Excitation coil for sentinel lymph node harvesting: design, digital twin and prototype.

A recently developed prototype (Laparoscopic Differential Magnetometer, in short LapDiffMag) identifies magnetic tracer accumulated inside sentinel lymph nodes (SLNs) during clinical laparoscopic procedures. The LapDiffMag relies on excitation of superparamagnetic iron oxide nanoparticles (SPIONs) and subsequent laparoscopic detection based on a nonlinear detection principle. The prototype uses an excitation coil to generate a magnetic field needed to activate SPIONs. This study reports on the process of developing a new excitation coil by describing the design choices based upon clinical requirements, by modeling delivered magnetic field using digital twin, and by comparing the magnetic fields of modeled and manufactured prototype. Digital twin technology was used to produce relevant and reliable data to demonstrate the safety and effectiveness of the excitation coil. The magnetic field originating from manufactured prototype was validated at two different heights above the excitation coil and have shown a good concordance to the data generated by its digital twin. Clinical Relevance- Current standard-of-care for a variety of tumor types consists of minimally invasive radical resection of primary tumor and regional lymph nodes (LNs). The newly introduced excitation coil will (after full validation) enable minimally invasive harvesting of sentinel LNs by means of magnetic tracer detection.

Assessment of disease severity in a Canine Model of Duchenne Muscular Dystrophy: Classification of Quantitative MRI.

Duchenne muscular dystrophy (DMD) is a fatal Xlinked muscle disorder caused by mutations in the dystrophin gene with a consequence of progressive degeneration of skeletal and cardiac muscle. Golden retriever muscular dystrophy (GRMD) is a spontaneous X-linked canine model of DMD with similar effects. Due to high soft-tissue contrast images, MRI is preferred as a non-invasive method to extract information corresponding to biological characteristics. We propose and evaluate non-invasive MRI-based imaging biomarkers to assess the severity of golden retriever muscular dystrophy (GRMD) using 3T and 4.7T MRI data of nine animals. These imaging biomarkers use first order statistics and texture (assessed by wavelets) in quantitative MRI (qMRI). In a leave-one-sampleout cross-validation framework, we use SVM to differentiate between young and old GRMD animals. The preliminary results show good differentiation between young and old animals for different qMRI sequences and based on a different selection of features.

Regional heterogeneity changes in DCE-MRI as response to isolated limb perfusion in experimental soft-tissue sarcomas.

Experimental evidence supports an association between heterogeneity in tumor perfusion and response to chemotherapy/radiotherapy, disease progression and malignancy. Therefore, changes in tumor perfusion may be used to assess early effects of tumor treatment. However, evaluating changes in tumor perfusion during treatment is complicated by extensive changes in tumor type, size, shape and appearance. Therefore, this study assesses the regional heterogeneity of tumors by dynamic contrast-enhanced MRI (DCE-MRI) and evaluates changes in response to isolated limb perfusion (ILP) with tumor necrosis factor alpha and melphalan. Data were acquired in an experimental cancer model, using a macromolecular contrast medium, albumin-(Gd-DTPA)45. Small fragments of BN 175 (a soft-tissue sarcoma) were implanted in eight brown Norway rats. MRI of five drug-treated and three sham-treated rats was performed at baseline and 1 h after ILP intervention. Properly co-registered baseline and follow-up DCE-MRI were used to estimate the volume transfer constant (K(trans) ) pharmacokinetic maps. The regional heterogeneity was estimated in 16 tumor sectors and presented in cumulative map-volume histograms. On average, ILP-treated tumors showed a decrease in regional heterogeneity on the histograms. This study shows that heterogenic changes in regional tumor perfusion, estimated using DCE-MRI pharmacokinetic maps, can be measured and used to assess the short-term effects of a potentially curative treatment on the tumor microvasculature in an experimental soft-tissue sarcoma model.

Heterogeneity in DCE-MRI parametric maps: a biomarker for treatment response?

This study aims to quantify the heterogeneity of tumour enhancement in dynamic contrast-enhanced MRI (DCE-MRI) using texture analysis methods. The suitability of the coherence and the fractal dimension to monitor tumour response was evaluated in 18 patients with limb sarcomas imaged by DCE-MRI pre- and post-treatment. According to the histopathology, tumours were classified into responders and non-responders. Pharmacokinetic (K(trans)) and heuristic model-based parametric maps (slope, max enhancement, AUC) were computed from the DCE-MRI data. A substantial correlation was found between the pharmacokinetic and heuristic model-based parametric maps: ρ = 0.56 for the slope, ρ = 0.44 for maximum enhancement, and ρ = 0.61 for AUC. From all four parametric maps, the enhancing fraction, and the heterogeneity features (i.e. coherence and fractal dimension) were determined. In terms of monitoring tumour response, using both pre- and post-treatment DCE-MRI, the enhancing fraction and the coherence showed significant differences between the response group and the non-response group (i.e. the highest sensitivity (91%) for K(trans), and the highest specificity (83%) for max enhancement). In terms of treatment prediction, using solely the pre-treatment DCE-MRI, the enhancing fraction and coherence discriminated between responders and non-responders. For prediction, the highest sensitivity (91%) was shared by K(trans), slope and max enhancement, and the highest specificity (71%) was achieved by K(trans). On average, tumours that responded showed a high enhancing fraction and high coherence on the pre-treatment scan. These results suggest that specific heterogeneity features, computed from both pharmacokinetic and heuristic model-based parametric maps, show potential as a biomarker for monitoring tumour response.

Estimation of respiratory parameters via fuzzy clustering.

The results of monitoring respiratory parameters estimated from flow-pressure-volume measurements can be used to assess patients' pulmonary condition, to detect poor patient-ventilator interaction and consequently to optimize the ventilator settings. A new method is proposed to obtain detailed information about respiratory parameters without interfering with the expiration. By means of fuzzy clustering, the available data set is partitioned into fuzzy subsets that can be well approximated by linear regression models locally. Parameters of these models are then estimated by least-squares techniques. By analyzing the dependence of these local parameters on the location of the model in the flow-volume-pressure space, information on patients' pulmonary condition can be gained. The effectiveness of the proposed approaches is demonstrated by analyzing the dependence of the expiratory time constant on the volume in patients with chronic obstructive pulmonary disease (COPD) and patients without COPD.

Primary lymphoma of the brain: a case report and review of the literature.

A case of primary lymphoma of the brain is presented. The disease is rare and thus firm guidelines for therapy are lacking. Whole-brain irradiation therapy, the accepted treatment of choice, when given to a dose of 5000 rads, is associated with improved survival. However, the overall prognosis is poor due to local recurrence in the central nervous system and the tumor's ability to diffusely infiltrate the meninges. Twenty-six percent of the cases may have positive cerebrospinal fluid cytology. Whether the addition of intrathecal chemotherapy with agents such as methotrexate will improve upon the results obtained with irradiation therapy alone would be an appropriate subject for a cooperative prospective randomized study.