Validation of a mathematical model for laser-induced thermotherapy in liver tissue

The purpose of the study was to develop a simulation approach for laser-induced thermotherapy (LITT) that is based on mathematical models for radiation transport, heat transport, and tissue damage. The LITT ablation was applied to ex vivo pig liver tissue. Experiments were repeated with different laser powers, i.e., 22–34 W, and flow rates of the cooling water in the applicator system, i.e., 47–92 ml/min. During the procedure, the temperature was measured in the liver sample at different distances to the applicator as well as in the cooling circuit using a fiber optic thermometer. For validation, the simulation results were compared with the results of the laser ablation experiments in the ex vivo pig liver samples. The simulated and measured temperature curves presented a relatively good agreement. The Bland-Altman plot showed an average of temperature differences of –0.13 ∘C and 95%-limits-of-agreement of ±7.11 ∘C. The standard deviation amounted to ±3.63 ∘C. The accuracy of the developed simulation is comparable with the accuracy of the MR thermometry reported in other clinical studies. The simulation showed a significant potential for the application in treatment planning

Generative Adversarial Networks: A Primer for Radiologists

Artificial intelligence techniques involving the use of artificial neural networks-that is, deep learning techniques-are expected to have a major effect on radiology. Some of the most exciting applications of deep learning in radiology make use of generative adversarial networks (GANs). GANs consist of two artificial neural networks that are jointly optimized but with opposing goals. One neural network, the generator, aims to synthesize images that cannot be distinguished from real images. The second neural network, the discriminator, aims to distinguish these synthetic images from real images. These deep learning models allow, among other applications, the synthesis of new images, acceleration of image acquisitions, reduction of imaging artifacts, efficient and accurate conversion between medical images acquired with different modalities, and identification of abnormalities depicted on images. The authors provide an introduction to GANs and adversarial deep learning methods. In addition, the different ways in which GANs can be used for image synthesis and image-to-image translation tasks, as well as the principles underlying conditional GANs and cycle-consistent GANs, are described. Illustrated examples of GAN applications in radiologic image analysis for different imaging modalities and different tasks are provided. The clinical potential of GANs, future clinical GAN applications, and potential pitfalls and caveats that radiologists should be aware of also are discussed in this review. The online slide presentation from the RSNA Annual Meeting is available for this article.</p

A thermometry software tool for monitoring laser-induced interstitial thermotherapy

The purpose of this study was to develop a thermometry software tool for temperature monitoring during laser-induced interstitial thermotherapy (LITT). C++ programming language and several libraries including DICOM Toolkit, Grassroots DICOM library, Insight Segmentation and Registration Toolkit, Visualization Toolkit and Quasar Toolkit were used. The software’s graphical user interface creates windows displaying the temperature map and the coagulation extent in the tissue, determined by the magnetic resonance imaging (MRI) thermometry with the echo planar imaging sequence and a numerical simulation based on the radiation and heat transfer in biological tissues, respectively. The software was evaluated applying the MRI-guided LITT to ex vivo pig liver and simultaneously measuring the temperature through a fiber-optic thermometer as reference. Using the software, the temperature distribution determined by the MRI method was compared with the coagulation extent simulation. An agreement was shown between the MRI temperature map and the simulated coagulation extent. Furthermore, the MRI-based and simulated temperatures agreed with the measured one – a correlation coefficient of 0.9993 and 0.9996 was obtained, respectively. The precision of the MRI temperature amounted to 2.4°C. In conclusion, the software tool developed in the present study can be applied for monitoring and controlling the LITT procedure in ex vivo tissues

A translational study “case report” on the small molecule “energy blocker” 3-bromopyruvate (3BP) as a potent anticancer agent: from bench side to bedside

The small alkylating molecule, 3-bromopyruvate (3BP), is a potent and specific anticancer agent. 3BP is different in its action from most currently available chemo-drugs. Thus, 3BP targets cancer cells’ energy metabolism, both its high glycolysis (“Warburg Effect”) and mitochondrial oxidative phosphorylation. This inhibits/ blocks total energy production leading to a depletion of energy reserves. Moreover, 3BP as an “Energy Blocker”, is very rapid in killing such cells. This is in sharp contrast to most commonly used anticancer agents that usually take longer to show a noticeable effect. In addition, 3BP at its effective concentrations that kill cancer cells has little or no effect on normal cells. Therefore, 3BP can be considered a member, perhaps one of the first, of a new class of anticancer agents. Following 3BP’s discovery as a novel anticancer agent in vitro in the Year 2000 (Published in Ko et al. Can Lett 173:83–91, 2001), and also as a highly effective and rapid anticancer agent in vivo shortly thereafter (Ko et al. Biochem Biophys Res Commun 324:269–275, 2004), its efficacy as a potent anticancer agent in humans was demonstrated. Here, based on translational research, we report results of a case study in a young adult cancer patient with fibrolamellar hepatocellular carcinoma. Thus, a bench side discovery in the Department of Biological Chemistry at Johns Hopkins University, School of Medicine was taken effectively to bedside treatment at Johann Wolfgang Goethe University Frankfurt/Main Hospital, Germany. The results obtained hold promise for 3BP as a future cancer therapeutic without apparent cyto-toxicity when formulated properly

Prospective comparison of endorectal ultrasound, three-dimensional endorectal ultrasound, and endorectal MRI in the preoperative evaluation of rectal tumors. Preliminary results

Background: The aim of this study was to compare the value of endorectal ultrasound (EUS), three-dimensional (3D) EUS, and endorectal MRI in the preoperative staging of rectal neoplasms. Methods: Thirty consecutive patients with rectal tumors were assessed by EUS and endorectal MRI. Additionally, three-dimensional ultrasound was performed in a subgroup of 25 patients. EUS data were obtained with a bifocal multiplane transducer (10 MHz) and processed on a 3D ultrasound workstation. MR imaging was carried out with a 1.5 T superconducting unit using an endorectal surface coil. Results: EUS was carried out successfully in all 30 patients, whereas endorectal MRI was not feasible in two patients. Compared with the histopathological classification, EUS and endorectal MRI correctly determined the tumor infiltration depth in 25 of 30 and 28 patients, respectively. The comparative accuracy of EUS, 3D EUS, and endorectal MRI in predicting tumor invasion was 84%, 88%, and 91%, respectively. EUS, three-dimensional EUS, and endorectal MRI enabled us to assess the lymph node status correctly in 25, 25, and 24 patients, respectively. Both three-dimensional EUS and endorectal MRI combined high-resolution imaging and multiplanar display options. Assessment of additional scan planes facilitated the interpretation of the findings and improved the understanding of the three-dimensional anatomy. Conclusion: The accuracy of three-dimensional EUS and endorectal MRI in the assessment of the infiltration depth of rectal cancer is comparable to conventional EUS. One advantage of both methods is the ability to obtain multiplanar images, which may be helpful for the planning of surgery in the future