Knowledge Of Tumor Location Research Articles

Efficacy of a Novel Augmented Reality Navigation System Using 3D Computer Graphic Modeling in Endoscopic Transsphenoidal Surgery for Sellar and Parasellar Tumors

In endoscopic transsphenoidal skull base surgery, knowledge of tumor location on imaging and the anatomic structures is required simultaneously. However, it is often difficult to accurately reconstruct the endoscopic vision of the surgical field from the pre-surgical radiographic images because the lesion remarkably displaces the geography of normal anatomic structures. We created a precise three-dimensional computer graphic model from preoperative radiographic data that was then superimposed on a visual image of the actual surgical field and displayed on a video monitor during endoscopic transsphenoidal surgery. We evaluated the efficacy of this augmented reality (AR) navigation system in 15 consecutive patients with sellar and parasellar tumors. The average score overall was 4.7 [95% confidence interval: 4.58-4.82], which indicates that the AR navigation system was as useful as or more useful than conventional navigation in certain patients. In two patients, AR navigation was assessed as less useful than conventional navigation because perception of the depth of the lesion was more difficult. The developed system was more useful than conventional navigation for facilitating an immediate three-dimensional understanding of the lesion and surrounding structures.

Radiological Wheeler staging system: a retrospective cohort analysis to improve the local staging of prostate cancer with multiparametric MRI.

The knowledge of tumor location and extension can allow a modulated radical prostatectomy in order to minimize positive surgical margins and reduce functional morbidity after surgery in patients with prostate cancer (PCa). Multiparametric (mp) magnetic resonance imaging (MRI) could allow the assessment of tumor extension and of its relationship with external structures. Aim of this study is to propose a new radiological Wheeler (rW) staging system applied to mp-MRI, based on the pathologic staging system (pW) for the local assessment of PCa. This retrospective single-center multi-reader study included consecutive patients with PCa and preoperative mp-MRI, who underwent non-nerve sparing radical prostatectomy. Three radiologists reported on all examinations and classified each selected lesion according to imaging criteria following rW. Whole-mount histological sections were used as the reference standard. An experienced pathologist classified the extent of prostatic capsular invasion of each PCa according to the pW. Each histological section was scanned for comparison with mp-MRI findings. The rate of PCa correctly classified by radiologists using the pW was assessed. To evaluate the accuracy of mp-MRI in the discrimination between T2 and T3 PCa, the AUC was computed. One-hundred and five patients with a total of 195 PCa foci were included in the study. 130/195 tumors with a clear overlap between mp-MRI and surgical specimens were selected. The sensitivity of the most experienced reader was lower than that of the other two readers (48.6% vs. 68.6% and 62.9%, P>0.09) while specificity and PPV were higher (95.8% vs. 79.0% and 57.9%, P<0.001; 81.0% vs. 54.6% and 35.5%, P<0.041; respectively). The AUC values for the most and the intermediate experienced readers in the detection of extracapsular extension were in the range 0.72-0.74. The rW staging system has low accuracy in predicting each single pW class, while accuracy was over 80% for experienced readers in the identification of organ-confined (T2 stage class) tumors and non-organ confined cases (T3 stage class).

A novel dual calibration technique for microwave early breast tumour detection in MR images-based model

ABSTRACTA novel dual calibration confocal imaging technique is presented for microwave early breast tumour detection. The physical basis for microwave breast tumour detection is the contrast in electrical properties of normal tissues and tumours. Confocal imaging technique employs short pulse signals to illuminate breast model from a number of antennas over skin surface, and backscattered energy is collected to analyse the internal structure. In this research, a novel calibration technique is developed to remove artefacts and amplify the tumour responses, and a doubling of tumour response data is obtained without the prior knowledge of tumour location. The internal structure of the breast model is built based on magnetic resonance (MR) images, and the proposed method is verified through computer simulations. The imaging results show that a small tumour with 3 millimetres in diameter has been successfully detected using this method. Though the tumour response is weaker than the residual artefact in small tumour scene, the method can keep noise pixels from overlapping and improve its robustness. Details steps of the method are discussed in this research.

TRANSRECTAL SONOELASTOGRAPHY IN THE DETECTION OF PROSTATE CANCERS: A META-ANALYSIS

Imaging of prostate cancer is becoming more important as new therapy options, such as focal ablation, gain in popularity. Precise knowledge of tumour location within the prostate and of the aggressiveness of this heterogeneous and multifocal tumour are key requirements for both established and new therapies and techniques. However, diagnosis still relies on biopsy results which might underestimate [ 1 ] tumour aggressiveness and/or bilateral disease.

SU-FF-J-46: A Probabilistic Method for Online Treatment Plan Modification

Purpose: To develop an IMRT treatment planning method that accounts for increased knowledge of tumor and normal tissue location gained from inter- or intra-fractional imaging. Method and Materials: Knowledge of tumor location in each fraction or sub-fraction is represented by a probability density function (pdf), p(n,n′,t), that describes the probability that a voxel at index n in the planning image will be located at voxel n′ at a later time t. The pdf is changing as the new information becomes available. A set of beam profiles for each fraction or sub-fraction is then obtained by minimizing the quadratic objective function by accounting for probabilistic nature of the beamlet dose distribution: 〈d〉n,t=∑n,dn,p(n,n′,t). in each fraction. This optimization problem is set with the intention that the beamlets that have the highest risk of missing the tumor will not be delivered until adequate knowledge of tumor location becomes available. We apply this method to a case of a disk-shaped tumor inside a disk-shaped phantom with a tomotherapy beam geometry. Results: The method proved to deliver more conservative dose distributions at the beginning of treatment than at the end for both inter- and intra-fractional cases. For early fractions and sub-fractions, low-risk doses were delivered to regions where the probability was high that the tumor would be present during the treatment. As knowledge of tumor location improved, the remaining dose at the periphery of the tumor was filled-in. Conclusion: We showed that incorporating increased knowledge about tumor and normal tissue location, obtained by repeatitive on-line imaging leads to superior treatment plans.