Method for the Detection of Tumor Blood Vessels in Neurosurgery Using a Gripping Force Feedback System.

Avoiding unnecessary bleeding during neuroendoscopic surgeries is crucial because achieving hemostasis in a narrow operating space is challenging. However, when the location of a blood vessel in a tumor cannot be visually confirmed, unintentional damage to the vessel and subsequent bleeding may occur. This study proposes a method for tumor blood vessel detection using a master-slave surgical robot system equipped with a force sensor in the slave gripper. Using this method, blood pulsation inside a tumor was detected, displayed as a gripping force wave, via the slave force sensor. The characteristics of gripping force due to blood pulsation were extracted by measuring the fluctuation of the force in real time. The presence or absence of blood vessels was determined on the basis of cross-correlation coefficients between the gripping force fluctuation waveform due to blood pulsation and model fluctuation waveform. Experimental validation using two types of simulated tumors (soft: E = 6 kPa; hard: E = 38 kPa) and a simulated blood vessel (E = 1.9 MPa, radius = 0.5 mm, thickness = 0.1 mm) revealed that the presence of blood vessels could be detected while gripping at a constant angle and during transient gripping.

Bright spot analysis for photodynamic diagnosis of brain tumors using confocal microscopy.

BACKGROUND: In a previous study of photodynamic tumor diagnosis using 5-aminolevulinic acid (5-ALA), the authors proposed using fluorescence intensity and bright spot analyses under confocal microscopy for the precise discrimination of tumorous brain tissue (such as glioblastoma, GBM) from normal tissue. However, it remains unclear if bright spot analysis can discriminate infiltrating tumor in the boundary zone and whether this method is suitable for GBM with no 5-ALA fluorescence or for other tumor types. METHODS: Brain tumor tissue resected from 5-ALA-treated patients was sectioned to evaluate bright spots under confocal microscopy with a 544.5 - 619.5 nm band-pass filter, which eliminated the fluorescence induced by 5-ALA. Border regions and adjacent normal tissues were observed for differences in bright spot distribution. Histopathology was also conducted by hematoxylin and eosin (H&E) staining of serial slices from the same samples to confirm the locations of tumorous, infiltrating, and normal regions. Bright spot areas were then calculated for the same regions evaluated by histopathology. This method was applied for GBM with and without 5-ALA-induced fluorescence as well as for lower-grade gliomas and other brain tumor types. RESULTS: The bright spot area was substantially smaller in the GBM body than in normal brain tissues. Bright spot area was also smaller in infiltrating tumors than in normal tissue at the margin. The same bright spot pattern was observed in tumorous tissues with no 5-ALA-induced fluorescence and in non-GBM tumors. The bright spot fluorescence is suggested to arise from lipofuscin based on emission spectra (mainly within 544.5 - 619.5 nm) and optimum excitation wavelength (about 405 nm). CONCLUSIONS: Bright spot analysis is useful for discriminating infiltrating tumor from bordering normal tissue as an alternative or complement to photodynamic diagnosis with 5-ALA. This method is also potentially useful for tumors with no 5-ALA-derived red fluorescence and other nervous system tumors.

Finger-attachment device for the feedback of gripping and pulling force in a manipulating system for brain tumor resection.

PURPOSE: Development and evaluation of an effective attachment device for a bilateral brain tumor resection robotic surgery system based on the sensory performance of the human index finger in order to precisely detect gripping- and pulling-force feedback. METHODS: First, a basic test was conducted to investigate the performance of the human index finger in the gripping- and pulling-force feedback system. Based on the test result, a new finger-attachment device was designed and constructed. Then, discrimination tests were conducted to assess the pulling force and the feedback on the hardness of the gripped material. RESULTS: The results of the basic test show the application of pulling force on the side surface of the finger has an advantage to distinguish the pulling force when the gripping force is applied on the finger-touching surface. Based on this result, a finger-attachment device that applies a gripping force on the finger surface and pulling force on the side surface of the finger was developed. By conducting a discrimination test to assess the hardness of the gripped material, an operator can distinguish whether the gripped material is harder or softer than a normal brain tissue. This will help in confirming whether the gripped material is a tumor. By conducting a discrimination test to assess the pulling force, an operator can distinguish the pulling-force resistance when attempting to pull off the soft material. Pulling-force feedback may help avoid the breaking of blood pipes when they are trapped in the gripper or attached to the gripped tissue. CONCLUSION: The finger-attachment device that was developed for detecting gripping- and pulling-force feedback may play an important role in the development of future neurosurgery robotic systems for precise and safe resection of brain tumors.

