis to fill this information gap. Methods From 2008 to 2016, we included 112 patients who had predictive CRM involvement on baseline magnetic resonance imaging (MRI) and who underwent surgery following pCRT for LARC. Baseline and posttreatment radiologic and clinical factors were analyzed. Results Of 493 patients with LARC, 112 had CRM involvement by baseline MRI (mrCRM). In 40 patients (35.7%), mrCRM involvement was converted as negative posttreatment CRM (ymrCRM−). Multivariate analysis showed the risk factors for persistent CRM involvement (ymrCRM+) after pCRT were extramural venous invasion (mrEMVI+) (P = 0.030) and lower tumor location (P = 0.007). In addition, persistent CRM involvement after pCRT was an independent risk factor for predicting pathologic CRM involvement. The Cox proportional hazard model showed baseline positive mrEMVI remained significant for disease-free survival (DFS) (P < 0.001). On posttreatment MRI, abdominoperineal resection (P = 0.031), intersphincteric resection (P = 0.006), and persistent CRM involvement (P = 0.001) remained significant for local recurrence-free survival. With regard to DFS, persistent CRM involvement (P = 0.048) and positive EMVI on posttreatment MRI (ymrEMVI) (P = 0.014) were significant. In the patient subgroup with persistent CRM involvement, 5-year DFS in patients with mrEMVI and ymrEMVI was 29.8% and 21.2%, respectively. Conclusion Patients who fail to convert to negative CRM have extremely poor oncologic outcomes. Lower tumor height and negative mrEMVI status were good responders to ymrCRM conversion. Our results suggest that these patients require a more intensive treatment modality.
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Affiliation(s)
- Chang Hyun Kim
- Department of Surgery, Chonnam National University Hwasun Hospital and Medical School, Gwangju, Korea
| | - Seung-Seop Yeom
- Department of Surgery, Chonnam National University Hwasun Hospital and Medical School, Gwangju, Korea
| | - Hand-Duk Kwak
- Department of Surgery, Chonnam National University Medical School, Gwangju, Korea
| | - Soo Young Lee
- Department of Surgery, Chonnam National University Hwasun Hospital and Medical School, Gwangju, Korea
| | - Jae Kyun Ju
- Department of Surgery, Chonnam National University Medical School, Gwangju, Korea
| | - Young Jin Kim
- Department of Surgery, Chonnam National University Hwasun Hospital and Medical School, Gwangju, Korea
| | - Hyeong Rok Kim
- Department of Surgery, Chonnam National University Hwasun Hospital and Medical School, Gwangju, Korea
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16
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Li J, Yuan Y, Yang F, Wang Y, Zhu X, Wang Z, Zheng S, Wan D, He J, Wang J, Ba Y, Bai C, Bai L, Bai W, Bi F, Cai K, Cai M, Cai S, Chen G, Chen K, Chen L, Chen P, Chi P, Dai G, Deng Y, Ding K, Fan Q, Fang W, Fang X, Feng F, Fu C, Fu Q, Gu Y, He Y, Jia B, Jiang K, Lai M, Lan P, Li E, Li D, Li J, Li L, Li M, Li S, Li Y, Li Y, Li Z, Liang X, Liang Z, Lin F, Lin G, Liu H, Liu J, Liu T, Liu Y, Pan H, Pan Z, Pei H, Qiu M, Qu X, Ren L, Shen Z, Sheng W, Song C, Song L, Sun J, Sun L, Sun Y, Tang Y, Tao M, Wang C, Wang H, Wang J, Wang S, Wang X, Wang X, Wang Z, Wu A, Wu N, Xia L, Xiao Y, Xing B, Xiong B, Xu J, Xu J, Xu N, Xu R, Xu Z, Yang Y, Yao H, Ye Y, Yu Y, Yu Y, Yue J, Zhang J, Zhang J, Zhang S, Zhang W, Zhang Y, Zhang Z, Zhang Z, Zhao L, Zhao R, Zhou F, Zhou J, Jin J, Gu J, Shen L. Expert consensus on multidisciplinary therapy of colorectal cancer with lung metastases (2019 edition). J Hematol Oncol 2019; 12:16. [PMID: 30764882 PMCID: PMC6376656 DOI: 10.1186/s13045-019-0702-0] [Citation(s) in RCA: 58] [Impact Index Per Article: 11.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2018] [Accepted: 01/28/2019] [Indexed: 02/08/2023] Open
Abstract
The lungs are the second most common site of metastasis for colorectal cancer (CRC) after the liver. Rectal cancer is associated with a higher incidence of lung metastases compared to colon cancer. In China, the proportion of rectal cancer cases is around 50%, much higher than that in Western countries (nearly 30%). However, there is no available consensus or guideline focusing on CRC with lung metastases. We conducted an extensive discussion and reached a consensus of management for lung metastases in CRC based on current research reports and the experts' clinical experiences and knowledge. This consensus provided detailed approaches of diagnosis and differential diagnosis and provided general guidelines for multidisciplinary therapy (MDT) of lung metastases. We also focused on recommendations of MDT management of synchronous lung metastases and initial metachronous lung metastases. This consensus might improve clinical practice of CRC with lung metastases in China and will encourage oncologists to conduct more clinical trials to obtain high-level evidences about managing lung metastases.
