Highlights•

Abdominal CT is valuable for the diagnosis and staging of colorectal cancer.

•

The rectum was the most common site, often showing annular wall thickening.

•

An unhealthy diet is seen in most patients with CRC.

•

Hematochezia and constipation were the leading clinical presentations.

•

Alcohol use and low education level were significantly associated with CRC.

AbstractBackground

Colorectal cancer (CRC) is the second-leading cause of cancer deaths worldwide, and its incidence is rising in developing countries. In resource-limited settings, abdominal CT scans are commonly used to detect and stage CRC before treatment. This study examined CT scan results and associated factors in patients suspected of having CRC at Muhimbili National Hospital between August 2019 and February 2020.

Methodology

This was a cross-sectional, hospital-based study of 60 patients with suspected CRC who were referred to our centre for abdominal CT. Clinical characteristics, abdominal CT findings, and histology results were recorded in a structured questionnaire. Categorical and numerical data were analyzed using frequency distribution tables, and the Chi-square (X2) test was used to assess the association between the independent and dependent variables. Multivariate logistic regression was performed to evaluate independent associations after adjusting for age and sex.

Results

Most participants were over 40 years old (more females than males, 1.4:1). An unhealthy diet was common (71.7%). Main symptoms: constipation (61.7%) and hematochezia (58.3%). Among 60 suspected patients, colorectal tumours were confirmed in 56.7%, mostly rectal (26.7%), often with annular thickening (46.7%) and heterogeneous enhancement (43.3%). Abdominal CT showed good performance (sensitivity 88.9%, specificity 91.7%, accuracy 90.0%). Significant associations were found with lower education (p = 0.04), alcohol use (p = 0.02), and hematochezia (p = 0.03). These associations should be considered exploratory, given the small sample size and multiple comparisons performed.

Conclusion

CRC is present in the majority of patients with suspected cases who follow an unhealthy diet, occurring most commonly in the rectum and presenting as annular wall thickening on abdominal CT. This association is also linked to educational attainment and alcohol consumption.

Graphical abstractDownload: Download high-res image (300KB)Download: Download full-size imageKeywords

Rectal cancer

;

Resource-limited settings

;

Tanzania

;

Risk factors

;

Colorectal cancer

;

Abdominal computed tomography

;

Imaging findings

Introduction

Colorectal cancer (CRC) is the most fatal gastrointestinal cancer and the second leading cause of death related to cancer diseases worldwide [1]. In Africa, CRC is among the four most common types of cancer; a study conducted in Zambia, Southern Africa, reported an incidence rate of CRC to be 10.9 per 100,000 cancer patients [2]. Besides, a retrospective study conducted in Tanzania reported a 6-fold increase in the incidence of CRC. Previous studies have associated the development of colorectal cancer with an increase in age, poor dietary habits, being overweight/obese, lack of education, alcohol consumption, smoking, and family history of CRC in the first/second degree relative [3]. The introduction of computed tomography (CT) scans as a modern diagnostic technique has facilitated the development of management plans for patients with CRC [4].

An abdominal CT scan helps assess tumours, characterize their location, soft-tissue nature, and relationship to adjacent organs. This imaging technique is helpful in the diagnosis and staging of cancer patients, as well as in assessing the response to treatment, due to its ability to demonstrate tumor invasion both locally and in distant organs. When reading Abdominal CT-scan images, the following key issues are observed: tumor location, morphological type, pattern of wall thickening, enhancement pattern, fatty infiltration and lymph node invasion. However, the diagnostic effectiveness (accuracy) of CT scanning in diagnosing CRC compared with histopathology was moderate (77%), with 96% specificity (ability to reject those without CRC). Studies have reported that Abdominal CT scan findings depend on the knowledge and experience of the radiologist(s), the quality of the CT scan machines, the size of the tumor, and the soft tissue characteristics [4,5].

Understanding the patterns of CT scan findings and associated factors among CRC patients in a resource-limited setting, such as ours, is crucial to improving diagnosis, treatment, and monitoring. Therefore, this study aimed to describe the patterns of CT scan findings and associated factors among patients suspected of having CRC at Muhimbili National Hospital (MNH), Tanzania.

Organizational accessGet full-text access by signing in with your organisationSection snippetsStudy design

This was a hospital-based cross-sectional study conducted over 6 months from August 2019 to February 2020.

