Method Of Tumor Localization Research Articles

Diagnostic Benefits and Surgical Implications of Methods for Tumor Localization in Sigmoid and Rectum Tumors.

(1) Background: In our study, we aimed to determine the accuracy rates of imaging methods for sigmoid, rectosigmoid colon, and rectum cancer. (2) Methods: Patients with tumors located in the rectosigmoid colon, sigmoid colon, and rectum who were operated on were included. Upon admission, we examined the patients' first diagnostic colonoscopies and their preoperative repeat control colonoscopies and computed tomography (CT) report. (3) Results: In this study, 23 patients (57.5%) were male. The overall accuracy rates were 80.0% (32/40) in colonoscopy, 65.0% (26/40) in preoperative CT, and 87.5% (35/40) in retro CT, and the differences among the examination methods were statistically significant (p = 0.049). The sensitivity levels decreased to 50.0% for colonoscopy and preoperative CT and 75.0% for retro CT in rectosigmoid colon tumors. In rectal tumors, the sensitivity levels were 75.0% in colonoscopy, 60.0% in preoperative CT, and 80.0% in retro CT. In two patients, the tumor location was given incorrectly, and postoperative pathological evaluations indicated T3N0 tumors; the initially planned treatment was thus changed to include radiotherapy in addition to chemotherapy in the postoperative period because the tumor was located in the middle rectum. (4) Conclusions: Accuracy in tumor localization in sigmoid, rectosigmoid, and rectum tumors still needs to be improved, which could be accomplished with prospective studies. CT evaluations for cancer localization in this patient group should be re-evaluated by a radiologist.

A Multimodal Point Cloud-Based Method for Tumor Localization in Robotic Ultrasound-Guided Radiotherapy.

Objectives: Part of the tumor localization methods in radiotherapy have poor real-time performance and may generate additional radiation. We propose a multimodal point cloud-based method for tumor localization in robotic ultrasound-guided radiotherapy, which only irradiates computed tomography (CT) during radiotherapy planning to avoid additional radiation. Methods: The tumor position was determined using the CT point cloud, and the red green blue depth (RGBD) point cloud was used to determine body surface scanning location corresponding to the tumor location. The relationship between the CT point cloud and RGBD point cloud was established through multi-modal point cloud registration. The point cloud was then used for robot tumor localization through coordinate transformation between camera and robot. Results: The maximum mean absolute error of the tumor location in the X, Y, and Z directions of the robot coordinate system were 0.781, 1.334, and 1.490 mm, respectively. The average point-to-point translation mean absolute error between the actual and predicted positions of the localization points was 1.847 mm. The maximum error in the random positioning experiment was 1.77 mm. Conclusion: The proposed method is radiation free and has real-time performance, with tumor localization accuracy that meets the requirements of radiotherapy. The proposed method, which potentially reduces the risks associated with radiation exposure while ensuring efficient and accurate tumor localization, represents a promising advancement in the field of radiotherapy.

Assessment of low-cost surgical metallic clip placement for tumor localization in BIRDAS VI breast cancer patients undergoing neoadjuvant chemotherapy

