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Characterization of adnexal masses using multidetector contrast-enhanced CT scan – recognising common pitfalls that masquerade as ovarian cancer
Suppiah, S1, Kamal, S.H2, Mohd Zabid, A.Z3, Abu Hassan, H4.
Adnexal masses are growths that form near the uterus; the majority being ovarian tumours. Although
there is no established population-screening tool for detecting ovarian cancer, ultrasound and contrastenhanced
computed tomography (CECT) are useful imaging tools in the management of adnexal masses.
Our study aimed to determine the characteristics of malignant adnexal masses on CECT scan and to
describe common pitfalls in diagnosis of ovarian cancer when interpreting images. We also determined the
sensitivity and specificity of diagnosing ovarian cancer using CECT. A retrospective study was conducted
in Hospital Serdang using data from all patients who underwent CECT scan and detected with adnexal
masses, and had histopathological examination correlation from January 2013 until January 2015. Out of
the 64 cases analysed; the majority of malignant lesions were serous carcinoma of the ovary (40%). The
CECT scan characteristics, tumour consistency of mixed type, presence of wall enhancement, septations,
ascites and peritoneal nodule/omental caking were significantly associated with ovarian malignancy
(p<0.05). The sensitivity, specificity, PPV and NPV of CECT scan was 95.45%, 71.43%, 63.63% and
96.77% respectively. Contrast-enhanced computed tomography scan is a good, non-invasive method
to diagnose ovarian cancer. By using a pro-forma document as a guide, good results can be achieved to
help differentiate between benign and malignant lesions. Nevertheless, caution needs to be exercised in
interpreting cases that mimic features of malignancy.
Affiliation:
- Universiti Putra Malaysia, Malaysia
- Universiti Putra Malaysia, Malaysia
- Universiti Putra Malaysia, Malaysia
- Universiti Putra Malaysia, Malaysia
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Indexation |
Indexed by |
MyJurnal (2021) |
H-Index
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3 |
Immediacy Index
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0.000 |
Rank |
0 |
Indexed by |
Scopus 2020 |
Impact Factor
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CiteScore (1.1) |
Rank |
Q3 (Agricultural and Biological Sciences (all)) Q3 (Environmental Science (all)) Q3¬¬- (Computer Science (all)) Q3 (Chemical Engineering (all)) |
Additional Information |
SJR (0.174) |
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