Electrochemotherapy: A Review of Current Status, Alternative IGP Approaches, and Future Perspectives

The efficiency of electroporation (EP) has made it a widely used therapeutic procedure to transfer cell killing substances effectively to the target site. A lot of researches are being done on EP-based cancer treatment techniques. Electrochemotherapy (ECT) is the first EP-based application in the field of drug administration. ECT is a local and nonthermal treatment of cancer that combines the use of a medical device with pharmaceutical agents to obtain local tumor control in solid cancers. It involves the application of eight, 100µs, pulses at 1 or 5000 Hz frequency and specified electric field (V/cm) with a median duration of 25 minutes. The efficacy of chemotherapeutic drugs increases by applying short and intense electrical pulses. Several clinical studies proposed ECT as a safe and complementary curative or palliative treatment option (curative intent of 50% to 63% in the treatment of Basal Cell Carcinoma (BCC)) to treat a number of solid tumors and skin malignancies, which are not suitable for conventional treatments. It is used currently for treatment of cutaneous and subcutaneous lesions, without consideration of their histology. On the contrary, it is also becoming a practical method for treatment of internal, deep-seated tumors and tissues. A review of this method, needed instruments, alternative image-guided procedures (IGP) approaches, and future perspectives and recommendations are discussed in this paper.

[99mTc]oxotechnetium(V) complexes amine-amide-dithiol chelates with dialkylaminoalkyl substituents as potential diagnostic probes for malignant melanoma

[99mTc]oxotechnetium(V) complexes of amine-amide-dithiol (AADT) chelates containing tertiary amine substituents were synthesized and shown to have affinity for melanoma. For complexation the AADT-CH2[CH2]nNR2 (n = 1, 2; R = Et, n-Bu) ligand was mixed with a [99mTc]oxotechnetium(V)-glucoheptonate precursor to make the AADT-[99mTc]oxotechnetium(V) complexes in nearly quantitative yield. Structurally analogous nonradioactive oxorhenium(V) complexes were also synthesized and characterized. In vitro sigma-receptor affinity measurements indicate these complexes to possess sigma-affinity in the low micromolar range with K(i) values in the 7.8-26.1 and 0.18-2.3 microM range for the sigma1- and sigma2-receptors, respectively. In vitro cell uptake of the 99mTc complexes in intact B16 murine melanoma cells at 37 degrees C after a 60-min incubation ranged from 12% for complex 2 (n = 1, R = n-Bu) to 68% for complex 4 (n = 2, R = n-Bu). In vivo evaluation of complexes 1-Tc-4-Tc in the C57Bl/B16 mouse melanoma model demonstrated significant tumor localization. Complex 1-Tc (n = 1, R = Et) displayed an in vivo tumor uptake of 7.6% ID/g at 1 h after administration with initial melanoma/blood (M/B), melanoma/spleen (M/S), and melanoma/lung (M/L) ratios >4; these ratios increased to 10.8, 10.1, and 7.3, respectively, at 6 h. While complex 3-Tc (n = 3, R = Et) had an initial tumor uptake of 3.7% ID/g 1 h after administration with M/B, M/S, and M/L ratios >2, a greater tumor retention and slightly faster clearance from nontumor-containing organs resulted in M/B, M/S, and M/L ratios of 19.1, 19.1, and 12.7, respectively, at 6 h. The high tumor uptake and significant tumor/nontumor ratios indicate that such small technetium-99m-based molecular probes can be developed as in vivo diagnostic agents for melanoma and its metastases.

Determination of dissociation constants of 99mTechnetium radiopharmaceuticals by capillary electrophoresis

Capillary electrophoresis was applied to investigate pKa values of 99mTc radiotracers used in nuclear medicine. Therefore, the protonation equilibria of the carboxyl groups of 99mTc-mercaptoacetylglycylglycylglycine (99mTc-MAG3) and 99mTc-ethylenecysteine dimer (99mTc-EC) were studied by pH-dependent determination of electrophoretical velocities. 99mTc-ethylenecysteine dimer diethyl ester (99mTc-ECD) was used as a non-protonable standard. The capillary electrophoresis system was equipped with a radioactivity detector. Measurements were performed using a pressure-driven capillary zone electrophoresis which allowed runs even in the low pH range. For the determination of pKa values, the electrophoretical velocities of the analytes were referred to the electrophoretical velocities of tetraphenyle arsonium chloride as a positively charged marker. Calculation of pKa values was accomplished by non-linear curve fitting of both structure-based equilibria equations and sigmoidal decay functions to the experimental data. 99mTc-MAG3 was shown to have a carboxyl group pKa value of 4.22. The value for the carboxyl groups of 99mTc-EC is 2.90 (determined by structure-based equilibria equations), which represents a common value for both carboxyl groups. By the use of sigmoidal functions, similar values were elucidated. As expected, 99mTc-ECD shows no protonation step.