BackgroundNeoadjunvant chemotherapy has become a challenging connotation for both surgeons and radiologists due to the high clinical response up to dramatic pathological complete response (pCR) that may hinder proper localization of any residual tumoral tissue. So the radiopaque markers implantation at the tumor bed became a reliable and recommended method for tumor localization before surgical intervention or NAC. Many types of commercial clips and markers are available; however they are relatively of high cost and represent a considerable burden on the governments and the heath institute that made the researchers study cheaper alternatives as standard titanium based cholecystectomy surgical clips for tumor localization.ResultsThe study was conducted on 45 patients where 57 clips were inserted corresponding to number of lesions found in the total number of the patients. The response to Neoadjunvant chemotherapy was recorded and showed that 6 patients (about 13.3%) had complete radiological response after NAC, while 27 patients (60%) had regressive course after the treatment. The low cost surgical clips were evaluated by using sono-mammography and magnetic resonance imaging, and complications that occurred were recorded. Our study showed that in only 2 patients (3.5%) there was difficulty in clip visualization by Ultrasound during post-treatment follow up. In 45 patients, all the inserted clips (100%) were well visualized as small signal void on MRI at both T1WIs and T2WIs sequences, and the primary malignancy was easily visualized on both MRI and sono-mammography not interfering with the image interpretation and judgment. As regards the reported complications, our results revealed that in only 2 patients (3.5%) there was evidence of positive clip migration, while only 2 patients (3.5%) developed hematoma during the procedure as shown by ultrasound, Also 4 patients (7%) complained of pain only shortly after clip insertion. No other significant complications like infection or heat sensation developed either during the procedure or during MRI. The total price of the surgical clips was calculated with average cost of the needle about 10 US$ equivalent to 170 LE Egyptian pounds and the clip about 1.3 US$ or 20 Egyptian pounds, which is considered of lower cost when compared to the commercial breast markers of different companies with an estimated price range for clip = 75–200 US$ (average 90 US$). So insertion of surgical clips saved about 1135 Egyptian pounds equivalent to 73–75 US$ per clip placement.ConclusionWe concluded from our study that the use of breast markers are mandatory before NAC where Surgical clips can safely substitute the commercial tissue markers as tumor localizers as they are effective, safe, well tolerated, easily visualized on imaging and do not interfere with assessment of the treatment response, with no evidence of complications and are of low cost compared with the commercial breast clips.

Brain tumor segmentation in MRI images using nonparametric localization and enhancement methods with U-net.

Segmentation is one of the critical steps in analyzing medical images since it provides meaningful information for the diagnosis, monitoring, and treatment of brain tumors. In recent years, several artificial intelligence-based systems have been developed to perform this task accurately. However, the unobtrusive or low-contrast occurrence of some tumors and similarities to healthy brain tissues make the segmentation task challenging. These yielded researchers to develop new methods for preprocessing the images and improving their segmentation abilities. This study proposes an efficient system for the segmentation of the complete brain tumors from MRI images based on tumor localization and enhancement methods with a deep learning architecture named U-net. Initially, the histogram-based nonparametric tumor localization method is applied to localize the tumorous regions and the proposed tumor enhancement method is used to modify the localized regions to increase the visual appearance of indistinct or low-contrast tumors. The resultant images are fed to the original U-net architecture to segment the complete brain tumors. The performance of the proposed tumor localization and enhancement methods with the U-net is tested on benchmark datasets, BRATS 2012, BRATS 2019, and BRATS 2020, and achieved superior results as 0.94, 0.85, 0.87, 0.88 dice scores for the BRATS 2012 HGG-LGG, BRATS 2019, and BRATS 2020 datasets, respectively. The results and comparisons showed how the proposed methods improve the segmentation ability of the deep learning models and provide high-accuracy and low-cost segmentation of complete brain tumors in MRI images. The results might yield the implementation of the proposed methods in segmentation tasks of different medical fields.

Microwave breast tumor localization using wavelet feature extraction and genetic algorithm-neural network.

