Optimal tumor coverage with different beam energies by IMRT, VMAT and TOMO: Effects on patients with proximal gastric cancer.

To compare the effects of different photon energies on radiation planning by intensity-modulated radiotherapy (IMRT), volumetric-modulated arc therapy (VMAT) and helical tomotherapy (TOMO) for proximal gastric cancer (PGC). Network analysis with microarray procession and gene ontology were used to identify the effect of radiotherapy (RT) on PGC. Then, we retrospectively analyzed 8 PGC patients after receiving irradiation with a prescribed dose of 50.4 Gy. The Pinnacle treatment planning system (TPS, V9.8) was used to generate IMRT and VMAT plans by using 6 or 10 MV. TOMO plans were calculated on the Tomotherapy Planning Station Hi-Art Version 4.2.3 workstation (Tomotherapy Incorporated, Madison, WI, USA). PGC is associated with high DNA repair ability. TOMO plan results in higher tumor coverage and a better conformity index than IMRT and VMAT. 10-MV VMAT yields better dosimetric quality of the gradient index than 6-MV VMAT (P = .012). TOMO was associated with a lower irradiation dose in the mean dose to the right kidney (P = .049), left kidney and heart than 6-MV IMRT and 6-MV VMAT. 6-MV IMRT plan presented a higher dose of lung Dmean (P = .017) than 10-MV IMRT. Additionally, VMAT, using a planning energy of 6 MV, was associated with a significantly higher left kidney Dmean (P = .018) and V10 (P = .036) than a planning energy of 10 MV. TOMO is a better RT plan not only for tumor coverage but also for sparing organs at risk. IMRT and VMAT plans with 10 MV beams are more suitable than 6 MV beams for PGC treatment.

Variations in dosimetric distribution and plan complexity with collimator angles in hypofractionated volumetric arc radiotherapy for treating prostate cancer.

PURPOSE: Hypofractionated radiotherapy can reduce treatment durations and produce effects identical to those of conventionally fractionated radiotherapy for treating prostate cancer. Volumetric arc radiotherapy (VMAT) can decrease the treatment machine monitor units (MUs). Previous studies have shown that VMAT with multileaf collimator (MLC) rotation exhibits better target dose distribution. Thus, VMAT with MLC rotation warrants further investigation. METHODS AND MATERIALS: Ten patients with prostate cancer were included in this study. The prostate gland and seminal vesicle received 68.75 and 55 Gy, respectively, in 25 fractions. A dual-arc VMAT plan with a collimator angle of 0° was generated and the same constraints were used to reoptimize VMAT plans with different collimator angles. The conformity index (CI), homogeneity index (HI), gradient index (GI), normalized dose contrast (NDC), MU, and modulation complexity score (MCSV ) of the target were analyzed. The dose-volume histogram of the adjacent organs was analyzed. A Wilcoxon signed-rank test was used to compare different collimator angles. RESULTS: Optimum values of CI, HI, and MCSV were obtained with a collimator angle of 45°. The optimum values of GI, and NDC were observed with a collimator angle of 0°. In the rectum, the highest values of maximum dose and volume receiving 60 Gy (V60 Gy ) were obtained with a collimator angle of 0°, and the lowest value of mean dose (Dmean ) was obtained with a collimator angle of 45°. In the bladder, high values of Dmean were obtained with collimator angles of 75° and 90°. In the rectum and bladder, the values of V60 Gy obtained with the other tested angles were not significantly higher than those obtained with an angle of 0°. CONCLUSION: This study found that MLC rotation affects VMAT plan complexity and dosimetric distribution. A collimator angle of 45° exhibited the optimal values of CI, HI, and MCSv among all the tested collimator angles. Late side effects of the rectum and bladder are associated with high-dose volumes by previous studies. MLC rotation did not have statistically significantly higher values of V60 Gy in the rectum and bladder than did the 0° angle. We thought a collimator angle of 45° was an optimal angle for the prostate VMAT treatment plan. The findings can serve as a guide for collimator angle selection in prostate hypofractionated VMAT planning.

Behavioral alterations following blood-brain barrier disruption stimulated by focused ultrasound.