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Affiliation(s)
- Jian Li
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Peking University Cancer Hospital & Institute, No. 52, Fucheng Road, Haidian District, Beijing, 100142, China
| | - Ying Yuan
- The Second Affiliated Hospital of Zhejiang University School of Medicine, No. 88, Jiefang Road, Hangzhou, Zhejiang, China
| | - Fan Yang
- Peking University People's Hospital, No. 11, Xizhimen Nandajie, Beijing, China
| | - Yi Wang
- Peking University People's Hospital, No. 11, Xizhimen Nandajie, Beijing, China
| | - Xu Zhu
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Peking University Cancer Hospital & Institute, No. 52, Fucheng Road, Haidian District, Beijing, 100142, China
| | - Zhenghang Wang
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Peking University Cancer Hospital & Institute, No. 52, Fucheng Road, Haidian District, Beijing, 100142, China
| | - Shu Zheng
- The Second Affiliated Hospital of Zhejiang University School of Medicine, No. 88, Jiefang Road, Hangzhou, Zhejiang, China
| | - Desen Wan
- Sun Yat-sen University Cancer Center, No. 651, Dongfeng East Road, Yuexiu District, Guangzhou, Guangdong, China
| | - Jie He
- National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, No. 17, Panjiayuan Nanli, Chaoyang District, Beijing, China
| | - Jianping Wang
- The Sixth Hospital Affiliated of Sun Yat-sen University, No. 19, Erheng Road, Yuancun, Tianhe District, Guangzhou, Guangdong, China
| | - Yi Ba
- Tianjin Medical University Cancer Institute & Hospital, Huanhu West Road, Tiyuanbei, Hexi District, Tianjin, China
| | - Chunmei Bai
- Peking Union Medical College Hospital, No. 1, Shuaifuyuan, Dongcheng District, Beijing, China
| | - Li Bai
- Chinese People's Liberation Army General Hospital, No. 28, Fuxing Road, Haidian District, Beijing, China
| | - Wei Bai
- Shanxi Provincial Cancer Hospital, No. 3, Zhigong Xincun, Xinghualing District, Taiyuan, Shanxi, China
| | - Feng Bi
- Huaxi Hospital of Sichuan University, No. 37, Guoxue Lane, Wuhou District, Chengdu, Sichuan, China
| | - Kaican Cai
- Nanfang Hospital of Southern Medical University, No. 1838, Guangzhou North Road, Guangzhou, Guangdong, China
| | - Muyan Cai
- Sun Yat-sen University Cancer Center, No. 651, Dongfeng East Road, Yuexiu District, Guangzhou, Guangdong, China
| | - Sanjun Cai
- Fudan University Shanghai Cancer Center, No. 270, Dongan Road, Xuhui District, Shanghai, China
| | - Gong Chen
- Sun Yat-sen University Cancer Center, No. 651, Dongfeng East Road, Yuexiu District, Guangzhou, Guangdong, China
| | - Keneng Chen
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Peking University Cancer Hospital & Institute, No. 52, Fucheng Road, Haidian District, Beijing, 100142, China
| | - Lin Chen
- Chinese People's Liberation Army General Hospital, No. 28, Fuxing Road, Haidian District, Beijing, China
| | - Pengju Chen
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Peking University Cancer Hospital & Institute, No. 52, Fucheng Road, Haidian District, Beijing, 100142, China
| | - Pan Chi
- Fujian Medical University Union Hospital, No. 29, Xinquan Road, Gulou District, Fuzhou, Fujian, China
| | - Guanghai Dai
- Chinese People's Liberation Army General Hospital, No. 28, Fuxing Road, Haidian District, Beijing, China
| | - Yanhong Deng
- The Sixth Hospital Affiliated of Sun Yat-sen University, No. 19, Erheng Road, Yuancun, Tianhe District, Guangzhou, Guangdong, China
| | - Kefeng Ding
- The Second Affiliated Hospital of Zhejiang University School of Medicine, No. 88, Jiefang Road, Hangzhou, Zhejiang, China
| | - Qingxia Fan
- The First Affiliated Hospital of Zhengzhou University, No. 1, Jianhe East Road, Zhengzhou, Henan, China
| | - Weijia Fang
- The First Affiliated Hospital of Zhejiang University School of Medicine, No. 79, Qingchun Road, Zhejiang, Hangzhou, China
| | - Xuedong Fang
- China-Japan Union Hospital of Jilin University, No. 126, Sendai Street, Changchun, Jilin, China
| | - Fengyi Feng
- National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, No. 17, Panjiayuan Nanli, Chaoyang District, Beijing, China
| | - Chuangang Fu