Ultra-Wide Band (UWB) microwave breast cancer detection is a promising new technology for routine physical examination and home monitoring. The existing microwave imaging algorithms for breast tumor detection are complex and the effect is still not ideal, due to the heterogeneity of breast tissue, skin reflection, and fibroglandular tissue reflection in backscatter signals. This study aims to develop a machine learning method to accurately locate breast tumor. A microwave-based breast tumor localization method is proposed by time-frequency feature extraction and neural network technology. First, the received microwave array signals are converted into representative and compact features by 4-level Discrete Wavelet Transform (DWT) and Principal Component Analysis (PCA). Then, the Genetic Algorithm-Neural Network (GA-NN) is developed to tune hyper-parameters of the neural network adaptively. The neural network embedded in the GA-NN algorithm is a four-layer architecture and 10-fold cross-validation is performed. Through the trained neural network, the tumor localization performance is evaluated on four datasets that are created by FDTD simulation method from 2-D MRI-derived breast models with varying tissue density, shape, and size. Each dataset consists of 1000 backscatter signals with different tumor positions, in which the ratio of training set to test set is 9:1. In order to verify the generalizability and scalability of the proposed method, the tumor localization performance is also tested on a 3-D breast model. For these 2-D breast models with unknown tumor locations, the evaluation results show that the proposed method has small location errors, which are 0.6076mm, 3.0813mm, 2.0798mm, and 3.2988mm, respectively, and high accuracy, which is 99%, 80%, 94%, and 85%, respectively. Furthermore, the location error and the prediction accuracy of the 3-D breast model are 3.3896mm and 81%. These evaluation results demonstrate that the proposed machine learning method is effective and accurate for microwave breast tumor localization. The traditional microwave-based breast cancer detection method is to reconstruct the entire breast image to highlight the tumor. Compared with the traditional method, our proposed method can directly get the breast tumor location by applying neural network to the received microwave array signals, and circumvent any complicated image reconstruction processing.

Does Localization Technique Matter for Non-palpable Breast Cancers?

There are several techniques for localization of non-palpable breast tumors, but comparisons of these techniques in terms of margin positivity and volume of tissue resected are lacking. Between 2011-2013 and 2016-2018, 2 randomized controlled trials involving 10 centers across the United States accrued 631 patients with stage 0-3 breast cancer, all of whom underwent breast conserving surgery. Of these, 522 had residual non-palpable tumors for which localization was required. The localization technique was left to the discretion of the individual surgeon. We compared margin positivity and volume of tissue resected between various localization techniques. The majority of the patients (n = 465; 89.1%) had wire localization (WL), 50 (9.6%) had radioactive seed (RS) localization, and 7 (1.3%) had Savi Scout (SS) localization. On bivariate analysis, there was no difference in terms of margin positivity (37.8% vs. 28.0% vs. 28.6%, P = .339) nor re-excision rates (13.3% vs. 12.0% vs. 14.3%, P = .961) for the WL, RS, and SS groups, respectively. Further, the volume of tissue removed was not significantly different between the 3 groups (71.9cm3 vs. 55.8cm3 vs. 86.6cm3 for the WL, RS, and SS groups, respectively, P = .340). On multivariate analysis, margin status was affected by tumor size (OR = 1.336; 95% CI: 1.148-1.554, P<.001) but not by type of localization (P = .670). While there are a number of methods for tumor localization, choice of technique does not seem to influence volume of tissue resected nor margin status.

A patient-independent CT intensity matching method using conditional generative adversarial networks (cGAN) for single x-ray projection-based tumor localization

A convolutional neural network (CNN)-based tumor localization method with a single x-ray projection was previously developed by us. One finding is that the discrepancy in the discrepancy in the intensity between a digitally reconstructed radiograph (DRR) of a three-dimensional computed tomography (3D-CT) and the measured x-ray projection has an impact on the performance. To address this issue, a patient-dependent intensity matching process for 3D-CT was performed using 3D-cone-beam computed tomography (3D-CBCT) from the same patient, which was sometimes inefficient and could adversely affect the clinical implementation of the framework. To circumvent this, in this work, we propose and validate a patient-independent intensity matching method based on a conditional generative adversarial network (cGAN). A 3D cGAN was trained to approximate the mapping from 3D-CT to 3D-CBCT from previous patient data. By applying the trained network to a new patient, a synthetic 3D-CBCT could be generated without the need to perform an actual CBCT scan on that patient. The DRR of the synthetic 3D-CBCT was subsequently utilized in our CNN-based tumor localization scheme. The method was tested using data from 12 patients with the same imaging parameters. The resulting 3D-CBCT and DRR were compared with real ones to demonstrate the efficacy of the proposed method. The tumor localization errors were also analyzed. The difference between the synthetic and real 3D-CBCT had a median value of no more than 10 HU for all patients. The relative error between the DRR and the measured x-ray projection was less than 4.8% ± 2.0% for all patients. For the three patients with a visible tumor in the x-ray projections, the average tumor localization errors were below 1.7 and 0.9 mm in the superior-inferior and lateral directions, resepectively. A patient-independent CT intensity matching method was developed, based on which accurate tumor localization was achieved. It does not require an actual CBCT scan to be performed before treatment for each patient, therefore making it more efficient in the clinical workflow.

