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Related Concept Videos

Radiological Investigation II: MRI and Ventilation Perfusion Scan01:30

Radiological Investigation II: MRI and Ventilation Perfusion Scan

Description
Magnetic Resonance Imaging (MRI) and Ventilation Perfusion Scans are two radiological investigations that offer detailed diagnostic images of the body, particularly lung structures.
MRI
MRI uses magnetic fields and radiofrequency signals to distinguish between normal and abnormal tissues. This technology provides a more detailed diagnostic image than CT scans, enabling it to characterize pulmonary nodules, stage bronchogenic carcinoma, and evaluate inflammatory activity in...
Imaging Studies III: Computed Tomography01:27

Imaging Studies III: Computed Tomography

DefinitionComputed Tomography (CT) of the genitourinary (GU) tract is a non-invasive imaging modality that utilizes X-rays and computer processing to generate detailed cross-sectional images of the urinary system, encompassing the kidneys, ureters, bladder, and adjacent structures such as the adrenal glands.PurposeCT scans of the GU tract serve several diagnostic and therapeutic purposes, including:Diagnosis of Urinary Tract Diseases: Detects kidney stones, tumors, cysts, and congenital...
Radiological Investigation I: X-ray and CT01:30

Radiological Investigation I: X-ray and CT

Radiological investigations, including X-rays and computed tomography (CT) scans, are critical for diagnosing and evaluating various medical conditions. These imaging techniques provide valuable insights into the body's internal structures, aiding in the detection of abnormalities, assessment of disease progression, and development of treatment strategies. This article delves into two primary radiological investigations, chest X-rays and CT scans, outlining their purpose, procedures, and the...
Computed Tomography01:10

Computed Tomography

Tomography refers to imaging by sections. Computed tomography (CT) is a non-invasive imaging technique that uses computers to analyze several cross-sectional X-rays to reveal minute details about structures in the body.
The technique was invented in the 1970s and is based on the principle that as X-rays pass through the body, they are absorbed or reflected at different levels. In the technique, a patient lies on a motorized platform while a computerized axial tomography (CAT) scanner rotates...
Radiological Investigation III: Pulmonary Angiogram and PET Scan01:13

Radiological Investigation III: Pulmonary Angiogram and PET Scan

Radiological investigations are paramount in the diagnosis and management of various pulmonary diseases. Two essential investigations are the Pulmonary Angiogram and the Positron Emission Tomography (PET) Scan.
Pulmonary Angiogram
A Pulmonary Angiogram is an invasive procedure involving injecting a contrast medium through a catheter threaded into the pulmonary artery or the right side of the heart to visualize the pulmonary vasculature. Computed Tomography (CT) scans have mainly replaced this...

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Related Experiment Video

Updated: Jun 19, 2026

Guidelines and Experience Using Imaging Biomarker Explorer (IBEX) for Radiomics
10:17

Guidelines and Experience Using Imaging Biomarker Explorer (IBEX) for Radiomics

Published on: January 8, 2018

Radiomics-informed CT protocol optimization through feature-level trade-off analysis in a phantom study.

Mehrnoosh Karimipourfard1, David Stocker1, Christian Sommer1

  • 1ZHAW School of Engineering, 8401 Winterthur, Switzerland.

Physics in Medicine and Biology
|June 18, 2026
PubMed
Summary
This summary is machine-generated.

Optimizing CT protocols using radiomics improves feature reproducibility and low-contrast detectability. A new framework balances feature sensitivity and detectability for better quantitative CT analysis.

Keywords:
computed tomography (CT)low-contrast detectabilityphantom studyprotocol optimizationradiomic features

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Published on: July 29, 2013

Area of Science:

  • Medical Imaging
  • Radiology
  • Quantitative CT Analysis

Background:

  • Reproducibility of radiomic features in quantitative CT analysis is challenged by acquisition protocol variations.
  • Identifying robust features is crucial for reliable diagnostic performance.

Purpose of the Study:

  • To identify radiomic features predicting low-contrast detectability.
  • To quantify feature sensitivity to CT acquisition parameters.
  • To develop a framework for CT protocol optimization based on feature trade-offs.

Main Methods:

  • Extraction of 107 radiomic features from phantom scans across multiple CT protocols.
  • Assessment of feature robustness using coefficient of variation (CV) and intraclass correlation coefficient (ICC).
  • Development of a random forest model for detectability prediction and sensitivity analysis using Spearman's correlation.

Main Results:

  • ComBat harmonization significantly improved feature reproducibility.
  • First-order features demonstrated the highest predictive power for detectability (AUC = 0.94, accuracy = 0.90).
  • Texture and shape features showed varying sensitivities to protocol parameters and dose, respectively. A trade-off exists between detectability and feature sensitivity.

Conclusions:

  • A quantitative framework for radiomics-informed CT protocol optimization was established.
  • Moderate acquisition settings offer a more balanced and robust performance.
  • The findings provide a foundation for optimizing CT protocols in clinical settings.