Role of Unenhanced Computed Tomography of the Chest in the Prediction of Anaemia: A Cross-sectional Study

Introduction: Anaemia is a common clinical condition. The detection of incidental findings on unenhanced Computed Tomography (CT) that predict the presence of anaemia may play a pivotal role in early diagnosis, treatment and prognosis. Aim: To assess the role of unenhanced CT thorax in predicting anaemia by determining the sensitivity and specificity of the Interventricular Septum Sign (IVS) and Aortic Rim Sign (ARS) in the prediction of anaemia. Materials and Methods: This was a cross-sectional study conducted on 300 patients who underwent High-resolution Computed Tomography (HRCT) of the thorax using a 128-slice CT scanner in the Department of Radiology, Nizam’s Institute of Medical Sciences, Hyderabad, Telangana, India, Nizams Institute of Medical Sciences, Hyderabad, from July 2022 to September 2022. An estimation of haemoglobin levels was performed from a peripheral blood sample within 24 hours of the scan and the diagnosis of anaemia was made based on World Health Organisation (WHO) guidelines of haemoglobin values according to age and gender. On imaging, the following parameters were analysed: the variables considered for each patient included age and gender, the presence or absence of ARS, the presence or absence of an IVS and the Hounsfield Units (HU) values of seven selected Regions of Interest (ROI) on each examination. Three ROIs were placed in the Left Ventricular (LV) cavity, three on the IVS and a single ROI was placed in the aorta at the same level. Mean, percentage, frequency and standard deviation were calculated. The Chi-square test was applied for statistical analysis and a p-value of <0.05 was considered significant. Results: Out of the total sample size of 300, 188 were males and 112 were females with the mean age of 47.16±19.77 years. The mean haemoglobin percentage in the study was 11.62±2.25 gm%. Approximately 195 (65%) out of 300 patients were found to be anaemic based on blood reports. Among them, the majority were diagnosed with moderate anaemia 109 (36.3%), followed by mild anaemia 76 (25.3%) and severe anaemia 10 (3.3%), respectively. The sensitivity of the dense IVS was 100% for severe anaemia, 75.6% for moderate anaemia and 55.3% for mild anaemia. In comparison, the aortic rim sign showed a sensitivity of 100% for severe anaemia, 86.5% for moderate anaemia and 67.69% for mild anaemia, with a specificity of 88.57%. Conclusion: The presence of an IVS on an unenhanced CT predicts the likelihood of underlying anaemia and suggests the need for further evaluation and timely management.

Authors

Publication Details

Journal
JOURNAL OF CLINICAL AND DIAGNOSTIC RESEARCH
Published
2024-12-01
DOI
https://doi.org/10.7860/jcdr/2024/73616.20361
Citations
1
Primary Topic
COVID-19 diagnosis using AI
Type
article
Field-Weighted Citation Impact
0.40
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Role of Unenhanced Computed Tomography of the Chest in the Prediction of Anaemia: A Cross-sectional Study

Rajani Thakur, Tarani Chetana Naga Sai, ankeerteerth Kendyala, Varigonda Mahidhar
1 citations
JOURNAL OF CLINICAL AND DIAGNOSTIC RESEARCH
COVID-19 diagnosis using AI
0.40
article

Role of Unenhanced Computed Tomography of the Chest in the Prediction of Anaemia: A Cross-sectional Study

Rajani Thakur, Tarani Chetana Naga Sai, ankeerteerth Kendyala, Varigonda Mahidhar
article en
1 citations

Abstract

Introduction: Anaemia is a common clinical condition. The detection of incidental findings on unenhanced Computed Tomography (CT) that predict the presence of anaemia may play a pivotal role in early diagnosis, treatment and prognosis. Aim: To assess the role of unenhanced CT thorax in predicting anaemia by determining the sensitivity and specificity of the Interventricular Septum Sign (IVS) and Aortic Rim Sign (ARS) in the prediction of anaemia. Materials and Methods: This was a cross-sectional study conducted on 300 patients who underwent High-resolution Computed Tomography (HRCT) of the thorax using a 128-slice CT scanner in the Department of Radiology, Nizam’s Institute of Medical Sciences, Hyderabad, Telangana, India, Nizams Institute of Medical Sciences, Hyderabad, from July 2022 to September 2022. An estimation of haemoglobin levels was performed from a peripheral blood sample within 24 hours of the scan and the diagnosis of anaemia was made based on World Health Organisation (WHO) guidelines of haemoglobin values according to age and gender. On imaging, the following parameters were analysed: the variables considered for each patient included age and gender, the presence or absence of ARS, the presence or absence of an IVS and the Hounsfield Units (HU) values of seven selected Regions of Interest (ROI) on each examination. Three ROIs were placed in the Left Ventricular (LV) cavity, three on the IVS and a single ROI was placed in the aorta at the same level. Mean, percentage, frequency and standard deviation were calculated. The Chi-square test was applied for statistical analysis and a p-value of <0.05 was considered significant. Results: Out of the total sample size of 300, 188 were males and 112 were females with the mean age of 47.16±19.77 years. The mean haemoglobin percentage in the study was 11.62±2.25 gm%. Approximately 195 (65%) out of 300 patients were found to be anaemic based on blood reports. Among them, the majority were diagnosed with moderate anaemia 109 (36.3%), followed by mild anaemia 76 (25.3%) and severe anaemia 10 (3.3%), respectively. The sensitivity of the dense IVS was 100% for severe anaemia, 75.6% for moderate anaemia and 55.3% for mild anaemia. In comparison, the aortic rim sign showed a sensitivity of 100% for severe anaemia, 86.5% for moderate anaemia and 67.69% for mild anaemia, with a specificity of 88.57%. Conclusion: The presence of an IVS on an unenhanced CT predicts the likelihood of underlying anaemia and suggests the need for further evaluation and timely management.

JOURNAL OF CLINICAL AND DIAGNOSTIC RESEARCH
Good health and well-being
Openalex Percentile: Top 32%
COVID-19 diagnosis using AI
0.40
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.