IMPORTANCE of PRETREATMENT 18F-FDG PET/CT TEXTURE ANALYSIS in PREDICTING EGFR and ALK MUTATION in PATIENTS with NON-SMALL CELL LUNG CANCER

Agüloğlu, Nurşin; Aksu, Ayşegül; Akyol, Murat; Katgi, Nuran; Doksöz, Tuğçe Çiftçi

doi:10.1055/a-1868-4918

Cited by 7 publications

(3 citation statements)

References 24 publications

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“…Recently, the idea that imaging studies contain a great quantity of data, in the form of grey-level patterns, which are imperceptible to the human eyes, has become more and more interesting [ 116 , 117 , 118 , 119 , 120 , 121 , 122 , 123 , 124 , 125 , 126 , 127 , 128 , 129 , 130 , 131 , 132 , 133 , 134 ]. These texture features, when correlated with clinical-pathological data and outcomes [ 135 , 136 , 137 , 138 , 139 , 140 , 141 , 142 , 143 , 144 , 145 , 146 , 147 , 148 , 149 , 150 , 151 , 152 , 153 ], theoretically allow diagnostic and prognostic assessment [ 154 , 155 , 156 , 157 , 158 , 159 , 160 , 161 , 162 ]. The assessment of textural characteristics, obtained by radiological images, which depend on mathematical analysis, such as histogram analysis, is called radiomics [ 163 , 164 , 165 , …”

Section: Common Postoperative Complicationsmentioning

confidence: 99%

Post-Surgical Imaging Assessment in Rectal Cancer: Normal Findings and Complications

Muzio

Fusco

Cutolo

et al. 2023

JCM

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Rectal cancer (RC) is one of the deadliest malignancies worldwide. Surgery is the most common treatment for RC, performed in 63.2% of patients. The type of surgical approach chosen aims to achieve maximum residual function with the lowest risk of recurrence. The selection is made by a multidisciplinary team that assesses the characteristics of the patient and the tumor. Total mesorectal excision (TME), including both low anterior resection (LAR) and abdominoperineal resection (APR), is still the standard of care for RC. Radical surgery is burdened by a 31% rate of major complications (Clavien–Dindo grade 3–4), such as anastomotic leaks and a risk of a permanent stoma. In recent years, less-invasive techniques, such as local excision, have been tested. These additional procedures could mitigate the morbidity of rectal resection, while providing acceptable oncologic results. The “watch and wait” approach is not a globally accepted model of care but encouraging results on selected groups of patients make it a promising strategy. In this plethora of treatments, the radiologist is called upon to distinguish a physiological from a pathological postoperative finding. The aim of this narrative review is to identify the main post-surgical complications and the most effective imaging techniques.

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Section: Common Postoperative Complicationsmentioning

confidence: 99%

Post-Surgical Imaging Assessment in Rectal Cancer: Normal Findings and Complications

Muzio

Fusco

Cutolo

et al. 2023

JCM

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“…Profiling the TIME phenotype aids in patient selection for immunotherapy. Agüloğlu ( 39 ) and Chang ( 40 ) predicted anaplastic lymphoma kinase (ALK) rearrangement and EGFR mutation status in NSCLC via radiomics models based on 18 F-FDG PET/CT images, assisting in targeted therapy decisions. Numerous studies have demonstrated the capability of 18 F-FDG PET/CT radiomics models to predict programmed death ligand-1 (PD-L1) expression in NSCLC ( 41 – 44 ).…”

Section: Progress In the Application Of Pet-related Radiomics In Lung...mentioning

confidence: 99%

Current status and prospect of PET-related imaging radiomics in lung cancer

Tang,

Wu,

Chen

et al. 2023

Front. Oncol.

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Lung cancer is highly aggressive, which has a high mortality rate. Major types encompass lung adenocarcinoma, lung squamous cell carcinoma, lung adenosquamous carcinoma, small cell carcinoma, and large cell carcinoma. Lung adenocarcinoma and lung squamous cell carcinoma together account for more than 80% of cases. Diverse subtypes demand distinct treatment approaches. The application of precision medicine necessitates prompt and accurate evaluation of treatment effectiveness, contributing to the improvement of treatment strategies and outcomes. Medical imaging is crucial in the diagnosis and management of lung cancer, with techniques such as fluoroscopy, computed radiography (CR), digital radiography (DR), computed tomography (CT), magnetic resonance imaging (MRI), positron emission tomography (PET)/CT, and PET/MRI being essential tools. The surge of radiomics in recent times offers fresh promise for cancer diagnosis and treatment. In particular, PET/CT and PET/MRI radiomics, extensively studied in lung cancer research, have made advancements in diagnosing the disease, evaluating metastasis, predicting molecular subtypes, and forecasting patient prognosis. While conventional imaging methods continue to play a primary role in diagnosis and assessment, PET/CT and PET/MRI radiomics simultaneously provide detailed morphological and functional information. This has significant clinical potential value, offering advantages for lung cancer diagnosis and treatment. Hence, this manuscript provides a review of the latest developments in PET-related radiomics for lung cancer.

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“…Agüloğlu et al. ( 50 ) found that the NB machine learning algorithm established using the GLZLM_GLNU feature and clinical data contributed to the most successful prediction of EGFR mutations (AUC = 0.751). Shiri et al.…”

Section: Introductionmentioning

confidence: 99%

New research progress on 18F-FDG PET/CT radiomics for EGFR mutation prediction in lung adenocarcinoma: a review

Ge,

Gao,

Niu

et al. 2023

Front. Oncol.

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Lung cancer, the most frequently diagnosed cancer worldwide, is the leading cause of cancer-associated deaths. In recent years, significant progress has been achieved in basic and clinical research concerning the epidermal growth factor receptor (EGFR), and the treatment of lung adenocarcinoma has also entered a new era of individualized, targeted therapies. However, the detection of lung adenocarcinoma is usually invasive. 18F-FDG PET/CT can be used as a noninvasive molecular imaging approach, and radiomics can acquire high-throughput data from standard images. These methods play an increasingly prominent role in diagnosing and treating cancers. Herein, we reviewed the progress in applying 18F-FDG PET/CT and radiomics in lung adenocarcinoma clinical research and how these data are analyzed via traditional statistics, machine learning, and deep learning to predict EGFR mutation status, all of which achieved satisfactory results. Traditional statistics extract features effectively, machine learning achieves higher accuracy with complex algorithms, and deep learning obtains significant results through end-to-end methods. Future research should combine these methods to achieve more accurate predictions, providing reliable evidence for the precision treatment of lung adenocarcinoma. At the same time, facing challenges such as data insufficiency and high algorithm complexity, future researchers must continuously explore and optimize to better apply to clinical practice.

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IMPORTANCE of PRETREATMENT 18F-FDG PET/CT TEXTURE ANALYSIS in PREDICTING EGFR and ALK MUTATION in PATIENTS with NON-SMALL CELL LUNG CANCER

Cited by 7 publications

References 24 publications

Post-Surgical Imaging Assessment in Rectal Cancer: Normal Findings and Complications

Post-Surgical Imaging Assessment in Rectal Cancer: Normal Findings and Complications

Current status and prospect of PET-related imaging radiomics in lung cancer

New research progress on 18F-FDG PET/CT radiomics for EGFR mutation prediction in lung adenocarcinoma: a review

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