- Tongji University Shanghai East Hospital, No. 150, Jimo Road, Pudong New Area, Shanghai, China
| | - Qihan Fu
- The Second Affiliated Hospital of Zhejiang University School of Medicine, No. 88, Jiefang Road, Hangzhou, Zhejiang, China
| | - Yanhong Gu
- Jiangsu Provincial People's Hospital, No. 300, Guangzhou Road, Nanjing, Jiangsu, China
| | - Yulong He
- The Seventh Affiliated Hospital of Sun Yat-sen University, No. 628, Zhenyuan Road, Shenzhen, Guangdong, China
| | - Baoqing Jia
- Chinese People's Liberation Army General Hospital, No. 28, Fuxing Road, Haidian District, Beijing, China
| | - Kewei Jiang
- Peking University People's Hospital, No. 11, Xizhimen Nandajie, Beijing, China
| | - Maode Lai
- Zhejiang University School of Medicine, No. 866, Yuhangtang Road, Zhejiang, Hangzhou, China
| | - Ping Lan
- The Sixth Hospital Affiliated of Sun Yat-sen University, No. 19, Erheng Road, Yuancun, Tianhe District, Guangzhou, Guangdong, China
| | - Enxiao Li
- The First Affiliated Hospital of Xi'an Jiaotong University, No. 277, Yanta West Road, Xi'an, Shaanxi, China
| | - Dechuan Li
- Zhejiang Cancer Hospital, No. 38, Guangji Road, Banshanqiao, Gongshu District, Zhejiang, Hangzhou, China
| | - Jin Li
- Tongji University Shanghai East Hospital, No. 150, Jimo Road, Pudong New Area, Shanghai, China
| | - Leping Li
- Shandong Provincial Hospital, No. 324, Jingwuweiqi Road, Ji'nan, Shangdong, China
| | - Ming Li
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Peking University Cancer Hospital & Institute, No. 52, Fucheng Road, Haidian District, Beijing, 100142, China
| | - Shaolei Li
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Peking University Cancer Hospital & Institute, No. 52, Fucheng Road, Haidian District, Beijing, 100142, China
| | - Yexiong Li
- National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, No. 17, Panjiayuan Nanli, Chaoyang District, Beijing, China
| | - Yongheng Li
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Peking University Cancer Hospital & Institute, No. 52, Fucheng Road, Haidian District, Beijing, 100142, China
| | - Zhongwu Li
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Peking University Cancer Hospital & Institute, No. 52, Fucheng Road, Haidian District, Beijing, 100142, China
| | - Xiaobo Liang
- Shanxi Provincial Cancer Hospital, No. 3, Zhigong Xincun, Xinghualing District, Taiyuan, Shanxi, China
| | - Zhiyong Liang
- Peking Union Medical College Hospital, No. 1, Shuaifuyuan, Dongcheng District, Beijing, China
| | - Feng Lin
- The Sixth Hospital Affiliated of Sun Yat-sen University, No. 19, Erheng Road, Yuancun, Tianhe District, Guangzhou, Guangdong, China
| | - Guole Lin
- Peking Union Medical College Hospital, No. 1, Shuaifuyuan, Dongcheng District, Beijing, China
| | - Hongjun Liu
- Shandong Provincial Hospital, No. 324, Jingwuweiqi Road, Ji'nan, Shangdong, China
| | - Jianzhong Liu
- Tianjin Medical University Cancer Institute & Hospital, Huanhu West Road, Tiyuanbei, Hexi District, Tianjin, China
| | - Tianshu Liu
- Zhongshan Hospital of Fudan University, No. 180, Fenglin Road, Xuhui District, Shanghai, China
| | - Yunpeng Liu
- The First Hospital of China Medical University, No. 155, Nanjing North Street, Heping District, Shenyang, Liaoning, China
| | - Hongming Pan
- Sir Run Run Shaw Hospital of Zhejiang University School of Medicine, No. 3, Qingchun East Road, Zhejiang, Hangzhou, China
| | - Zhizhong Pan
- Sun Yat-sen University Cancer Center, No. 651, Dongfeng East Road, Yuexiu District, Guangzhou, Guangdong, China
| | - Haiping Pei
- Xiangya Hospital of Central South University, No. 87, Xiangya Road, Changsha, Hunan, China
| | - Meng Qiu
- Huaxi Hospital of Sichuan University, No. 37, Guoxue Lane, Wuhou District, Chengdu, Sichuan, China
| | - Xiujuan Qu
- The First Hospital of China Medical University, No. 155, Nanjing North Street, Heping District, Shenyang, Liaoning, China
| | - Li Ren
- Zhongshan Hospital of Fudan University, No. 180, Fenglin Road, Xuhui District, Shanghai, China
| | - Zhanlong Shen
- Peking University People's Hospital, No. 11, Xizhimen Nandajie, Beijing, China
| | - Weiqi Sheng