Real-time tumor localization with single x-ray projection at arbitrary gantry angles using a convolutional neural network (CNN)

For tumor tracking therapy, precise knowledge of tumor position in real-time is very important. A technique using single x-ray projection based on a convolutional neural network (CNN) was recently developed which can achieve accurate tumor localization in real-time. However, this method was only validated at fixed gantry angles. In this study, an improved technique is developed to handle arbitrary gantry angles for rotational radiotherapy.To evaluate the highly complex relationship between x-ray projections at arbitrary angles and tumor motion, a special CNN was proposed. In this network, a binary region of interest (ROI) mask was applied on every extracted feature map. This avoids the overfitting problem due to gantry rotation by directing the network to neglect those irrelevant pixels whose intensity variation had nothing to do with breathing motion. In addition, an angle-dependent fully connection layer (ADFCL) was utilized to recover the mapping from extracted feature maps to tumor motion, which would vary with the gantry angles. The method was tested with images from 15 realistic patients and compared with a variant network of VGG, developed by Oxford University’s Visual Geometry Group.The tumors were clearly visible on x-ray projections for five patients only. The average tumor localization error was under 1.8 mm and 1.0 mm in superior-inferior and lateral directions. For the other ten patients whose tumors were not clearly visible in the x-ray projection, a feature point localization error was computed to evaluate the proposed method, the mean value of which was no more than 1.5 mm and 1.0 mm in both directions for all patients.A tumor localization method for single x-ray projection at arbitrary angles based on a novel CNN was developed and validated in this study for real-time operation. This greatly expanded the applicability of the tumor localization framework to the rotation therapy.

Breast Cancer Patient Auto-Setup Using Residual Neural Network for CT-Guided Therapy

Patient setup will influence the treatment of the breast cancer in radiation therapy. Improving the accuracy of the tumor target localization is vital for the cancer treatment. In this study, we focus on the breast patient setup and develop an accurate tumor localization method based on the deep learning in radiation therapy. The proposed method used a double residual neural network model to achieve the high precision and efficiency patient tumor localization. In the network training, the model attempt to localize the breast and then detect the landmarks inside the localized region. After the model training, we used an iterative filter scheme for calculating a transformation to the daily CT. Therefore, the gray value distribution can match well with the training image. The final landmark positions were obtained after the iteration. The translation errors in the daily CT were determined using the detected landmarks. We used the digital CT phantom images and the real patient CT images to evaluate the proposed method. Then result of the breast patient setup was shown to be clinically acceptable. The mean and standard deviation setup errors were 0.64 ± 1.40 mm, 0.15 ± 1.28 mm, -0.46±1.17 mm in the anterior-posterior, left-right, and superior-inferior, respectively. In conclusion, we proposed an accurate patient setup method, which shown a very promising alternative for marker-free breast auto-setup.

Convolutional Neural Network (CNN) Based Three Dimensional Tumor Localization Using Single X-Ray Projection

Accurate localization of lung tumor in real time based on a single X-ray projection is of great interest to the tumor-tracking radiotherapy but is very challenging. In this paper, a convolutional neural network (CNN)-based tumor localization method was proposed to address this problem with the aid of principal component analysis-based motion modeling. A CNN regression model was trained before treatment to recover the ill-conditioned nonlinear mapping from the single X-ray projection to the tumor motion. Novel intensity correction and data augmentation techniques were adopted to improve the model's robustness to the scatter and noise in the X-ray projection image. During treatment, the volumetric image and tumor position could be obtained by applying the CNN model on the acquired X-ray projection. This method was validated and compared with the other state-of-the-art methods on three real patient data. It was found that the proposed method could achieve real-time tumor localization with much higher accuracy (<;1 mm) and robustness.