The purpose of this study was to investigate the behavioral alterations and histological changes of the brain after FUS-induced BBB disruption (BBBD). Rats were behaviorally tested using the open field, hole-board, and grip strength tests from day 1 through day 32 after undergoing BBBD induced by FUS with either a mild or heavy parameter. In the open field test, we found an increase in center entries on day 1 and day 9 following heavy FUS treatment and a decrease in center entries at day 18 following mild FUS treatment. With regard to memory-related alterations, rats subjected to heavy FUS treatment exhibited longer latency to start exploring and to find the first baited hole. However, rats subjected to mild FUS treatment exhibited no significant differences in terms of memory performance or grip force. The obtained data suggest that heavy FUS treatment might induce hyperactivity, spatial memory impairment, and forelimb gripping deficits. Furthermore, while mild FUS treatment may have an impact on anxiety-related behaviors, the data suggested it had no impact on locomotor activity, memory, or grip force. Thus, the behavioral alterations following FUS-induced BBBD require further investigation before clinical application.

Automatic vertebral column extraction by whole-body bone SPECT scan.

Bone extraction and division can enhance the accuracy of diagnoses based on whole-body bone SPECT data. This study developed a method for using conventional SPECT for automatic recognition of the vertebral column. A novel feature of the proposed approach is a novel "bone graph" image description method that represents the connectivity between these image regions to facilitate manipulation of morphological relationships in the skeleton before surgery. By tracking the paths shown on the bone graph, skeletal structures can be identified by performing morphological operations. The performance of the method was evaluated quantitatively and qualitatively by two experienced nuclear medicine physicians. Datasets for whole-body bone SPECT scans in 46 lung cancer patients with bone metastasis were obtained with Tc-99m MDP. The algorithm successfully segmented vertebrae in the thoracolumbar spine. The quantitative assessment shows that the segmentation method achieved an average TP, FP, and FN rates of 95.1%, 9.1%, and 4.9%. The qualitative evaluation shows an average acceptance rate of 83%, where the data for the acceptable and unacceptable groups had a Cronbach's alpha value of 0.718, which indicated reasonable internal consistency and reliability.

Analysis of tumor vascularity using three-dimensional power Doppler ultrasound images.

Tumor vascularity is an important factor that has been shown to correlate with tumor malignancy and was demonstrated as a prognostic indicator for a wide range of cancers. Three-dimensional (3-D) power Doppler ultrasound (PDUS) offers a convenient tool for investigators to inspect the signals of blood flow and vascular structures in breast cancer. In this paper, a new computer-aided diagnosis (CAD) system for quantifying Doppler ultrasound images based on 3-D thinning algorithm and neural network is proposed. We extracted the skeleton of blood vessels from 3-D PDUS data to facilitate the capturing of morphological changes. Nine features including vessel-to-volume ratio, number of vascular trees, length of vessels, number of branching, mean of radius, number of cycles, and three tortuosity measures, were extracted from the thinning result. Benign and malignant tumors can therefore be differentiated by a score computed by a multilayered perceptron (MLP) neural network using these features as parameters. The proposed system was tested on 221 breast tumors, including 110 benign and 111 malignant lesions. The accuracy, sensitivity, specificity, and positive and negative predictive values were 88.69% (196/221), 91.89% (102/111), 85.45% (94/110), 86.44% (102/118), and 91.26% (94/103), respectively. The Az value of the ROC curve was 0.94. The results demonstrate a correlation between the morphology of blood vessels and tumor malignancy, indicating that the newly proposed method can retrieves a high accuracy in the classification of benign and malignant breast tumors.

Solid breast masses: neural network analysis of vascular features at three-dimensional power Doppler US for benign or malignant classification.

PURPOSE: To retrospectively evaluate the accuracy of neural network analysis of tumor vascular features at three-dimensional (3D) power Doppler ultrasonography (US) for classification of breast tumors as benign or malignant, with histologic findings as the reference standard. MATERIALS AND METHODS: This study was approved by the local ethics committee; informed consent was waived. Three-dimensional power Doppler US images of 221 solid breast masses (110 benign, 111 malignant) were obtained in 221 women (mean age, 46 years; range, 25-71 years). After narrowing down vessels to skeletons with a 3D thinning algorithm, six vascular feature values--vessel-to-volume ratio, number of vascular trees, total vessel length, longest path length, number of bifurcations, and vessel diameter-were computed. A neural network was used to classify tumors by using these features. Independent-samples t test and receiver operating characteristic (ROC) curve analysis were used. RESULTS: Mean values of vessel-to-volume ratio, number of vascular trees, total vessel length, longest path length, number of bifurcations, and vessel diameter were 0.0089 +/- 0.0073 (standard deviation), 26.41 +/- 14.73, 23.02 cm +/- 19.53, 8.44 cm +/- 10.38, 36.31 +/- 37.06, and 0.088 cm +/- 0.021 in malignant tumors, respectively, and 0.0028 +/- 0.0021, 9.69 +/- 6.75, 5.17 cm +/- 4.78, 1.68 cm +/- 1.79, 6.05 +/- 7.55, and 0.064 cm +/- 0.028 in benign tumors, respectively (P < .001 for all six features). Area under ROC curve (A(z)) values of the six features were 0.84, 0.87, 0.87, 0.82, 0.84, and 0.75, respectively. Accuracy, sensitivity, specificity, and positive and negative predictive values were 85% (187 of 221), 83% (96 of 115), 86% (91 of 106), 86% (96 of 111), and 83% (91 of 110), respectively, with A(z) of 0.92 based on all six feature values. CONCLUSION: Three-dimensional power Doppler US images and neural network analysis of features can aid in classification of breast tumors as benign or malignant.