Study setting

The study was conducted at the Department of Radiology in Muhimbili National Hospital. The department has a database assessment room with computers and several imaging platforms. In this setting, patients referred for abdominal CT were prepared, and imaging was performed according to protocol. The results were interpreted and reviewed by a senior radiologist.

Study area

The study was conducted in the

Socio-demographic and clinical characteristics of colorectal cancer

Table 3 shows that out of 60 patients who were suspected to have colorectal cancer, 80% were aged above 40 years, mostly being females by 58.3%, with more than half of the participants (51.7%) being urban residents, and 75% of the participants had completed primary and secondary school education.

Constipation was the most common clinical symptom reported in 61.7% of the study population, followed by hematochezia and vomiting, which were observed in only one participant in the study, as seen in

Discussion

Our study aimed to determine the magnitude and factors associated with colorectal cancer among patients attending Muhimbili National Hospital. This step is important for providing the necessary information to improve the diagnosis and treatment of colorectal cancer. Our findings are based on symptomatic patients referred to a major hospital for CT, where CRC was confirmed in over half (56.7%). The common rectal location (26.7%) may reflect referral patterns, as rectal symptoms (such as

Study limitations

This study was conducted over a six-month period at a single tertiary referral hospital and utilized a convenience sample of 60 patients. As participants were referred for CT imaging based on clinical suspicion of colorectal cancer, a degree of selection bias is likely, and the observed frequency of colorectal cancer and related imaging features may not be representative of the general population. In addition, referral patterns may have resulted in an overrepresentation of patients with

Conclusion and recommendations

This single-center study provides insight into the patterns of colorectal cancer among symptomatic patients in Tanzania. The predominance of rectal involvement, the association with dietary factors, the diagnostic contribution of CT imaging, and the observed links with alcohol use, lower educational attainment, and rectal bleeding reflect clinically relevant features commonly encountered in routine practice.

To achieve a more comprehensive understanding of colorectal cancer at the national

CRediT authorship contribution statement

Mwajabu Athman Saleh: Writing – original draft, Software, Resources, Project administration, Methodology, Investigation, Funding acquisition, Formal analysis, Data curation, Conceptualization. Revelian Iramu: Writing – review & editing, Supervision. Ramadhani Kazema: Writing – review & editing, Supervision. Lulu Fundikira: Writing – review & editing.

Funding sources

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Conflict of interest statement

The authors declare that they have no known competing financial interests or personal relationships that could be seen as influencing the work reported in this paper.

Acknowledgement

The authors sincerely thank Steven Charema and Lackson David for their support in data analysis and interpretation of the findings, as well as the team at Muhimbili National Hospital for their ongoing assistance during data collection for this research.

References (26)E.J. Kuipers et al.Colorectal cancer

Nat. Rev. Dis. Prim.

(2015 Dec 5)

A.W. Asombang et al.Descriptive analysis of colorectal cancer in Zambia, Southern Africa using the national cancer disease hospital database

Pan. Afr. Med. J.

(2018)

L.K. Katalambula et al.Pattern and distribution of colorectal cancer in Tanzania: a retrospective chart audit at two national hospitals

J. Cancer Epidemiol.

(2016)

B. Baeßler et al.Imaging procedures for colorectal cancer

Visc. Med.

(2016 Jun)

Yen-Kung Chen et al.Application of PET and PET/CT imaging for cancer screening

Anticancer Res.

(2004)

A. Graham et al.Correspondence to: estimating the incidence of colorectal cancer in Sub-Saharan Africa: a systematic analysis

J. glo

(2012)

B. Baran et al.Difference between left-sided and right-sided colorectal cancer: a focused review of literature

Gastroenterol. Res.

(2018 Aug)

M. Suh et al.Socioeconomic disparities in colorectal cancer screening in Korea

Medicine (Baltimore)

(2015 Sep)

J.J. Granados-Romero et al.Colorectal cancer: a review

Int. J. Res. Med. Sci.

(2017 Oct 27)

J. Hang et al.The joint effects of lifestyle factors and comorbidities on the risk of colorectal cancer: a large Chinese retrospective case-control studyW.H. Tsong et al.Cigarettes and alcohol in relation to colorectal cancer: the Singapore Chinese health study

Br J. Cancer

(2007 Mar 12)

N. Khanal et al.Colorectal carcinoma and emerging targeted therapies

Fed Pract.

(2015 Aug)

A. Jemal et al.

Global Cancer Stat.

(2011)

View full text

Recommended articlesNo articles found.

© 2026 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.