Search Our Scientific Publications & Authors

Publications
find publications by category +
Translate page:

Automated radiomic analysis of CT images to predict likelihood of spontaneous passage of symptomatic renal stones.

Authors:
Payam Mohammadinejad Andrea Ferrero David J Bartlett Ashish Khandelwal Roy Marcus John C Lieske Taylor R Moen Kristin C Mara Felicity T Enders Cynthia H McCollough Joel G Fletcher

Emerg Radiol 2021 Mar 1. Epub 2021 Mar 1.

Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA.

Purpose: To evaluate the ability of a semi-automated radiomic analysis software in predicting the likelihood of spontaneous passage of urinary stones compared with manual measurements.

Methods: Symptomatic patients visiting the emergency department with suspected stones in either kidney or ureters who underwent a CT scan were included. Patients were followed for up to 6 months for the outcome of a trial of passage. Maximum stone diameters in axial and coronal images were measured manually. Stone length, width, height, max diameter, volume, the mean and standard deviation of the Hounsfield units, and morphologic features were also measured using automated radiomic analysis software. Multivariate models were developed using these data to predict subsequent spontaneous stone passage, with results expressed as the area under a receiver operating curve (AUC).

Results: One hundred eighty-four patients (69 females) with a median age of 56 years were included. Spontaneous stone passage occurred in 114 patients (62%). Univariate analysis demonstrated an AUC of 0.83 and 0.82 for the maximum stone diameter determined manually in the axial and coronal planes, respectively. Multivariate models demonstrated an AUC of 0.82 for a model including manual measurement of maximum stone diameter in axial and coronal planes. The same AUC was found for a model including automatic measurement of maximum height and diameter of the stone. Further addition of morphological parameters measured automatically did not increase AUC beyond 0.83.

Conclusion: The semi-automated radiomic analysis of urinary stones shows similar accuracy compared with manual measurements for predicting urinary stone passage. Further studies are needed to predict clinical impacts of reporting the likelihood of urinary stone passage and improving inter-observer variation using automatic radiomic analysis software.

Download full-text PDF

 Source
http://dx.doi.org/10.1007/s10140-021-01915-4DOI Listing
March 2021

Publication Analysis

Top Keywords

radiomic analysis
20
stone passage
16
axial coronal
12
maximum stone
12
analysis software
12
stone
9
semi-automated radiomic
8
stone diameter
8
model including
8
automated radiomic
8
coronal planes
8
spontaneous passage
8
urinary stones
8
compared manual
8
demonstrated auc
8
urinary stone
8
spontaneous stone
8
measurement maximum
8
likelihood spontaneous
8
multivariate models
8

Keyword Occurance

Similar Publications

Optimising use of 4D-CT phase information for radiomics analysis in lung cancer patients treated with stereotactic body radiotherapy.

Authors:
Angela Davey Marcel van Herk Corinne Faivre-Finn Sean Brown Alan McWilliam

Phys Med Biol 2021 Apr 21. Epub 2021 Apr 21.

Division of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, United Kingdom., The University of Manchester, Manchester, Manchester, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND.

Purpose: 4D-CT is routine imaging for lung cancer patients treated with stereotactic body radiotherapy. No studies have investigated optimal 4D phase selection for radiomics. We aim to determine how phase data should be used to identify prognostic biomarkers for distant failure, and test whether stability assessment is required. Read More

View Article and Full-Text PDF
April 2021
Similar Publications

Current progress and quality of radiomic studies for predicting EGFR mutation in patients with non-small cell lung cancer using PET/CT images: a systematic review.

Authors:
Meilinuer Abdurixiti Mayila Nijiati Rongfang Shen Qiu Ya Naibijiang Abuduxiku Mayidili Nijiati

Br J Radiol 2021 Apr 21:20201272. Epub 2021 Apr 21.

Department of Radiology, The First People's Hospital of Kashi Area, Kashi, Xinjiang, China.

Objectives: To assess the methodological quality of radiomic studies based on positron emission tomography/computed tomography (PET/CT) images predicting epidermal growth factor receptor (EGFR) mutation status in patients with non-small cell lung cancer (NSCLC).

Methods: We systematically searched for eligible studies in the PubMed and Web of Science datasets using the terms "radiomics", "PET/CT", "NSCLC", and "EGFR". The included studies were screened by two reviewers independently. Read More

View Article and Full-Text PDF
April 2021
Similar Publications

Can radiomic analysis of a single-phase dual-energy CT improve the diagnostic accuracy of differentiating enhancing from non-enhancing small renal lesions?

Authors:
Yuqin Ding Mathias Meyer Peijie Lyu Francesca Rigiroli Juan Carlos Ramirez-Giraldo Kyle Lafata Siyun Yang Daniele Marin

Acta Radiol 2021 Apr 20:2841851211010396. Epub 2021 Apr 20.

Department of Radiology, Duke University Medical Center, Durham, NC, USA.

Background: The value of dual-energy computed tomography (DECT)-based radiomics in renal lesions is unknown.

Purpose: To develop DECT-based radiomic models and assess their incremental values in comparison to conventional measurements for differentiating enhancing from non-enhancing small renal lesions.

Material And Methods: A total of 349 patients with 519 small renal lesions (390 non-enhancing, 129 enhancing) who underwent contrast-enhanced nephrographic phase DECT examinations between June 2013 and January 2020 on multiple DECT platforms were retrospectively recruited. Read More

View Article and Full-Text PDF
April 2021
Similar Publications

Radiomics of Tumor Heterogeneity in Longitudinal Dynamic Contrast-Enhanced Magnetic Resonance Imaging for Predicting Response to Neoadjuvant Chemotherapy in Breast Cancer.

Authors:
Ming Fan Hang Chen Chao You Li Liu Yajia Gu Weijun Peng Xin Gao Lihua Li

Front Mol Biosci 2021 22;8:622219. Epub 2021 Mar 22.

Institute of Biomedical Engineering and Instrumentation, Hangzhou Dianzi University, Hangzhou, China.

Breast tumor morphological and vascular characteristics can be changed during neoadjuvant chemotherapy (NACT). The early changes in tumor heterogeneity can be quantitatively modeled by longitudinal dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), which is useful in predicting responses to NACT in breast cancer. In this retrospective analysis, 114 female patients with unilateral unifocal primary breast cancer who received NACT were included in a development ( = 61) dataset and a testing dataset ( = 53). Read More

View Article and Full-Text PDF
March 2021
Similar Publications

Noninvasive prediction of residual disease for advanced high-grade serous ovarian carcinoma by MRI-based radiomic-clinical nomogram.

Authors:
Haiming Li Rui Zhang Ruimin Li Wei Xia Xiaojun Chen Jiayi Zhang Songqi Cai Yong'ai Li Shuhui Zhao Jinwei Qiang Weijun Peng Yajia Gu Xin Gao

Eur Radiol 2021 Apr 16. Epub 2021 Apr 16.

Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163, China.

Objectives: To develop a preoperative MRI-based radiomic-clinical nomogram for prediction of residual disease (RD) in patients with advanced high-grade serous ovarian carcinoma (HGSOC).

Methods: In total, 217 patients with advanced HGSOC were enrolled from January 2014 to June 2019 and randomly divided into a training set (n = 160) and a validation set (n = 57). Finally, 841 radiomic features were extracted from each tumor on T2-weighted imaging (T2WI) and contrast-enhanced T1-weighted imaging (CE-T1WI) sequence, respectively. Read More

View Article and Full-Text PDF
April 2021
Similar Publications