Computer algorithm for analysing breast tumor angiogenesis using 3-D power Doppler ultrasound.

Angiogenesis provides blood supply for tumor expansion and also increases the opportunity for tumor cells to enter the blood or lymph circulation. Several proangiogenic factors as well as the contribution of the microenvironment to tumor-induced angiogenesis have been identified. Among these, vascular endothelial growth factor (VEGF) and the angiopoietin (Ang) family play a predominant role involved in the growth for endothelial cells. Tumor vessels are structurally and functionally abnormal because of an imbalance of these angiogenic regulators. In contrast to normal vessels, tumor vasculature is highly disorganized, tortuous and dilated, with uneven diameter and excessive branching. In other words, the morphologic features are likely to carry additional clues that, when used in conjunction with more established parameters, can improve the present diagnostic approaches. In our study, we present a new method that helps to capture the morphologic features from three-dimensional (3-D) power Doppler ultrasound (PDUS) images. After narrowing down the vessels into their skeletons using a 3-D thinning algorithm, we extracted seven features including vessel-to-volume ratio, number of vascular trees, number of bifurcation, mean of radius and three tortuosity measures, from the skeleton and applied a neural network to classify the tumors by using these features. In investigations into 221 solid breast tumors, including 110 benign and 111 malignant cases, the p values using the Student's t-test for all features were less than 0.05, indicating that the proposed features were deemed statistically significant. The A(Z) values for these seven features were 0.84, 0.87, 0.84, 0.75, 0.77, 0.79 and 0.69, respectively. The accuracy, sensitivity, specificity, and positive and negative predictive values were 80.09% (177 of 221), 80.18% (89 of 111), 80% (88 of 110), 80.18% (89 of 111) and 80% (88 of 110), respectively, with an A(Z) value of 0.89. The preliminary results show that the proposed method is feasible and has a good agreement with the diagnosis of the pathologists.

Characterization of spiculation on ultrasound lesions.

Spiculation is a stellate distortion caused by the intrusion of breast cancer into surrounding tissue. Its existence is an important clue to characterizing malignant tumors. Many successful mammographic methods have been proposed to detect tumors with spiculation. Traditional two-dimensional (2-D) ultrasound cannot easily find spiculations because spiculations normally appear parallel to the surface of the skin. Recently, three-dimensional (3-D) ultrasound has been gradually used in clinical applications and it has been proven to be useful in determining the architectural distortion or spiculation that surrounds a breast tumor. This paper aims to identify spiculation from 3-D ultrasonic volume data of a tumor found by a physician. In the proposed method, each coronal slice of volume data is successively extracted and then analyzed as a 2-D ultrasound image by the proposed spiculation detection method. First, in each horizontal slice, the modified rotating structuring element (ROSE) operation is used to find the central region in which spiculation lines converge. Second, the stick algorithm is used to estimate the direction of the edge of each pixel around the central region. A pixel whose edge points toward the central region is marked as a potential spiculation. Finally, the marked pixels are collected around the central region and their distribution is analyzed to determine whether spiculation is present. The 3-D test datasets were obtained using the Voluson 530 or 730, Kretztechnik, Austria. First, the proposed method was tested on 104 2-D typical coronal images (selected by an experienced physician) extracted from 52 3-D ultrasonic datasets. Finally, 225 3-D pathologically proven datasets were tested to evaluate the performance. Spiculations are more easily observed in the coronal view than in the other two views. That is, the 3-D ultrasound is a powerful tool for identifying spiculations. Furthermore, 16% (19/120) of benign cases and 90% (94/105) of malignant cases are detected as spiculations.