- Fudan University Shanghai Cancer Center, No. 270, Dongan Road, Xuhui District, Shanghai, China
| | - Chun Song
- Tongji University Shanghai East Hospital, No. 150, Jimo Road, Pudong New Area, Shanghai, China
| | - Lijie Song
- The First Affiliated Hospital of Zhejiang University School of Medicine, No. 79, Qingchun Road, Zhejiang, Hangzhou, China
| | - Jianguo Sun
- Xinqiao Hospital of Army Medical University, No. 83, Xinqiaozheng Street, Shapingba District, Chongqing, China
| | - Lingyu Sun
- The Fourth Affiliated Hospital of Harbin Medical University, No. 37, Yiyuan Street, Nangang District, Harbin, Heilongjiang, China
| | - Yingshi Sun
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Peking University Cancer Hospital & Institute, No. 52, Fucheng Road, Haidian District, Beijing, 100142, China
| | - Yuan Tang
- National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, No. 17, Panjiayuan Nanli, Chaoyang District, Beijing, China
| | - Min Tao
- The First Affiliated Hospital of Soochow University, No. 188, Shizi Street, Canglang District, Suzhou, Jiangsu, China
| | - Chang Wang
- The First Affiliated Hospital of Jilin University, No. 71, Xinmin Road, Changchun, Jilin, China
| | - Haijiang Wang
- The Third People's Hospital of Shenzhen, No. 29, Bulan Road, Longgang District, Shenzhen, Guangdong, China
| | - Jun Wang
- Peking University People's Hospital, No. 11, Xizhimen Nandajie, Beijing, China
| | - Shubin Wang
- Peking University Shenzhen Hospital, No. 1120, Lianhua Road, Futian District, Shenzhen, Guangdong, China
| | - Xicheng Wang
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Peking University Cancer Hospital & Institute, No. 52, Fucheng Road, Haidian District, Beijing, 100142, China
| | - Xishan Wang
- National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, No. 17, Panjiayuan Nanli, Chaoyang District, Beijing, China
| | - Ziqiang Wang
- Huaxi Hospital of Sichuan University, No. 37, Guoxue Lane, Wuhou District, Chengdu, Sichuan, China
| | - Aiwen Wu
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Peking University Cancer Hospital & Institute, No. 52, Fucheng Road, Haidian District, Beijing, 100142, China
| | - Nan Wu
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Peking University Cancer Hospital & Institute, No. 52, Fucheng Road, Haidian District, Beijing, 100142, China
| | - Lijian Xia
- Shandong Qianfoshan Hospital, No. 16766, Jingshi Road, Lixia District, Ji'nan, Shandong, China
| | - Yi Xiao
- Peking Union Medical College Hospital, No. 1, Shuaifuyuan, Dongcheng District, Beijing, China
| | - Baocai Xing
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Peking University Cancer Hospital & Institute, No. 52, Fucheng Road, Haidian District, Beijing, 100142, China
| | - Bin Xiong
- Zhongnan Hospital of Wuhan University, No. 169, Donghu Road, Wuchang District, Wuhan, Hubei, China
| | - Jianmin Xu
- Zhongshan Hospital of Fudan University, No. 180, Fenglin Road, Xuhui District, Shanghai, China
| | - Jianming Xu
- 307 Hospital of the Chinese People's Liberation Army, Road 8, Dong Street, Fengtai Distinct, Beijing, China
| | - Nong Xu
- The First Affiliated Hospital of Zhejiang University School of Medicine, No. 79, Qingchun Road, Zhejiang, Hangzhou, China
| | - Ruihua Xu
- Sun Yat-sen University Cancer Center, No. 651, Dongfeng East Road, Yuexiu District, Guangzhou, Guangdong, China
| | - Zhongfa Xu
- Affiliated Hospital of Shandong Academy of Medical Sciences, No. 38, Wuyingshan Road, Tianqiao District, Ji'nan, Shandong, China
| | - Yue Yang
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Peking University Cancer Hospital & Institute, No. 52, Fucheng Road, Haidian District, Beijing, 100142, China
| | - Hongwei Yao
- Beijing Friendship Hospital, No. 95, Yong'an Road, Xicheng District, Beijing, China
| | - Yingjiang Ye
- Peking University People's Hospital, No. 11, Xizhimen Nandajie, Beijing, China
| | - Yonghua Yu
- Shandong Cancer Hospital, No. 440, Jiyan Road, Ji'nan, Shandong, China
| | - Yueming Yu
- The Fourth Hospital of Hebei Medical University, No. 12, Jiankang Road, Shijiazhuang, Hebei, China
| | - Jinbo Yue
- Shandong Cancer Hospital, No. 440, Jiyan Road, Ji'nan, Shandong, China