'3+1' mixed-ligand oxotechnetium(V) complexes with affinity for melanoma: synthesis and evaluation in vitro and in vivo

'3+1' Mixed-ligand [(99m)Tc]oxotechnetium complexes with affinity for melanoma were synthesized in a one-pot reaction. Complexation of technetium-99m with a mixture of N-R(3-azapentane-1,5-dithiol) [R = Me, Pr, Bn, Et(2)N(CH(2))(2)] and N-(2-dialkylamino)ethanethiol [alkyl = X = Et, Bu, morpholinyl] using Sn(2+) as the reducing agent resulted in the formation of '3+1' mixed-ligand technetium-99m complexes [TcO(SN(R)S)(SNX(2))] in high radiochemical yield (60-98%). In vitro uptake studies in B16 murine melanoma cells indicated a moderate tumor-cell accumulation (40%) of compound 1 [R = Me, X = Et] and a higher accumulation (69%) of compound 2 [R = Me, X = Bu] after a 60-min incubation. In vivo evaluation of compounds 1-6 in the C57Bl6/B16 mouse melanoma model demonstrated tumor localization. Compound 2 displayed the highest accumulation with up to 5% ID/g at 60 min after injection. In vivo, 2 also showed a low blood-pool activity and high melanoma/spleen (4.3) and melanoma/lung (1.9) ratios at 1 h. These results suggest that small technetium-99m complexes could be useful as potential melanoma-imaging agents.

Radiation therapy techniques in the treatment of skin cancer: an overview of the current status and outlook

Nonmelanoma skin cancer (NMSC) is a major health concern due to its high incidence rate, its negative impact on the quality of life of patients as well as the associated economic burden to the healthcare system. Surgery is currently the primary treatment offered for skin cancer patients but not applicable or available in all cases. Radiation therapy (RT), with its long successful history in the management of cancer, has shown to be an effective alternative or complementary method in cutaneous oncology. Specifically, for dermatology applications, RT is very often the preferred option due to its favorable cosmetic results, besides the excellent control rate of the tumor. During the last 120 years since the introduction of treatments based on ionizing radiation, several techniques in this area have been developed. Radionuclide brachytherapy, electronic brachytherapy, X-ray therapies with kilovolt (kV) to megavolt (MV) photons and electron beam therapy are the established methods that are currently used on skin cancer patients. The purpose of this article is to overview these techniques and discuss the pros and cons of these methods in dermatology practices. Additionally, a new approach of beta RT of superficial skin tumors is discussed, which may offer exciting features in the management of NMSC.

Novel clinical device tracking and tissue event characterization using proximally placed audio signal acquisition and processing

We propose a new and complementary approach to image guidance for monitoring medical interventional devices (MID) with human tissue interaction and surgery augmentation by acquiring acoustic emission data from the proximal end of the MID outside the patient to extract dynamical characteristics of the interaction between the distal tip and the tissue touched or penetrated by the MID. We conducted phantom based experiments (n = 955) to show dynamic tool/tissue interaction during tissue needle passage (a) and vessel perforation caused by guide wire artery perforation (b). We use time-varying auto-regressive (TV-AR) modelling to characterize the dynamic changes and time-varying maximal energy pole (TV-MEP) to compute subsequent analysis of MID/tissue interaction characterization patterns. Qualitative and quantitative analysis showed that the TV-AR spectrum and the TV-MEP indicated the time instants of the needle path through different phantom objects (a) and clearly showed a perforation versus other generated artefacts (b). We demonstrated that audio signals acquired from the proximal part of an MID could provide valuable additional information to surgeons during minimally invasive procedures.

Thyroid Nodule Classification for Physician Decision Support Using Machine Learning-Evaluated Geometric and Morphological Features

The classification of thyroid nodules using ultrasound (US) imaging is done using the Thyroid Imaging Reporting and Data System (TIRADS) guidelines that classify nodules based on visual and textural characteristics. These are composition, shape, size, echogenicity, calcifications, margins, and vascularity. This work aims to reduce subjectivity in the current diagnostic process by using geometric and morphological (G-M) features that represent the visual characteristics of thyroid nodules to provide physicians with decision support. A total of 27 G-M features were extracted from images obtained from an open-access US thyroid nodule image database. 11 significant features in accordance with TIRADS were selected from this global feature set. Each feature was labeled (0 = benign and 1 = malignant) and the performance of the selected features was evaluated using machine learning (ML). G-M features together with ML resulted in the classification of thyroid nodules with a high accuracy, sensitivity and specificity. The results obtained here were compared against state-of the-art methods and perform significantly well in comparison. Furthermore, this method can act as a computer aided diagnostic (CAD) system for physicians by providing them with a validation of the TIRADS visual characteristics used for the classification of thyroid nodules in US images.