Clinical utility of radioactive seed localization in nonpalpable breast cancer: A retrospective single institutional cohort study

BackgroundWith advances in mammographic screening techniques, it has become easier to detect nonpalpable breast lesions at an early stage. Pre-surgical localization of lesions by radioactive seed localization (RSL) has several benefits over conventional wire localization (WL) in guiding breast conserving surgery. In this study, we compared WL and RSL, focusing on the relationship between the techniques and in-breast recurrence or margin positivity. MethodsThis study included 1083 patients with nonpalpable breast lesions who underwent breast conserving surgery between 2010 and 2015. The patients were classified into WL and RSL groups. ResultsMargin positivity and in-breast recurrence rates did not differ significantly between the WL and RSL groups (P = 0.368 and P = 0.167, respectively). Multivariate analysis showed that tumor grade (OR: 5.016; 95% CI: 1.53–23.059) was significantly associated with margin positivity in patients undergoing RSL. Tumor size was significantly associated with in-breast recurrence in both the WL group (OR: 2.299; 95% CI: 1.561–3.411) and RSL group (OR: 2.998; 95% CI: 1.128–8.043). ConclusionAs the method of tumor localization did not influence margin positivity or in-breast recurrence, either WL or RSL appear to be appropriate for breast conserving surgery. Given the advantages of RSL, including the ability to perform this technique days to weeks before surgery, we propose that high-volume breast centers consider adopting this localization method.

Application value of real-time B type ultrasound guidance in resection of low-grade gliomas

Objective To investigate the application value of real-time B type ultrasound guidance in resection of low-grade gliomas. Methods Seventy-two cases of patients with low-grade gliomas were selected, who were treated at Department of Neurosurgery, Central Hospital of Jiamusi from June 2012 to June 2016, and were divided into observation group (36 cases) and control group (36 cases). Conventional tumor localization method was used in control group prior to resection, while the patients in observation group underwent tumor resection under real-time B type ultrasound guidance. The following aspects were compared between 2 groups including surgical operation, accuracy of tumor localization, total resection rate, ADL (activities of daily living) score and KPS (Karnofsky performance status) score. Results The operation time in the observation group were significantly less than that in control group (P 0.05). The 6-month follow-up showed that the patients’ preoperative KPS scores in observation (81.1±7.8) and control (71.4±9.9) groups were significantly higher than postoperative scores (58.1±8.2, 56.9±9.2, respectively) (P<0.001) and the improvement in observation group was even greater (P<0.01). Conclusion Real-time B type ultrasound guidance used for low-grade gliomas resection could achieve good clinical results, significantly reduce the operation time and improve the patient’s quality of life. Key words: Glioma; Neurosurgical procedures; Treat outcome; Quality of life; Real-time guided B-ultrasonography

Changes in the diagnosis and treatment of soft tissue sarcoma in Japan, 1977–2016

The treatment of soft tissue tumors has maderemarkable progress through advancements in diagnostic imaging and analysis ofsurgical materials. Changes in the treatment of soft tissue tumors are describedfrom my experience since 1977. Prior to the introduction of CT scans, radiography and angiography were the only methods for tumor localization. Wholebody CT, echography, and soft tissue radiography were introduced around 1980,and significant progress was seen in the localization of soft tissue tumors.Although the localization and diagnostic characteristics of tumors becameeasier with the introduction of MRI, radiography and ultrasound still remainedthe primary diagnostic method for soft tissue tumors. Since 1980, preoperative needle biopsy hasbecome a powerful diagnostic procedure by combining rapid cytological andpathological diagnosis at the Cancer Institute Hospital.The curative wide resection method, based on barrier theory, was an index forpreoperative planning. In addition, with the advent of evaluation methods forsurgical margins, the curability of wide resections can be discussed on acommon platform to open new possibilities in limited resection. However,because current evaluation methods for surgical margins were based onmacroscopic findings, diagnostic measures for invasive sarcomas are stillneeded in future investigations. The development of In Situ Preparation (ISP) isuseful for acquiring information that cannot be obtained with preoperativeimages as it allows for intraoperative evaluation of margins without the riskof tumor contamination, and the surgical technique could be consideredessential for limited resection. In most areas, the preservation of affectedlimbs was made possible by combining ISP with vascular reconstruction, flaptransplantation, joint arthroplasty, bone grafting, among other techniques. Inorder to improve the outcome for the treatment of sarcoma, which is a rarecancer, it is essential to consolidate facilities.