| | - Jingdong Zhang
- Liaoning Cancer Hospital & Institute, No. 44, Xiaoheyan Road, Dadong District, Shenyang, Liaoning, China
| | - Jun Zhang
- Ruijin Hospital of Shanghai Jiaotong University School of Medicine, No. 197, Ruijin 2nd Road, Shanghai, China
| | - Suzhan Zhang
- The Second Affiliated Hospital of Zhejiang University School of Medicine, No. 88, Jiefang Road, Hangzhou, Zhejiang, China
| | - Wei Zhang
- Changhai Hospital, No. 168, Changhai Road, Yangpu District, Shanghai, China
| | - Yanqiao Zhang
- Harbin Medical University Cancer Hospital, No. 150, Haping Road, Nangang District, Harbin, Heilongjiang, China
| | - Zhen Zhang
- Fudan University Shanghai Cancer Center, No. 270, Dongan Road, Xuhui District, Shanghai, China
| | - Zhongtao Zhang
- Beijing Friendship Hospital, No. 95, Yong'an Road, Xicheng District, Beijing, China
| | - Lin Zhao
- Peking Union Medical College Hospital, No. 1, Shuaifuyuan, Dongcheng District, Beijing, China
| | - Ren Zhao
- Ruijin Hospital of Shanghai Jiaotong University School of Medicine, No. 197, Ruijin 2nd Road, Shanghai, China
| | - Fuxiang Zhou
- Zhongnan Hospital of Wuhan University, No. 169, Donghu Road, Wuchang District, Wuhan, Hubei, China
| | - Jian Zhou
- Zhongshan Hospital of Fudan University, No. 180, Fenglin Road, Xuhui District, Shanghai, China
| | - Jing Jin
- National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, No. 17, Panjiayuan Nanli, Chaoyang District, Beijing, China.
| | - Jin Gu
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Peking University Cancer Hospital & Institute, No. 52, Fucheng Road, Haidian District, Beijing, 100142, China.
| | - Lin Shen
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Peking University Cancer Hospital & Institute, No. 52, Fucheng Road, Haidian District, Beijing, 100142, China.
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17
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Lee KH, Park JH, Kim YH, Lee KW, Kim JW, Oh HK, Jeon JJ, Yoon H, Kim J, Lee KH. Diagnostic Yield and False-Referral Rate of Staging Chest CT in Patients with Colon Cancer. Radiology 2018; 289:535-545. [PMID: 30084734 DOI: 10.1148/radiol.2018180009] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
Purpose To measure the diagnostic yield and false-referral rate (FRR) of staging contrast material-enhanced chest CT based on the clinical stage from contrast-enhanced abdominal CT in patients with colon cancer. Materials and Methods This retrospective study included 1743 patients (mean age, 63.4 years; range, 18-96 years) with a diagnosis of colon cancer. The primary outcomes were diagnostic yield and FRR of contrast-enhanced chest CT in the detection of thoracic metastasis. The proportions of patients with occult thoracic metastasis and those undergoing pulmonary metastasectomy for true-positive metastases were key secondary outcomes. The outcomes were stratified according to clinical stage at contrast-enhanced abdominal CT. Results The diagnostic yields in clinical stage 0/I, cII, cIII, and cIV were 0% (95% confidence interval [CI]: 0%, 0.8%), 1.3% (95% CI: 0.4%, 3.3%), 4.4% (95% CI: 3.0%, 6.1%), and 43.3% (95% CI: 36.8%, 49.9%), respectively. The corresponding FRRs were 5.7% (95% CI: 3.8%, 8.2%), 2.9% (95% CI: 1.3%, 5.5%), 6.7% (95% CI: 5.0%, 8.8%), and 6.1% (95% CI: 3.4%, 10.0%), respectively. The proportions of patients with occult metastasis were 0% (95% CI: 0%, 0.8%), 3.3% (95% CI: 1.6%, 5.9%), 1.5% (95% CI: 0.8%, 2.7%), and 6.1% (95% CI: 3.4%, 10.0%), respectively. The proportion of patients who underwent pulmonary metastasectomy was 0% (none of 474; 95% CI: 0%, 0.8%) for clinical stage 0/I tumors. Conclusion In clinical stages 0 and I, the diagnostic yield of staging contrast-enhanced chest CT in detecting thoracic metastasis was zero. For clinical stages II, III, and IV, contrast-enhanced chest CT as a baseline examination was helpful for the detection of thoracic metastasis and allowed for the possibility of a curative metastasectomy. There was no significant association between clinical stage and false-referral rate. © RSNA, 2018 Online supplemental material is available for this article.