Evaluation of Vascular Patterns Using Contact Endoscopy and Narrow-Band Imaging (CE-NBI) for the Diagnosis of Vocal Fold Malignancy

The endoscopic detection of perpendicular vascular changes (PVC) of the vocal folds has been associated with vocal fold cancer, dysplastic lesions, and papillomatosis, according to a classification proposed by the European Laryngological Society (ELS). The combination of contact endoscopy with narrow-band imaging (NBI-CE) allows intraoperatively a highly contrasted, real-time visualization of vascular changes of the vocal folds. Aim of the present study was to determine the association of PVC to specific histological diagnoses, the level of interobserver agreement in the detection of PVC, and their diagnostic effectiveness in diagnosing laryngeal malignancy. The evaluation of our data confirmed the association of PVC to vocal fold cancer, dysplastic lesions, and papillomatosis. The level of agreement between the observers in the identification of PVC was moderate for the less-experienced observers and almost perfect for the experienced observers. The identification of PVC during NBI-CE proved to be a valuable indicator for diagnosing malignant and premalignant lesions.

Endoscopic Imaging Technology Today

One of the most applied imaging methods in medicine is endoscopy. A highly specialized image modality has been developed since the first modern endoscope, the "Lichtleiter" of Bozzini was introduced in the early 19th century. Multiple medical disciplines use endoscopy for diagnostics or to visualize and support therapeutic procedures. Therefore, the shapes, functionalities, handling concepts, and the integrated and surrounding technology of endoscopic systems were adapted to meet these dedicated medical application requirements. This survey gives an overview of modern endoscopic technology's state of the art. Therefore, the portfolio of several manufacturers with commercially available products on the market was screened and summarized. Additionally, some trends for upcoming developments were collected.

Novel automated vessel pattern characterization of larynx contact endoscopic video images

Purpose

Contact endoscopy (CE) is a minimally invasive procedure providing real-time information about the cellular and vascular structure of the superficial layer of laryngeal mucosa. This method can be combined with optical enhancement methods such as narrow band imaging (NBI). However, these techniques have some problems like subjective interpretation of vascular patterns and difficulty in differentiation between benign and malignant lesions. We propose a novel automated approach for vessel pattern characterization of larynx CE + NBI images in order to solve these problems.

Methods

In this approach, five indicators were computed to characterize the level of vessel’s disorder based on evaluation of consistency of gradient and two-dimensional curvature analysis and then 24 features were extracted from these indicators. The method evaluated the ability of the extracted features to classify CE + NBI images based on the vascular pattern and based on the laryngeal lesions. Four datasets were generated from 32 patients involving 1485 images. The classification scenarios were implemented using four supervised classifiers.

Results

For classification of CE + NBI images based on the vascular pattern, polykernel support vector machine (SVM), SVM with radial basis function (RBF), k-nearest neighbor (kNN), and random forest (RF) show an accuracy of 97%, 96%, 96%, and 96%, respectively. For the classification based on the histopathology, Polykernel SVM showed an accuracy of 84%, 86% and 84%, RBF SVM showed an accuracy of 81%, 87% and 83%, kNN showed an accuracy of 89%, 87%, 91%, RF showed an accuracy of 90%, 88% and 91% for classification between benign histopathologies, between malignant histopathologies and between benign and malignant lesions, respectively.

Conclusion

These promising results show that the proposed method could solve the problem of subjectivity in interpretation of vascular patterns and also support the clinicians in the early detection of benign, pre-malignant and malignant lesions.

3D segmentation of thyroid ultrasound images using active contours

In this paper, we propose a method to segment the thyroid from a set of 2D ultrasound images. We extended an active contour model in 2D to generate a 3D segmented thyroid volume. First, a preprocessing step is carried out to suppress the noise present in US data. Second, an active contour is used to segment the thyroid in each of the 2D images. Finally, all the segmented thyroid images are passed to a 3D reconstruction algorithm to obtain a 3D model of the thyroid. We obtained an average segmentation accuracy of 86.7% in six datasets with a total of 703 images.