A Force-Visualized Silicone Retractor Attachable to Surgical Suction Pipes.

This paper presents a force-visually-observable silicone retractor, which is an extension of a previously developed system that had the same functions of retracting, suction, and force sensing. These features provide not only high usability by reducing the number of tool changes, but also a safe choice of retracting by visualized force information. Suction is achieved by attaching the retractor to a suction pipe. The retractor has a deformable sensing component including a hole filled with a liquid. The hole is connected to an outer tube, and the liquid level displaced in proportion to the extent of deformation resulting from the retracting load. The liquid level is capable to be observed around the surgeon's fingertips, which enhances the usability. The new hybrid structure of soft sensing and hard retracting allows the miniaturization of the retractor as well as a resolution of less than 0.05 N and a range of 0.1-0.7 N. The overall structure is made of silicone, which has the advantages of disposability, low cost, and easy sterilization/disinfection. This system was validated by conducting experiments.

Fluorescence intensity and bright spot analyses using a confocal microscope for photodynamic diagnosis of brain tumors.

BACKGROUND: In photodynamic diagnosis using 5-aminolevulinic acid (5-ALA), discrimination between the tumor and normal tissue is very important for a precise resection. However, it is difficult to distinguish between infiltrating tumor and normal regions in the boundary area. In this study, fluorescent intensity and bright spot analyses using a confocal microscope is proposed for the precise discrimination between infiltrating tumor and normal regions. METHODS: From the 5-ALA-resected brain tumor tissue, the red fluorescent and marginal regions were sliced for observation under a confocal microscope. Hematoxylin and eosin (H&E) staining were performed on serial slices of the same tissue. According to the pathological inspection of the H&E slides, the tumor and infiltrating and normal regions on confocal microscopy images were investigated. From the fluorescent intensity of the image pixels, a histogram of pixel number with the same fluorescent intensity was obtained. The fluorescent bright spot sizes and total number were compared between the marginal and normal regions. RESULTS: The fluorescence intensity distribution and average intensity in the tumor were different from those in the normal region. The probability of a difference from the dark enhanced the difference between the tumor and the normal region. The bright spot size and number in the infiltrating tumor were different from those in the normal region. CONCLUSIONS: Fluorescence intensity analysis is useful to distinguish a tumor region, and a bright spot analysis is useful to distinguish between infiltrating tumor and normal regions. These methods will be important for the precise resection or photodynamic therapy of brain tumors.

Force-Sensing Silicone Retractor for Attachment to Surgical Suction Pipes.

This paper presents a novel force-sensing silicone retractor that can be attached to a surgical suction pipe to improve the usability of the suction and retraction functions during neurosurgery. The retractor enables simultaneous utilization of three functions: suction, retraction, and retraction-force sensing. The retractor also reduces the number of tool changes and ensures safe retraction through visualization of the magnitude of the retraction force. The proposed force-sensing system is based on a force visualization mechanism through which the force is displayed in the form of motion of a colored pole. This enables surgeons to estimate the retraction force. When a fiberscope or camera is present, the retractor enables measurement of the retraction force with a resolution of 0.05 N. The retractor has advantages of being disposable, inexpensive, and easy to sterilize or disinfect. Finite element analysis and experiments demonstrate the validity of the proposed force-sensing system.

Gait Analysis Using a Support Vector Machine for Lumbar Spinal Stenosis.

