Clinical Staging of Rectal Cancer

Computer-aided colorectal tumor classification in NBI endoscopy using local features

An early detection of colorectal cancer through colorectal endoscopy is important and widely used in hospitals as a standard medical procedure. During colonoscopy, the lesions of colorectal tumors on the colon surface are visually inspected by a Narrow Band Imaging (NBI) zoom-videoendoscope. By using the visual appearance of colorectal tumors in endoscopic images, histological diagnosis is presumed based on classification schemes for NBI magnification findings. In this paper, we report on the performance of a recognition system for classifying NBI images of colorectal tumors into three types (A, B, and C3) based on the NBI magnification findings. To deal with the problem of computer-aided classification of NBI images, we explore a local feature-based recognition method, bag-of-visual-words (BoW), and provide extensive experiments on a variety of technical aspects. The proposed prototype system, used in the experiments, consists of a bag-of-visual-words representation of local features followed by Support Vector Machine (SVM) classifiers. A number of local features are extracted by using sampling schemes such as Difference-of-Gaussians and grid sampling. In addition, in this paper we propose a new combination of local features and sampling schemes. Extensive experiments with varying the parameters for each component are carried out, for the performance of the system is usually affected by those parameters, e.g. the sampling strategy for the local features, the representation of the local feature histograms, the kernel types of the SVM classifiers, the number of classes to be considered, etc. The recognition results are compared in terms of recognition rates, precision/recall, and F-measure for different numbers of visual words. The proposed system achieves a recognition rate of 96% for 10-fold cross validation on a real dataset of 908 NBI images collected during actual colonoscopy, and 93% for a separate test dataset.

Complete pathological response to bevacizumab and chemoradiation in advanced rectal cancer

BACKGROUND

Localized rectal cancer responds well to 5-fluorouracil and radiation-based regimens. A phase I-II trial is currently testing the efficacy of adding bevacizumab, a VEGF-specific antibody, to standard chemoradiotherapy. The case presented here is a complete pathological response seen in a patient with extensive and locally invasive carcinoma after receiving this combined treatment.

INVESTIGATIONS

Physical examination, rectal ultrasound, PET-CT scan, laboratory tests, proctoscopic examination, chest radiograph, rectal forcep biopsies with immunohistochemistry, and protein and flow cytometric analyses.

DIAGNOSIS

Large, invasive, ultrasound stage T4 carcinoma of the rectum, which was positive for survivin.

MANAGEMENT

One 2-week cycle of bevacizumab alone, followed by 3 cycles of bevacizumab with continuous 5-fluorouracil infusion, and external-beam radiation therapy given 5 days per week to the pelvis, abdominoperineal resection with posterior vaginectomy, hysterectomy and bilateral salpingo-oophorectomy.