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Affiliation(s)
- Kyung Hee Lee
- From the Departments of Radiology (K. Hee Lee, J.H.P., Y.H.K., K.W.L., J.K., K. Ho Lee), Internal Medicine (J.W.K., H.Y.), and Surgery (H.K.O.), Seoul National University Bundang Hospital, Seoul National University College of Medicine, 300 Gumi-dong, Bundang-gu, Seongnam, Gyeonggi-do 13620, Korea; Institute of Radiation Medicine, Seoul National University Medical Research Center, Seoul, Korea (Y.H.K., K.W.L.); Department of Statistics, University of Seoul, Seoul, Korea (J.J.J.); and Program in Biomedical Radiation Sciences, Department of Transdisciplinary Studies, Graduate School of Convergence Science and Technology Seoul National University, Seoul, Korea (K. Ho Lee)
| | - Ji Hoon Park
- From the Departments of Radiology (K. Hee Lee, J.H.P., Y.H.K., K.W.L., J.K., K. Ho Lee), Internal Medicine (J.W.K., H.Y.), and Surgery (H.K.O.), Seoul National University Bundang Hospital, Seoul National University College of Medicine, 300 Gumi-dong, Bundang-gu, Seongnam, Gyeonggi-do 13620, Korea; Institute of Radiation Medicine, Seoul National University Medical Research Center, Seoul, Korea (Y.H.K., K.W.L.); Department of Statistics, University of Seoul, Seoul, Korea (J.J.J.); and Program in Biomedical Radiation Sciences, Department of Transdisciplinary Studies, Graduate School of Convergence Science and Technology Seoul National University, Seoul, Korea (K. Ho Lee)
| | - Young Hoon Kim
- From the Departments of Radiology (K. Hee Lee, J.H.P., Y.H.K., K.W.L., J.K., K. Ho Lee), Internal Medicine (J.W.K., H.Y.), and Surgery (H.K.O.), Seoul National University Bundang Hospital, Seoul National University College of Medicine, 300 Gumi-dong, Bundang-gu, Seongnam, Gyeonggi-do 13620, Korea; Institute of Radiation Medicine, Seoul National University Medical Research Center, Seoul, Korea (Y.H.K., K.W.L.); Department of Statistics, University of Seoul, Seoul, Korea (J.J.J.); and Program in Biomedical Radiation Sciences, Department of Transdisciplinary Studies, Graduate School of Convergence Science and Technology Seoul National University, Seoul, Korea (K. Ho Lee)
| | - Kyung Won Lee
- From the Departments of Radiology (K. Hee Lee, J.H.P., Y.H.K., K.W.L., J.K., K. Ho Lee), Internal Medicine (J.W.K., H.Y.), and Surgery (H.K.O.), Seoul National University Bundang Hospital, Seoul National University College of Medicine, 300 Gumi-dong, Bundang-gu, Seongnam, Gyeonggi-do 13620, Korea; Institute of Radiation Medicine, Seoul National University Medical Research Center, Seoul, Korea (Y.H.K., K.W.L.); Department of Statistics, University of Seoul, Seoul, Korea (J.J.J.); and Program in Biomedical Radiation Sciences, Department of Transdisciplinary Studies, Graduate School of Convergence Science and Technology Seoul National University, Seoul, Korea (K. Ho Lee)
| | - Jin Won Kim
- From the Departments of Radiology (K. Hee Lee, J.H.P., Y.H.K., K.W.L., J.K., K. Ho Lee), Internal Medicine (J.W.K., H.Y.), and Surgery (H.K.O.), Seoul National University Bundang Hospital, Seoul National University College of Medicine, 300 Gumi-dong, Bundang-gu, Seongnam, Gyeonggi-do 13620, Korea; Institute of Radiation Medicine, Seoul National University Medical Research Center, Seoul, Korea (Y.H.K., K.W.L.); Department of Statistics, University of Seoul, Seoul, Korea (J.J.J.); and Program in Biomedical Radiation Sciences, Department of Transdisciplinary Studies, Graduate School of Convergence Science and Technology Seoul National University, Seoul, Korea (K. Ho Lee)
| | - Heung-Kwon Oh
- From the Departments of Radiology (K. Hee Lee, J.H.P., Y.H.K., K.W.L., J.K., K. Ho Lee), Internal Medicine (J.W.K., H.Y.), and Surgery (H.K.O.), Seoul National University Bundang Hospital, Seoul National University College of Medicine, 300 Gumi-dong, Bundang-gu, Seongnam, Gyeonggi-do 13620, Korea; Institute of Radiation Medicine, Seoul National University Medical Research Center, Seoul, Korea (Y.H.K., K.W.L.); Department of Statistics, University of Seoul, Seoul, Korea (J.J.J.); and Program in Biomedical Radiation Sciences, Department of Transdisciplinary Studies, Graduate School of Convergence Science and Technology Seoul National University, Seoul, Korea (K. Ho Lee)
| | - Jong-June Jeon
- From the Departments of Radiology (K. Hee Lee, J.H.P., Y.H.K., K.W.L., J.K., K. Ho Lee), Internal Medicine (J.W.K., H.Y.), and Surgery (H.K.O.), Seoul National University Bundang Hospital, Seoul National University College of Medicine, 300 Gumi-dong, Bundang-gu, Seongnam, Gyeonggi-do 13620, Korea; Institute of Radiation Medicine, Seoul National University Medical Research Center, Seoul, Korea (Y.H.K., K.W.L.); Department of Statistics, University of Seoul, Seoul, Korea (J.J.J.); and Program in Biomedical Radiation Sciences, Department of Transdisciplinary Studies, Graduate School of Convergence Science and Technology Seoul National University, Seoul, Korea (K. Ho Lee)