Lumbar spinal canal stenosis (LSS) is diagnosed based on physical examination and radiological documentation of lumbar spinal canal narrowing. Differential diagnosis of the level of lumbar radiculopathy is difficult in multilevel spinal stenosis. Therefore, the authors focused on gait analysis as a classification method to improve diagnostic accuracy. The goal of this study was to identify gait characteristics of L4 and L5 radiculopathy in patients with LSS and to classify L4 and L5 radiculopathy using a support vector machine (SVM). The study group comprised 13 healthy volunteers (control group), 11 patients with L4 radiculopathy (L4 group), and 22 patients with L5 radiculopathy (L5 group). Light-emitting diode markers were attached at 5 sites on the affected side, and walking motion was analyzed using video recordings and the authors' development program. Potential gait characteristics of each group were identified to use as SVM parameters. In the knee joint of the L4 group, the waveform was similar to that of normal gait, but knee extension at initial contact was slightly greater than that of the other groups. In the ankle joint of the L5 group, the one-peak waveform pattern with disappearance of the second peak was present in 10 (45.5%) of 22 cases. The total classification accuracy was 80.4% using the SVM. The highest and lowest classification accuracies were obtained in the control group (84.6%) and the L4 group (72.7%), respectively. The authors' walking motion analysis system identified several useful factors for differentiating between healthy individuals and patients with L4 and L5 radiculopathy, with a high accuracy rate.

Differences in Gait Characteristics of Patients with Lumbar Spinal Canal Stenosis (L4 Radiculopathy) and Those with Osteoarthritis of the Hip.

It is important to differentially diagnose thigh pain from lumbar spinal stenosis (particularly lumbar fourth nerve root radiculopathy) and osteoarthritis of the hip. In this study, using a treadmill and a motion analysis method, gait characteristics were compared between these conditions. Patients with lumbar fourth nerve root radiculopathy had increased physiological knee flexion immediately after foot-ground contact, possibly owing to a slight decrease in the muscle strength of the quadriceps femoris muscle. Patients with osteoarthritis of the hip had decreased range of motion of the hip joint probably due to anatomically limited mobility as well as gait strategy to avoid pain resulting from increased internal pressure on the hip joint during its extension. Our facile and noninvasive method can be useful for the differential diagnosis of lumbar spinal canal stenosis from osteoarthritis of the hip.

Visualization method based stiffness sensing system for endoscopes.

This research developed novel stiffness sensing system attachable to endoscope. The system is an extension of our previous force sensing systems utilizing force visualization mechanism. The sensing part is attached to endoscopes. The force is visualized at the sensing part, and can be measured as visual information via endoscopes. The sensing part also has a structure of limiting the pressing amount. By measuring force at the limitation, the stiffness can be measured. The developed sensing part has the features of no electrical components, disposable, simple, easy sterilization, MRI-compatibility, and low-cost. The validation of the system was experimentally shown.

Identification of the causative disease of intermittent claudication through walking motion analysis: feature analysis and differentiation.

Intermittent claudication is a walking symptom. Patients with intermittent claudication experience lower limb pain after walking for a short time. However, rest relieves the pain and allows the patient to walk again. Unfortunately, this symptom predominantly arises from not 1 but 2 different diseases: LSS (lumber spinal canal stenosis) and PAD (peripheral arterial disease). Patients with LSS can be subdivided by the affected vertebra into 2 main groups: L4 and L5. It is clinically very important to determine whether patients with intermittent claudication suffer from PAD, L4, or L5. This paper presents a novel SVM- (support vector machine-) based methodology for such discrimination/differentiation using minimally required data, simple walking motion data in the sagittal plane. We constructed a simple walking measurement system that is easy to set up and calibrate and suitable for use by nonspecialists in small spaces. We analyzed the obtained gait patterns and derived input parameters for SVM that are also visually detectable and medically meaningful/consistent differentiation features. We present a differentiation methodology utilizing an SVM classifier. Leave-one-out cross-validation of differentiation/classification by this method yielded a total accuracy of 83%.