Anatomical Structure Segmentation in Ultrasound Volumes Using Cross Frame Belief Propagating Iterative Random Walks

Ultrasound (US) is widely used as a low-cost alternative to computed tomography or magnetic resonance and primarily for preliminary imaging. Since speckle intensity in US images is inherently stochastic, readers are often challenged in their ability to identify the pathological regions in a volume of a large number of images. This paper introduces a generalized approach for volumetric segmentation of structures in US images and volumes. We employ an iterative random walks (IRW) solver, a random forest learning model, and a gradient vector flow (GVF) based interframe belief propagation technique for achieving cross-frame volumetric segmentation. At the start, a weak estimate of the tissue structure is obtained using estimates of parameters of a statistical mechanics model of US tissue interaction. Ensemble learning of these parameters further using a random forest is used to initialize the segmentation pipeline. IRW is used for correcting the contour in various steps of the algorithm. Subsequently, a GVF-based interframe belief propagation is applied to adjacent frames based on the initialization of contour using information in the current frame to segment the complete volume by frame-wise processing. We have experimentally evaluated our approach using two different datasets. Intravascular ultrasound (IVUS) segmentation was evaluated using 10 pullbacks acquired at 20 MHz and thyroid US segmentation is evaluated on 16 volumes acquired at [Formula: see text] MHz. Our approach obtains a Jaccard score of [Formula: see text] for IVUS segmentation and [Formula: see text] for thyroid segmentation while processing each frame in [Formula: see text] for the IVUS and in [Formula: see text] for thyroid segmentation without the need of any computing accelerators such as GPUs.

Deep Convolution Neural Network for Laryngeal Cancer Classification on Contact Endoscopy-Narrow Band Imaging

(1) Background: Contact Endoscopy (CE) and Narrow Band Imaging (NBI) are optical imaging modalities that can provide enhanced and magnified visualization of the superficial vascular networks in the laryngeal mucosa. The similarity of vascular structures between benign and malignant lesions causes a challenge in the visual assessment of CE-NBI images. The main objective of this study is to use Deep Convolutional Neural Networks (DCNN) for the automatic classification of CE-NBI images into benign and malignant groups with minimal human intervention. (2) Methods: A pretrained Res-Net50 model combined with the cut-off-layer technique was selected as the DCNN architecture. A dataset of 8181 CE-NBI images was used during the fine-tuning process in three experiments where several models were generated and validated. The accuracy, sensitivity, and specificity were calculated as the performance metrics in each validation and testing scenario. (3) Results: Out of a total of 72 trained and tested models in all experiments, Model 5 showed high performance. This model is considerably smaller than the full ResNet50 architecture and achieved the testing accuracy of 0.835 on the unseen data during the last experiment. (4) Conclusion: The proposed fine-tuned ResNet50 model showed a high performance to classify CE-NBI images into the benign and malignant groups and has the potential to be part of an assisted system for automatic laryngeal cancer detection.

Proximally placed signal acquisition sensoric for robotic tissue tool interactions

Robotic surgeries are still limited with respect to the surgeon’s natural senses. The tactile sense is exceptional important in conventional clinical procedures. To identify critical structures inside the tissue, palpation is a commonly used technique in conventional open surgeries. The underlying organ or pathological structures conditions (healthy, abnormally hard or soft) can for example be localized and assessed through this process. Palpation needs a tactile sense; however, that is commonly not available or limited in robotic surgeries. The palpation need was already addressed by several research groups that integrated complex sensor-feedback-systems into prototype surgical instruments for robotic systems. We propose a new technique to acquire data of the tissue tool interaction of the surgical instruments. The structure borne transmission path is used to measure acoustic emission (AE) at the outpatient (proximal) end of the instruments with the help of different sensors attached to the surface of the surgical tool. Initial tests were performed using a microphone in combination with a stethoscope. This setup showed promising results and a more integrated prototype was subsequently designed. A piezoelectric charge accelerometer was used as vibration sensor and compared to a MEMS microphone. A signal acquisition system was developed to acquire signals from both sensors in parallel. The sensors were then attached onto the shaft of a daVinci Prograsp Forceps instrument. According to the surgery observation, a series of simulated experiments was conducted. The tip of the grasper was swiped manually over a human subject’s dorsal and palmar hand side, lateral side of neck and over the carotid artery. Additionally, contact with soft tissue and other instruments were evaluated since these are events of interest during surgery. Advanced signal processing techniques allowed the identification and characterization of significant events such as palpation dynamics, contact and pulsation. Signals acquired by the MEMS microphone showed the most promising results. This approach will now be used to build a prototype for further evaluation in a clinical setup. The paper presents the first results that show that this novel technique can provide valuable information about the tool-tissue interaction in robotic surgery that typically can only be obtained through advanced distal sensor systems or actual human touch.

