A primer on texture analysis in abdominal radiology

Horvat, Natally; Miranda, Joao; Homsi, Maria El; Peoples, Jacob; Long, Niamh M.; Simpson, Amber L.; Gian, Richard Kinh

doi:10.1007/s00261-021-03359-3

Cited by 13 publications

(5 citation statements)

References 83 publications

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“…Additionally, an effective means to interpret the vast and varied data derived from radiomics analysis is another key obstacle to the clinical implementation of radiomic models. Therefore, a balanced interpretation of results and an increased focus on interpretable models are essential to their successful integration into clinical practice[ 23 ]. Finally, manual segmentation is a time-consuming process and one of the most common limitations that should be managed with automatic or semiautomatic strategies before widespread use of radiomics tools.…”

Section: Radiomicsmentioning

confidence: 99%

“…Despite the increasing and encouraging results in the literature concerning radiomics in patients with HCC, there are challenges and limitations to be overcome before its clinical implementation, particularly related to reproducibility and repeatability, lesion segmentation, model overfitting, multidisciplinary acceptance, and multi-modal data integration[ 23 ].…”

Section: Future Directions Of Radiomics In Hccmentioning

confidence: 99%

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Current status and future perspectives of radiomics in hepatocellular carcinoma

Miranda¹,

Horvat²,

Fonseca³

et al. 2023

World J Gastroenterol

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Given the frequent co-existence of an aggressive tumor and underlying chronic liver disease, the management of hepatocellular carcinoma (HCC) patients requires experienced multidisciplinary team discussion. Moreover, imaging plays a key role in the diagnosis, staging, restaging, and surveillance of HCC. Currently, imaging assessment of HCC entails the assessment of qualitative characteristics which are prone to inter-reader variability. Radiomics is an emerging field that extracts high-dimensional mineable quantitative features that cannot be assessed visually with the naked eye from medical imaging. The main potential applications of radiomic models in HCC are to predict histology, response to treatment, genetic signature, recurrence, and survival. Despite the encouraging results to date, there are challenges and limitations that need to be overcome before radiomics implementation in clinical practice. The purpose of this article is to review the main concepts and challenges pertaining to radiomics, and to review recent studies and potential applications of radiomics in HCC.

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Section: Radiomicsmentioning

confidence: 99%

Section: Future Directions Of Radiomics In Hccmentioning

confidence: 99%

Current status and future perspectives of radiomics in hepatocellular carcinoma

Miranda¹,

Horvat²,

Fonseca³

et al. 2023

World J Gastroenterol

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“…Currently, AI and radiomics are increasingly being used to develop computer-aided detection systems [25]. Most of these AI-based computer-aided detection systems, however, use still images, and computer-aided detection for moving pictures in health is still in its early phase [26].…”

Section: Discussionmentioning

confidence: 99%

Quantifiable Measures of Abdominal Wall Motion for Quality Assessment of Cine-MRI Slices in Detection of Abdominal Adhesions

et al. 2023

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Abdominal adhesions present a diagnostic challenge, and classic imaging modalities can miss their presence. Cine-MRI, which records visceral sliding during patient-controlled breathing, has proven useful in detecting and mapping adhesions. However, patient movements can affect the accuracy of these images, despite there being no standardized algorithm for defining sufficiently high-quality images. This study aims to develop a biomarker for patient movements and determine which patient-related factors influence movement during cine-MRI. Included patients underwent cine-MRI to detect adhesions for chronic abdominal complaints, data were collected from electronic patient files and radiologic reports. Ninety slices of cine-MRI were assessed for quality, using a five-point scale to quantify amplitude, frequency, and slope, from which an image-processing algorithm was developed. The biomarkers closely correlated with qualitative assessments, with an amplitude of 6.5 mm used to distinguish between sufficient and insufficient-quality slices. In multivariable analysis, the amplitude of movement was influenced by age, sex, length, and the presence of a stoma. Unfortunately, no factor was changeable. Strategies for mitigating their impact may be challenging. This study highlights the utility of the developed biomarker in evaluating image quality and providing useful feedback for clinicians. Future studies could improve diagnostic quality by implementing automated quality criteria during cine-MRI.

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“…Given this potential, many studies have been conducted in recent years to explore the use of radiomics. Such studies involve a multistep pipeline [44,45], as described below (also, see Figure 5). Of note, the first two steps are applicable to all research studies involving radiological imaging, i.e., not only those involving radiomics.…”

Section: Pipeline Of Studies Using Radiomicsmentioning

confidence: 99%

CT Imaging Assessment of Pancreatic Adenocarcinoma Resectability after Neoadjuvant Therapy: Current Status and Perspective on the Use of Radiomics

Khasawneh,

Ferreira Dalla Pria,

Miranda

et al. 2023

JCM

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Pancreatic adenocarcinoma (PDAC) is the most common pancreatic cancer and is associated with poor prognosis, a high mortality rate, and a substantial number of healthy life years lost. Surgical resection is the primary treatment option for patients with resectable disease; however, only 10–20% of all patients with PDAC are eligible for resection at the time of diagnosis. In this context, neoadjuvant therapy has the potential to increase the number of patients who are eligible for resection, thereby improving the overall survival rate. For patients who undergo neoadjuvant therapy, computed tomography (CT) remains the primary imaging tool for assessing treatment response. Nevertheless, the interpretation of imaging findings in this context remains challenging, given the similarity between viable tumor and treatment-related changes following neoadjuvant therapy. In this review, following an overview of the various treatment options for PDAC according to its resectability status, we will describe the key challenges regarding CT-based evaluation of PDAC treatment response following neoadjuvant therapy, as well as summarize the literature on CT-based evaluation of PDAC treatment response, including the use of radiomics. Finally, we will outline key recommendations for the management of PDAC after neoadjuvant therapy, taking into consideration CT-based findings.

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A primer on texture analysis in abdominal radiology

Cited by 13 publications

References 83 publications

Current status and future perspectives of radiomics in hepatocellular carcinoma

Current status and future perspectives of radiomics in hepatocellular carcinoma

Quantifiable Measures of Abdominal Wall Motion for Quality Assessment of Cine-MRI Slices in Detection of Abdominal Adhesions

CT Imaging Assessment of Pancreatic Adenocarcinoma Resectability after Neoadjuvant Therapy: Current Status and Perspective on the Use of Radiomics

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