Force sensor attachable to thin fiberscopes/endoscopes utilizing high elasticity fabric.

An endoscope/fiberscope is a minimally invasive tool used for directly observing tissues in areas deep inside the human body where access is limited. However, this tool only yields visual information. If force feedback information were also available, endoscope/fiberscope operators would be able to detect indurated areas that are visually hard to recognize. Furthermore, obtaining such feedback information from tissues in areas where collecting visual information is a challenge would be highly useful. The major obstacle is that such force information is difficult to acquire. This paper presents a novel force sensing system that can be attached to a very thin fiberscope/endoscope. To ensure a small size, high resolution, easy sterilization, and low cost, the proposed force visualization-based system uses a highly elastic material-panty stocking fabric. The paper also presents the methodology for deriving the force value from the captured image. The system has a resolution of less than 0.01 N and sensitivity of greater than 600 pixels/N within the force range of 0-0.2 N.

Main disease classification of intermittent claudication via L1-regularized SVM.

There are multiple diseases that cause intermittent claudication, including lumber spinal canal stenosis (LSS) and peripheral arterial disease (PAD). LSS is categorized on the basis of the diseased part: L4 and L5. The medical treatment for these groups is totally different and the differentiation is important. With this in mind, we examined walking-motion data for patients and derived several features for the differentiation in previous studies. However, these features were not specialized for classification, and there is no guarantee that the features are effective for real differentiation. The present study investigates the possibility of differentiation by gait analysis, via use of an L1-regularized support vector machine (SVM). An L1-regularized SVM can execute both classification and feature selections simultaneously. On the basis of this method, our paper presents the methodology for classifying the underlying disease of the intermittent claudication with an accuracy of 79.7%. In addition, new effective features for the differentiation are extracted.

Force-detecting gripper and force feedback system for neurosurgery applications.

PURPOSE: For the application of less invasive robotic neurosurgery to the resection of deep-seated tumors, a prototype system of a force-detecting gripper with a flexible micromanipulator and force feedback to the operating unit will be developed. METHODS: Gripping force applied on the gripper is detected by strain gauges attached to the gripper clip. The signal is transmitted to the amplifier by wires running through the inner tube of the manipulator. Proportional force is applied on the finger lever of the operating unit by the surgeon using a bilateral control program. A pulling force experienced by the gripper is also detected at the gripper clip. The signal for the pulling force is transmitted in a manner identical to that mentioned previously, and the proportional torque is applied on the touching roller of the finger lever of the operating unit. The surgeon can feel the gripping force as the resistance of the operating force of the finger and can feel the pulling force as the friction at the finger surface. RESULTS: A basic operation test showed that both the gripping force and pulling force were clearly detected in the gripping of soft material and that the operator could feel the gripping force and pulling force at the finger lever of the operating unit. CONCLUSIONS: A prototype of the force feedback in the microgripping manipulator system has been developed. The system will be useful for removing deep-seated brain tumors in future master-slave-type robotic neurosurgery.

Study on differentiation factors for main disease identification of intermittent claudication.

Intermittent Claudication is a walking symptom. After a short time walking, patients suffer from pains at lower limbs. But if taking a rest, the pains can be relieved and they can walk again. Unfortunately, it arises from not one but mainly two kinds of diseases: LSS (lumber spinal canal stenosis) and PAD (peripheral arterial disease). Additionally, it is reported that symptom is similar and LSS groups is furthermore divided into two main groups: L4 and L5 groups. Therefore, it is clinically very important to differentiate which diseases the patients suffer from, PAD, L4 or L5. We aims at developing the system to differentiate them from short walking motion data. In our previous paper, we derived differentiation factors, but did not consider the difference between L4 and L5 and the results are limited. This paper focuses on biarticular muscles associated with the diseases, and derive new and effective differentiation factors. The results supports their effectiveness and validity.