Literature DB >> 26098287

Prognostic Significance of Intratumoral Metabolic Heterogeneity on 18F-FDG PET/CT in Pathological N0 Non-Small Cell Lung Cancer.

Do-Hoon Kim1, Ji-Hoon Jung, Seung Hyun Son, Choon-Young Kim, Chae Moon Hong, Jong-Ryool Oh, Shin Young Jeong, Sang-Woo Lee, Jaetae Lee, Byeong-Cheol Ahn.   

Abstract

PURPOSE: The aim of the study was to evaluate the prognostic significance of intratumoral metabolic heterogeneity on pretreatment F-FDG PET/CT in patients with lung cancer who were pathologically N0 (pN0) after curative surgical resection.
METHODS: We examined 119 patients (M/F = 79/40; mean age, 64.6 ± 9.0 years) who had undergone pretreatment F-FDG PET/CT and were diagnosed as pN0 after curative surgery for adenocarcinoma (ADC; n = 67) or squamous cell carcinoma (SQCC; n = 52). Heterogeneity factor (HF) and other metabolic parameters (SUVmax, metabolic tumor volume [MTV] and total lesion glycolysis [TLG]) for the primary lesions were measured, and the results were analyzed for recurrence. The HF, defined as the derivative of the volume-threshold function from 20% to 80%, was computed for primary lesions. Univariate and multivariate analyses for recurrence were performed using the Kaplan-Meier method and using the Cox proportional hazards model.
RESULTS: SUVmax, MTV, TLG, and HF were statistically different between patients with ADC and SQCC. Forty-one (34.5%) of 119 patients experienced recurrence (ADC, 25/67 = 37.3% vs. SQCC, 16/52 = 30.8%). Results of univariate analysis indicate that SUVmax, MTV, TLG, and HF in ADC and TLG and HF in SQCC were predictors for recurrence. After adjusting for sex, age, and histological grade in multivariate analysis, high SUVmax, MTV, TLG, and HF in ADC exhibited an association with increased risk of recurrence.
CONCLUSIONS: Metabolic parameters and heterogeneity of primary tumor on pretreatment F-FDG PET/CT can predict recurrence in pN0 NSCLC patients of ADC type who have undergone curative surgery but not in patients of SQCC type.

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Year:  2015        PMID: 26098287     DOI: 10.1097/RLU.0000000000000867

Source DB:  PubMed          Journal:  Clin Nucl Med        ISSN: 0363-9762            Impact factor:   7.794


  24 in total

1.  Use of radiomics based on 18F-FDG PET/CT and machine learning methods to aid clinical decision-making in the classification of solitary pulmonary lesions: an innovative approach.

Authors:  Yi Zhou; Xue-Lei Ma; Ting Zhang; Jian Wang; Tao Zhang; Rong Tian
Journal:  Eur J Nucl Med Mol Imaging       Date:  2021-02-05       Impact factor: 9.236

2.  Ability of FDG PET and CT radiomics features to differentiate between primary and metastatic lung lesions.

Authors:  Margarita Kirienko; Luca Cozzi; Alexia Rossi; Emanuele Voulaz; Lidija Antunovic; Antonella Fogliata; Arturo Chiti; Martina Sollini
Journal:  Eur J Nucl Med Mol Imaging       Date:  2018-04-06       Impact factor: 9.236

Review 3.  Radiomics in Oncological PET/CT: Clinical Applications.

Authors:  Jeong Won Lee; Sang Mi Lee
Journal:  Nucl Med Mol Imaging       Date:  2017-10-20

4.  Prediction of disease-free survival by the PET/CT radiomic signature in non-small cell lung cancer patients undergoing surgery.

Authors:  Margarita Kirienko; Luca Cozzi; Lidija Antunovic; Lisa Lozza; Antonella Fogliata; Emanuele Voulaz; Alexia Rossi; Arturo Chiti; Martina Sollini
Journal:  Eur J Nucl Med Mol Imaging       Date:  2017-09-24       Impact factor: 9.236

Review 5.  Drugging cancer metabolism: Expectations vs. reality.

Authors:  David C Montrose; Lorenzo Galluzzi
Journal:  Int Rev Cell Mol Biol       Date:  2019-07-29       Impact factor: 6.813

6.  The clinical value of texture analysis of dual-time-point 18F-FDG-PET/CT imaging to differentiate between 18F-FDG-avid benign and malignant pulmonary lesions.

Authors:  Masatoyo Nakajo; Megumi Jinguji; Masaya Aoki; Atsushi Tani; Masami Sato; Takashi Yoshiura
Journal:  Eur Radiol       Date:  2019-11-14       Impact factor: 5.315

7.  Intratumoral Metabolic Heterogeneity and Other Quantitative 18F-FDG PET/CT Parameters for Prognosis Prediction in Esophageal Cancer.

Authors:  Akilan Gopal; Yin Xi; Rathan M Subramaniam; Daniella F Pinho
Journal:  Radiol Imaging Cancer       Date:  2020-12-18

8.  PERCIST in Perspective.

Authors:  Joo Hyun O; Richard L Wahl
Journal:  Nucl Med Mol Imaging       Date:  2017-12-18

9.  FDG PET-CT SUVmax and IASLC/ATS/ERS histologic classification: a new profile of lung adenocarcinoma with prognostic value.

Authors:  Marina Suárez-Piñera; José Belda-Sanchis; Alvaro Taus; Albert Sánchez-Font; Antoni Mestre-Fusco; Marcel Jiménez; Lara Pijuan
Journal:  Am J Nucl Med Mol Imaging       Date:  2018-04-25

10.  Relationship Between Dual Time Point FDG PET/CT and Clinical Prognostic Indexes in Patients with High Grade Lymphoma: a Pilot Study.

Authors:  Do Hyoung Lim; Jai Hyuen Lee
Journal:  Nucl Med Mol Imaging       Date:  2017-04-10
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