Microwave ablation of lung tumors: A probabilistic approach for simulation-based treatment planning.

PURPOSE: Microwave ablation (MWA) is a clinically established modality for treatment of lung tumors. A challenge with existing application of MWA, however, is local tumor progression, potentially due to failure to establish an adequate treatment margin. This study presents a robust simulation-based treatment planning methodology to assist operators in comparatively assessing thermal profiles and likelihood of achieving a specified minimum margin as a function of candidate applied energy parameters. METHODS: We employed a biophysical simulation-based probabilistic treatment planning methodology to evaluate the likelihood of achieving a specified minimum margin for candidate treatment parameters (i.e., applied power and ablation duration for a given applicator position within a tumor). A set of simulations with varying tissue properties was evaluated for each considered combination of power and ablation duration, and for four different scenarios of contrast in tissue biophysical properties between tumor and normal lung. A treatment planning graph was then assembled, where distributions of achieved minimum ablation zone margins and collateral damage volumes can be assessed for candidate applied power and treatment duration combinations. For each chosen power and time combination, the operator can also visualize the histogram of ablation zone boundaries overlaid on the tumor and target volumes. We assembled treatment planning graphs for generic 1, 2, and 2.5 cm diameter spherically shaped tumors and also illustrated the impact of tissue heterogeneity on delivered treatment plans and resulting ablation histograms. Finally, we illustrated the treatment planning methodology on two example patient-specific cases of tumors with irregular shapes. RESULTS: The assembled treatment planning graphs indicate that 30 W, 6 min ablations achieve a 5-mm minimum margin across all simulated cases for 1-cm diameter spherical tumors, and 70 W, 10 min ablations achieve a 3-mm minimum margin across 90% of simulations for a 2.5-cm diameter spherical tumor. Different scenarios of tissue heterogeneity between tumor and lung tissue revealed 2 min overall difference in ablation duration, in order to reliably achieve a 4-mm minimum margin or larger each time for 2-cm diameter spherical tumor. CONCLUSIONS: An approach for simulation-based treatment planning for microwave ablation of lung tumors is illustrated to account for the impact of specific geometry of the treatment site, tissue property uncertainty, and heterogeneity between the tumor and normal lung.

The first Smartphone application for microsurgery monitoring: SilpaRamanitor.

BACKGROUND: Postoperative monitoring of free flap tissue perfusion is vital. Devices available are expensive and complex to operate. Most surgeons rely on direct clinical observation. A monitoring system that is reliable, inexpensive, and easy to operate is needed. Using mobile phone technology, the authors developed and evaluated a new free flap monitoring system: SilpaRamanitor. METHODS: Software was developed for Android-operated mobile phones. Forty-two normal subjects were recruited to assess its effectiveness. Varying degrees of pressure were applied around the index finger to produce partial venous occlusion, partial arterial occlusion, complete venous occlusion, and complete arterial occlusion sequentially. Photographs of each subject's index and middle fingers were taken using the smartphone camera. To detect the abnormal perfusion presented on the index finger, the application was instructed to analyze photographs for color difference, with the unoccluded middle finger serving as the control. RESULTS: The sensitivity, specificity, accuracy, false-negative results, and false-positive results were 94, 98, 95, 6, and 1 percent, respectively. The accuracy of the application in grading occlusion severity was also evaluated. Thirty-nine cases (93 percent) were correctly identified as venous occlusion. The occlusion severity was correctly identified in 33 cases (85 percent). Likewise, for the 40 cases (95 percent) correctly identified as arterial occlusion, the method correctly categorized its severity in 33 cases (83 percent). CONCLUSIONS: The authors developed a new, accurate, and reliable diagnostic system for postoperative microsurgery monitoring using a smartphone application. SilpaRamanitor is inexpensive and easy to use, making it applicable in many microsurgical settings. CLINICAL QUESTION/LEVEL OF EVIDENCE: Diagnostic, IV.

Automatic definition of the central-chest lymph-node stations.

PURPOSE: Lung cancer remains the leading cause of cancer death in the United States. Central to the lung-cancer diagnosis and staging process is the assessment of the central-chest lymph nodes. This assessment requires two steps: (1) examination of the lymph-node stations and identification of diagnostically important nodes in a three-dimensional (3D) multidetector computed tomography (MDCT) chest scan; (2) tissue sampling of the identified nodes. We describe a computer-based system for automatically defining the central-chest lymph-node stations in a 3D MDCT chest scan. METHODS: Automated methods first construct a 3D chest model, consisting of the airway tree, aorta, pulmonary artery, and other anatomical structures. Subsequent automated analysis then defines the 3D regional nodal stations, as specified by the internationally standardized TNM lung-cancer staging system. This analysis involves extracting over 140 pertinent anatomical landmarks from structures contained in the 3D chest model. Next, the physician uses data mining tools within the system to interactively select diagnostically important lymph nodes contained in the regional nodal stations. RESULTS: Results from a ground-truth database of unlabeled lymph nodes identified in 32 MDCT scans verify the system's performance. The system automatically defined 3D regional nodal stations that correctly labeled 96% of the database's lymph nodes, with 93% of the stations correctly labeling 100% of their constituent nodes. CONCLUSIONS: The system accurately defines the regional nodal stations in a given high-resolution 3D MDCT chest scan and eases a physician's burden for analyzing a given MDCT scan for lymph-node station assessment. It also shows potential as an aid for preplanning lung-cancer staging procedures.