| | - Hyuk Yoon
- From the Departments of Radiology (K. Hee Lee, J.H.P., Y.H.K., K.W.L., J.K., K. Ho Lee), Internal Medicine (J.W.K., H.Y.), and Surgery (H.K.O.), Seoul National University Bundang Hospital, Seoul National University College of Medicine, 300 Gumi-dong, Bundang-gu, Seongnam, Gyeonggi-do 13620, Korea; Institute of Radiation Medicine, Seoul National University Medical Research Center, Seoul, Korea (Y.H.K., K.W.L.); Department of Statistics, University of Seoul, Seoul, Korea (J.J.J.); and Program in Biomedical Radiation Sciences, Department of Transdisciplinary Studies, Graduate School of Convergence Science and Technology Seoul National University, Seoul, Korea (K. Ho Lee)
| | - Jihang Kim
- From the Departments of Radiology (K. Hee Lee, J.H.P., Y.H.K., K.W.L., J.K., K. Ho Lee), Internal Medicine (J.W.K., H.Y.), and Surgery (H.K.O.), Seoul National University Bundang Hospital, Seoul National University College of Medicine, 300 Gumi-dong, Bundang-gu, Seongnam, Gyeonggi-do 13620, Korea; Institute of Radiation Medicine, Seoul National University Medical Research Center, Seoul, Korea (Y.H.K., K.W.L.); Department of Statistics, University of Seoul, Seoul, Korea (J.J.J.); and Program in Biomedical Radiation Sciences, Department of Transdisciplinary Studies, Graduate School of Convergence Science and Technology Seoul National University, Seoul, Korea (K. Ho Lee)
| | - Kyoung Ho Lee
- From the Departments of Radiology (K. Hee Lee, J.H.P., Y.H.K., K.W.L., J.K., K. Ho Lee), Internal Medicine (J.W.K., H.Y.), and Surgery (H.K.O.), Seoul National University Bundang Hospital, Seoul National University College of Medicine, 300 Gumi-dong, Bundang-gu, Seongnam, Gyeonggi-do 13620, Korea; Institute of Radiation Medicine, Seoul National University Medical Research Center, Seoul, Korea (Y.H.K., K.W.L.); Department of Statistics, University of Seoul, Seoul, Korea (J.J.J.); and Program in Biomedical Radiation Sciences, Department of Transdisciplinary Studies, Graduate School of Convergence Science and Technology Seoul National University, Seoul, Korea (K. Ho Lee)
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18
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Newton AD, Predina JD, Frenzel-Sulyok LG, Shin MH, Wang Y, Singhal S. Intraoperative near-infrared imaging can identify sub-centimeter colorectal cancer lung metastases during pulmonary metastasectomy. J Thorac Dis 2018; 10:E544-E548. [PMID: 30174930 DOI: 10.21037/jtd.2018.06.161] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Affiliation(s)
- Andrew D Newton
- Center for Precision Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.,Department of Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Jarrod D Predina
- Center for Precision Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.,Division of Thoracic Surgery, Department of Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Lydia G Frenzel-Sulyok
- Center for Precision Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.,Division of Thoracic Surgery, Department of Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Michael H Shin
- Center for Precision Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.,Division of Thoracic Surgery, Department of Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Yiqing Wang
- College of Engineering and Applied Sciences, Nanjing University, Nanjing 210000, China
| | - Sunil Singhal
- Center for Precision Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.,Division of Thoracic Surgery, Department of Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
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19
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Hu T, Wang S, Huang L, Wang J, Shi D, Li Y, Tong T, Peng W. A clinical-radiomics nomogram for the preoperative prediction of lung metastasis in colorectal cancer patients with indeterminate pulmonary nodules. Eur Radiol 2018; 29:439-449. [DOI: 10.1007/s00330-018-5539-3] [Citation(s) in RCA: 45] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2018] [Revised: 05/01/2018] [Accepted: 05/14/2018] [Indexed: 12/19/2022]
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20
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Role of 18F-Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography in the Diagnosis of Newly Found Suspected Malignant Solitary Pulmonary Lesions in Patients Who Have Received Curative Treatment for Colorectal Cancer. Gastroenterol Res Pract 2017; 2017:3458739. [PMID: 28487728 PMCID: PMC5405602 DOI: 10.1155/2017/3458739] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/09/2017] [Revised: 02/28/2017] [Accepted: 03/09/2017] [Indexed: 12/13/2022] Open
Abstract
