Thirty-seven patients with newly diagnosed or treated sarcomas had 47 sets of sequential thallium scans (TS) followed by three-phase bone scan (TPBS) on the same day. The diagnosis in all patients was verified by biopsy (n = 40) or long-term follow-up studies (n = 7). The sensitivity, specificity, and accuracy of TS and TPBS in detecting sarcomatous lesions was calculated: TS sensitivity was 88%, specificity 69%, and accuracy 83%; blood flow (BF) and blood pool (BP) sensitivity was 91%, specificity 54%, and accuracy 81%; delayed bone scan (DB) sensitivity was 88%, specificity 38%, and accuracy 74%. In 17 studies the flow and blood pool parts of the TPBS and TS demonstrated the soft tissue component of sarcomas, which would have been missed if only the delayed bone scan had been performed. The TS lesion to normal tissue ratio alone was not very helpful in differentiating sarcomas from benign conditions because some benign lesions are highly cellular and vascular while some malignant lesions, such as chondrosarcoma, have poor vascularity and a less cellular chondroid matrix. However, when the thallium ratio was correlated with similar ratios calculated from the BP image, it was found that if the TS lesion to normal tissue ratio exceeded the BP lesion to normal tissue ratio (12 patients), the specificity for detecting sarcomatous lesions was 100%. Nevertheless, the reverse was not true. The positive predictive value of this observation was 100% and the negative predictive value was 37%.
We propose to develop a portable, handheld, noninvasive solution for accurate screening and real-time monitoring of traumatic brain injury (BI) in ambulatory/emergency response scenarios. A layered sensing concept that unifies alternate modalities such as a) ultrasound (US), b) near infrared spectroscopy (NIRS), c) tonometry (IOP), to predict BI, their severity and mode of recommendations for emergency medical service (EMS) personnel is offered. Specifically, we aim to determine i) novel 3D morphometric parameters of optic nerve sheath that can predict elevated intracranial pressure from US data, ii) incidence of intracranial hematomas using NIRS, iii) intraocular pressure using a tonometer, iv) cerebral blood flow and blood oxygen content using other auxiliary non-invasive sensing modes and v) finally provide a sensor fused outcome of all i)-iv) combined. This decision-support system (DSS) will improve BI detection by incorporating accurate on-site measurements that accounts for individual baseline variations and monitors temporal manifestation of the injury. The data collected and the preliminary analysis performed by the DSS will be sent to an emergency department (ED) physician stationed at a nearby trauma center via a wireless 3G network. Based on the available bandwidth, either all the data including the preliminary analysis (US video, images, 1D measurements, etc) or only the refined signals (feature vector extracted during screening) along with the DSS diagnosis will be sent to the physician. If the DSS determined output is agreeable to the physician then the screening can be terminated and
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