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We presented and evaluated two deformable model-based approaches, region plus contour deformation (RPCD), and level sets to extract metastatic cervical nodal lesions from pretreatment T2-weighted magnetic resonance images. The RPCD method first uses a region deformation to achieve a rough boundary of the target node from a manually drawn initial contour, based on signal statistics. After that, an active contour deformation is employed to drive the rough boundary to the real node-normal tissue interface. Differently, the level sets move a manually drawn initial contour toward the desired nodal boundary under the control of the evolvement speed function, which is influenced by image gradient force. The two methods were tested by extracting 33 metastatic cervical nodes from 18 nasopharyngeal carcinoma patients. Experiments on a basis of pixel matching to reference standard showed that RPCD and level sets achieved averaged percentage matching at 82-84% and 87-88%, respectively. In addition, both methods had significantly lower interoperator variances than the manual tracing method. It was suggested these two methods could be useful tools for the evaluation of metastatic nodal volume as an indicator of classification and treatment response, or be alternatives for the delineation of metastatic nodal lesions in radiation treatment planning.

The tongue enables taste and plays a critical role in formation of food bolus and deglutition. The tongue is also crucial for speech and the earliest sign of tongue paresis is a change in the quality of speech. Given the importance of the tongue, tongue carcinoma should be accurately staged in order to optimise treatment options and preserve organ function. The intent of this review is to familiarize radiologists with the pertinent anatomy of the tongue and the behaviour of tongue carcinoma so as to map malignant infiltration accurately., ((c) International Cancer Imaging Society.)

Purpose: To measure nasopharyngeal carcinoma tumor volume based on magnetic resonance images using a validated semiautomated measurement methodology and correlate tumor volume with TNM T classification., Methods and Materials: The study population consisted of 206 consecutive nasopharyngeal carcinoma patients who had magnetic resonance imaging staging scans. Tumor volume was measured using a semisupervised knowledge-based fuzzy clustering algorithm. Patients were divided into 4 groups according to TNM T classification. The difference in tumor volumes among the various TNM T-classification groups was examined., Results: The mean tumor volume in each T-classification group is as follows: T1, 8.6 mL +/- 5.0 (standard deviation [SD]); T2, 18.1 mL +/- 8.1 (SD); T3, 25.8 mL +/- 14.1 (SD); and T4, 36.2 mL +/- 18.9 (SD). The mean tumor volume increased significantly with advancing T classification (p < 0.0001). Tumor volume in a more advanced T group was significantly larger than that in an adjacent early T group (p < 0.01)., Conclusion: Validated magnetic resonance imaging-based tumor volume shows positive correlation between tumor volume and advancing T-classification groups. It may be possible to incorporate tumor volume as an additional prognostic factor into the existing TNM system.

Tumor volume was measured in 69 patients with nasopharyngeal carcinoma. On transverse nonenhanced T1-weighted and gadolinium-enhanced T1-weighted magnetic resonance (MR) images, segmentation was performed by means of seed growing and knowledge-based fuzzy clustering methods. Data were compared with those collected with the manual tracing method and analyzed for interoperator variance and interobserver reliability. There was no significant difference between the volumes determined with manual tracing or semiautomated segmentation (P >.05). On the volume level, Pearson correction coefficients were close for both the manual tracing and semiautomated methods. Significant differences in interoperator variance existed between the two methods on the pixel level (P <.05). Compared with manual tracing, the semiautomated method helped reduce interoperator variance and obtain higher interobserver reliability. Findings in the current study validate the use of semiautomated volume measurement methods for nasopharyngeal carcinoma., (Copyright RSNA, 2004)

The prerequisite for the correct diagnosis and accurate delineation of skull base lesions is familiarity with the complex anatomy of the skull base. Imaging plays a central role in the management of skull base disease because this region is often difficult to evaluate clinically. CT and MR imaging are complementary; they are often used together to demonstrate the full disease extent. This article focuses on the critical anatomy of theskull base and how this knowledge contributes to accurate disease assessment.