Background. Positron emission tomography/computed tomography (PET/CT) is recommended for colorectal cancer (CRC) patients with suspected malignant pulmonary lesions. This study aims to systematically discuss the 18F-FDG-PET/CT diagnosis of solitary pulmonary lesions that are strongly suspected to be malignant in CRC patients who have previously undergone curative therapy. Methods. This retrospective study involved 49 consecutive CRC patients who had previously undergone curative therapy and then underwent PET/CT for the investigation of solitary pulmonary lesions that were strongly suspected to be malignant. Results. Pathological examination confirmed the presence of pulmonary metastases (29 patients, 59.2%), primary lung cancer (15 patients, 30.6%), and benign pulmonary disease (5 patients, 10.2%). Small lung lesions, advanced pathological stage, adjuvant chemotherapy after CRC surgery, solitary pulmonary lesions with lower border irregularity, higher carcinoembryonic antigen level, and the lack of concomitant mediastinal lymph node metastasis were more likely to be associated with pulmonary metastasis than with primary lung cancer. None of these factors was independently significant in the multivariate analysis. Conclusion. Clinicopathological characteristics help to differentiate metastasis and primary lung cancer to some extent during the diagnosis of solitary pulmonary lesions suspected to be malignant in this group of patients. This may provide valuable information to clinicians.
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21
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Indeterminate Pulmonary Nodules in Resected Liver Metastases from Colorectal Cancer: A Comparison of Patient Outcomes. World J Surg 2017; 41:1834-1839. [DOI: 10.1007/s00268-017-3930-x] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/15/2023]
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22
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Hammer MM, Mortani Barbosa EJ. Predictive factors for malignancy in incidental pulmonary nodules detected in breast cancer patients at baseline CT. Eur Radiol 2016; 27:2802-2809. [PMID: 27798753 DOI: 10.1007/s00330-016-4627-5] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2016] [Revised: 09/02/2016] [Accepted: 09/29/2016] [Indexed: 12/21/2022]
Abstract
OBJECTIVES Pulmonary nodules are commonly encountered at staging CTs in patients with extrathoracic malignancies, but their significance on a per-patient basis remains uncertain. METHODS We undertook a retrospective analysis of pulmonary nodules identified in patients with a diagnosis of breast cancer from 2010 - 2015, evaluating nodules present at a baseline CT (i.e. prevalent nodules). We reviewed 211 patients with 248 individual nodules. RESULTS The rate of malignancy in prevalent nodules is low, approximately 13 %. Variables associated with metastasis include pleural studding, hilar lymphadenopathy and the presence of extrapulmonary metastasis, as well as number of nodules, nodule size and nodule shape. Using a combination of these factors, we have developed an evidence-based multivariate decision tree to predict which nodules are malignant in these patients, which is 91 % accurate and 100 % sensitive for metastasis. CONCLUSIONS We propose a simplified clinical prediction algorithm to guide radiologists and oncologists in managing patients with breast cancer and incidental pulmonary nodules. KEY POINTS • Incidental pulmonary nodules are common on computed tomography in breast cancer patients. • Nodules present at baseline have a lower malignancy risk than incident nodules. • We present an evidence-based decision algorithm predicting which nodules are likely malignant. • This algorithm can help direct patient management.
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Affiliation(s)
- Mark M Hammer
- Division of Cardiothoracic Imaging, Department of Radiology, Perelman School of Medicine, University of Pennsylvania, 3400 Spruce Street, Ground Floor Founders Bldg., Philadelphia, PA, 19104, USA
| | - Eduardo J Mortani Barbosa
- Division of Cardiothoracic Imaging, Department of Radiology, Perelman School of Medicine, University of Pennsylvania, 3400 Spruce Street, Ground Floor Founders Bldg., Philadelphia, PA, 19104, USA.
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23
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Surgical Management of the Colorectal Cancer Patient with Simultaneous Liver and Lung Metastases. CURRENT COLORECTAL CANCER REPORTS 2016. [DOI: 10.1007/s11888-016-0325-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
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24
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Prediction of Pulmonary Metastasis in Renal Cell Carcinoma Patients with Indeterminate Pulmonary Nodules. Eur Urol 2016; 69:352-60. [DOI: 10.1016/j.eururo.2015.08.053] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2015] [Accepted: 08/29/2015] [Indexed: 12/21/2022]
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