Role of Cross Sectional Imaging Modalities in the Diagnosis and Characterization of Colonic Masses

Обзор

Colonic masses are frequently encountered in clinical practice and can be benign or malignant. Accurate characterization is crucial for optimal management. Traditional imaging techniques such as colonoscopy remain the gold standard; however, multi-modality imaging-including computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET)-has gained importance. Colorectal cancer (CRC) is one of the most commonly diagnosed malignancies worldwide, ranking as the third most common cancer and the second leading cause of cancer-related mortality. According to the Global Cancer Observatory (GLOBOCAN), in 2020, there were approximately 1.9 million new cases of CRC and over 930,000 deaths. The incidence varies geographically, with higher rates in developed countries due to lifestyle factors, dietary habits, and genetic predispositions. Early detection through screening and imaging plays a pivotal role in reducing morbidity and mortality. (Sung et al., 2021). Recent studies have demonstrated that multi-modality imaging improves diagnostic confidence in colonic lesions. CT colonography has been shown to have a sensitivity of approximately 96% for detecting polyps ≥10mm (Pickhardt et al., 2019). MRI provides superior soft tissue contrast, aiding in local tumor staging (Beets-Tan et al., 2020). These advancements underline the importance of integrating multiple imaging techniques for comprehensive colonic mass evaluation. Staging of colorectal cancer is crucial for treatment planning and prognosis assessment. The TNM (Tumor, Node, Metastasis) staging system is widely used: * T (Tumor size and invasion): Ranges from T1 (tumor confined to the mucosa) to T4 (tumor invading adjacent structures). * N (Lymph node involvement): N0 (no nodal involvement) to N2 (extensive nodal spread). * M (Distant metastases): M0 (no metastases) to M1 (presence of metastases). Imaging plays a fundamental role in staging. CT is the primary modality for detecting lymph node involvement and distant metastases (Liu et al., 2020). MRI, particularly with diffusion-weighted imaging, provides superior soft-tissue contrast for local staging, especially in rectal cancer (Maas et al., 2019). Colonoscopy with histopathological biopsy remains the gold standard for diagnosing colonic masses. It allows direct visualization, biopsy sampling, and polyp removal if necessary. This study aims to evaluate the diagnostic accuracy and clinical utility of these imaging modalities in detecting and differentiating colonic masses.

Вмешательства

• Диагностический тест ROLE OF Cross sectional imaging modalities in the diagnosis and characterization of colonic masses
  Study tools (in detail, e.g., lab methods, instruments, steps, chemicals, …): * CT Scan: To evaluate mass morphology, size, and lymph node involvement. * MRI: To assess tissue composition, characterization and diffusion restriction. * Colonoscopy and Biopsy: Gold standard reference to assess the diagnostic accuracy for different

Первичные конечные точки

• • Accuracy, sensitivity, and specificity of imaging modalities in detecting & diagnosis of colonic masses [Срок оценки: two years]

Критерии участия

Критерии включения

• Adults (>18 years) referred for imaging due to suspected colonic mass. Histopathological confirmation is available.

Критерии исключения

• • Patients with contraindications to contrast imaging as sensitivity to contrast media or renal impairment

• Patient with contraindication for MRI e.g patients having a devices with Para magnetic effect e.g pacemakers and claustrophobia
• Patients with prior colorectal cancer diagnosis or surgical intervention

Критерии приведены из реестра в оригинале (на английском). Окончательную оценку соответствия проводит исследовательский центр.

Дизайн исследования

Модель наблюдения

Другое

Центры проведения

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Идентификаторы

NCT: NCT06939075 · Diagnosis of colonic masses

Первоисточники (государственные реестры)

• ClinicalTrials.gov (NIH, США)

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