Increasing the visibility of thin NITINOL vascular implants

New implants for vascular therapy like flow diverters are made of tiny braided wires. The radio opacity of these wires is poor, which makes assessment of implant expansion and exact positioning difficult. Additional markers only allow the estimation of the current device position, but they also induce artefacts that impair the assessment during the intervention and in follow-up examination. A new strategy to increase implant visibility is the braiding of composite wires with a radiopaque core along the whole implant. This paper shows some useful combinations of these new wires on a phantom study with five vascular implants.

Cyclist Effort Features: A Novel Technique for Image Texture Characterization Applied to Larynx Cancer Classification in Contact Endoscopy-Narrow Band Imaging

BACKGROUND

Feature extraction is an essential part of a Computer-Aided Diagnosis (CAD) system. It is usually preceded by a pre-processing step and followed by image classification. Usually, a large number of features is needed to end up with the desired classification results. In this work, we propose a novel approach for texture feature extraction. This method was tested on larynx Contact Endoscopy (CE)-Narrow Band Imaging (NBI) image classification to provide more objective information for otolaryngologists regarding the stage of the laryngeal cancer.

METHODS

The main idea of the proposed methods is to represent an image as a hilly surface, where different paths can be identified between a starting and an ending point. Each of these paths can be thought of as a Tour de France stage profile where a cyclist needs to perform a specific effort to arrive at the finish line. Several paths can be generated in an image where different cyclists produce an average cyclist effort representing important textural characteristics of the image. Energy and power as two Cyclist Effort Features (CyEfF) were extracted using this concept. The performance of the proposed features was evaluated for the classification of 2701 CE-NBI images into benign and malignant lesions using four supervised classifiers and subsequently compared with the performance of 24 Geometrical Features (GF) and 13 Entropy Features (EF).

RESULTS

The CyEfF features showed maximum classification accuracy of 0.882 and improved the GF classification accuracy by 3 to 12 percent. Moreover, CyEfF features were ranked as the top 10 features along with some features from GF set in two feature ranking methods.

CONCLUSION

The results prove that CyEfF with only two features can describe the textural characterization of CE-NBI images and can be part of the CAD system in combination with GF for laryngeal cancer diagnosis.

Parametrical modelling for texture characterization-A novel approach applied to ultrasound thyroid segmentation

Texture analysis is an important topic in Ultrasound (US) image analysis for structure segmentation and tissue classification. In this work a novel approach for US image texture feature extraction is presented. It is mainly based on parametrical modelling of a signal version of the US image in order to process it as data resulting from a dynamical process. Because of the predictive characteristics of such a model representation, good estimations of texture features can be obtained with less data than generally used methods require, allowing higher robustness to low Signal-to-Noise ratio and a more localized US image analysis. The usability of the proposed approach was demonstrated by extracting texture features for segmenting the thyroid in US images. The obtained results showed that features corresponding to energy ratios between different modelled texture frequency bands allowed to clearly distinguish between thyroid and non-thyroid texture. A simple k-means clustering algorithm has been used for separating US image patches as belonging to thyroid or not. Segmentation of thyroid was performed in two different datasets obtaining Dice coefficients over 85%.

Radioguided surgery: physical principles and an update on technological developments

Radioguided surgery (RGS) is the use of radiation detection probes and handheld gamma cameras in surgery rooms to identify radioactively labeled lesions inside the body with an aim to improve surgical outcome. In today’s surgery, application of these devices is a well-established practice, which provides surgeons with real-time information to guide them to the site of a lesion. In recent years, there have been several major improvements in the technology and design of gamma probes and handheld gamma cameras, enhancing their applications in surgical practices. Handheld gamma cameras, for example, are now moving from single-modality to dual-modality scanners that add anatomical data to the physiologic data, and with that provide more clinical information of the tissue under study. Also, in the last decade, a radioguided surgical technique based on the Cerenkov radiation was introduced, with more improved sensitivity in identifying radioactively labeled lesions. Additionally, recent advances in hybrid tracers have led to more efficient detection of lesions labeled with these tracers. Besides, it seems that combining medical robotics and augmented reality technology with current radioguided surgical practices potentially will change the delivery and performance of RGS in the near future. The current paper aims to give an overview of the physics of RGS and summarizes recent advances in this field that have a potential to improve the application of radioguided surgical procedures in the management of cancer.