Nasopharyngeal carcinoma (NPC) is the most common epithelial tumor of the nasopharynx. Radiation therapy is the mainstay of treatment while surgery or chemotherapy is used in selected patients. NPC usually regresses after 3 months of radiation therapy. Nonetheless, a residual mass may be present following treatment and this does not necessarily indicate viable tumor. Imaging studies are often used in conjunction with clinical examination following treatment. While computed tomography (CT) is widely used due to its greater availability, less expensive, and less time consuming, MR imaging is now becoming the preferred modality. MR imaging is more capable than CT for identifying mature scarring, tumor recurrence and postradiation complications. However, MR imaging cannot reliably demonstrate mucosal recurrence or differentiate tumor recurrence from postradiation tissue changes. Familiarity with the imaging findings of various posttreatment changes, tumor recurrence and postradiation complications is essential for management of NPC. Comparison with previous images or imaging-guided biopsy facilitates definitive diagnosis.

This article reports on the use of both magnetization-transfer (MT) imaging and 1H-MR spectroscopy in two cases of bilateral temporal-lobe changes after radiation therapy for nasopharyngeal carcinoma. In the first case, the following patterns were noted: (i) although the temporal lobes appeared relatively normal on T2-weighted MR imaging, corresponding MT imaging clearly showed signal abnormalities (decreased MT effect) consistent with alterations in macromolecular structure; and (ii) concomitant strongly elevated choline on 1H-MR spectroscopy was observed, and this is associated with metabolic changes in cell membranes. The second case presented similar characteristics. In addition, there was an increased lactate signal and T2 signal changes in keeping with established oedema. Both MT and proton-spectroscopic findings were consistent with postulated pathophysiological features of radiation injury, but their specificity for this condition remains unclear. Magnetization-transfer imaging, and possibly 1H-MR spectroscopy, might be sensitive techniques for the early detection of late radiation injury.

We presented and evaluated two deformable model-based approaches, region plus contour deformation (RPCD), and level sets to extract metastatic cervical nodal lesions from pretreatment T2-weighted magnetic resonance images. The RPCD method first uses a region deformation to achieve a rough boundary of the target node from a manually drawn initial contour, based on signal statistics. After that, an active contour deformation is employed to drive the rough boundary to the real node–normal tissue interface. Differently, the level sets move a manually drawn initial contour toward the desired nodal boundary under the control of the evolvement speed function, which is influenced by image gradient force. The two methods were tested by extracting 33 metastatic cervical nodes from 18 nasopharyngeal carcinoma patients. Experiments on a basis of pixel matching to reference standard showed that RPCD and level sets achieved averaged percentage matching at 82–84% and 87–88%, respectively. In addition, both methods had significantly lower interoperator variances than the manual tracing method. It was suggested these two methods could be useful tools for the evaluation of metastatic nodal volume as an indicator of classification and treatment response, or be alternatives for the delineation of metastatic nodal lesions in radiation treatment planning. [ABSTRACT FROM AUTHOR]

Background: Tongue cancers are staged by the American Joint Committee on Cancer and the Union Internationale Contre le Cancer TNM staging systems. Cancer, however, evolves in a 3-D plane. Hence, using the largest tumour diameter will not reflect total cancer volume. We aim to evaluate the use of tongue cancer tumour volume (Tv) as a prognostic predictor of disease recurrence and survival. Methods: The study is a retrospective analysis of patients in Singapore General Hospital who underwent complete resection for histologically proven tongue carcinoma from 2000 to 2002. The Tv was measured on staging T2-weighted magnetic resonance imaging datasets by semiautomated methods. Results: Seventeen patients with a median follow-up duration of 57.9 months were studied. A wide range of volumes was noted in each T stage. The median time to relapse was 8.6 months for those with Tv ≥ 13 cc but was not achieved for those with Tv < 13 cc. The hazard ratio comparing Tv ≥13 cc versus <13 cc is 9.02 (95% confidence interval (CI) 1.70–47.94, P = 0.014). Of the seven deaths reported, five patients had Tv ≥ 13 cc. The median overall survival was 15.8 months for those with Tv ≥ 13 cc but was not achieved for those with Tv < 13 cc. The hazards of death for Tv ≥ 13 cc was 3.91 times that of Tv < 13 cc (95%CI 0.86–17.86, P = 0.078). Conclusion: Tongue cancer Tv measurement allows a more refined and accurate assessment of tumour status. This can be a possible prognostic indicator and be used in a novel staging method for the future. [ABSTRACT FROM AUTHOR]