P1.16-016 Comparing Safety and Effectiveness of Image-Guided VATS Versus Conventional VATS for Small or Deep Pulmonary Nodules

Video-assisted thoracic surgery (VATS) is currently performed to diagnose and treat solitary pulmonary nodules (SPN). However, the intra-operative identification of small and/or deep nodules can be challenging with VATS as the lung is difficult to palpate. Single-stage image-guided VATS(iVATS) performed in a hybrid operation room has been introduced in recent years for the simultaneous localization and removal of small SPN. However, its efficacy and safety compared with traditional workflow has not been studied. Patients with undiagnosed SPN who required tumor localization prior to surgical resection between 2017/3 to 2017/6 were retrospectively reviewed. Based on the type of tumor localization method, patients were divided into two groups ( Group1 : iVATS ; Group 2: preoperative computed tomography guide tumor localization followed by VATS). The efficacy in localizing the tumor, complications, necessity to convert VATS to thoracotomy and radiation dose were compared. The cohort comprised 24 patients (12 in each group). The median SPN diameter was 7 mm (range: 3 – 11 mm) and the median distance of the lesion from the pleural surface was 13 mm (range: 0 – 47 mm) with no intergroup difference (P>0.05). Tumor localization procedure was successful in all patients with similar procedure time ( group1: 28 mins[range: 16∼41 mins] ; group2: 20 mins[range:14-35 mins] , p>0.05). However, the time interval from completion of localization to surgery was significantly longer in group 2 (median: 159 mins [range:78∼313mins]) than in group1(median:10mins[range:3∼20 mins], p<0.001). In group 2, migration of the hook wire occurred in 1 patients during the waiting period although it did not affect the success of VATS resection (nodule location guided by the lung puncture site). The mean effective radiation dose for group1 was 11.53 mSv and that for group2 was 13.50 mSv, respectively (P>0.05). Compared with the traditional workflow (based on preoperative CT-guided lesion localization followed by its surgical removal), single-stage iVATS for simultaneous localization and removal of small SPN is equally safe and accurate but more efficient.

A Promising Method for Tumor Localization during Total Laparoscopic Distal Gastrectomy: Preoperative Endoscopic Clipping based on Negative Biopsy and Selective Intraoperative Radiography Findings.

PurposePrecise localization of tumors and creation of sufficient proximal resection margins are complicated processes during total laparoscopic distal gastrectomy (TLDG) for clinical T1/T2 gastric cancers. Various solutions to this problem have also yielded many disadvantages. In this study, we reviewed a preoperative endoscopic clipping method based on the results of negative biopsy and selective intraoperative radiography.Materials and MethodsA retrospective review of 345 consecutive patients who underwent TLDG and preoperative endoscopic clipping for tumor localization was conducted. During preoperative endoscopy, the endoscopists performed negative biopsies just 1–2 cm selectively above the tumor's upper limit. After confirming the biopsy results, endoscopic metal clips were applied just proximal to the negative biopsy site the day before surgery. Selective intraoperative tumor localization using portable abdominal radiography was performed only when we could not ensure a precise resection line.ResultsNegative biopsy was performed in 244 patients. Larger tumor size (P=0.008) and more distally located tumors (P=0.052) were observed more frequently in the negative biopsy group than in the non-negative biopsy group. The non-negative biopsy group had significantly higher frequencies of differentiated tumor types than the negative biopsy group (P=0.003). Of the 244 patients who underwent negative biopsies, 6 had cancer cells in their biopsy specimens. We performed intraoperative radiography in 12 patients whose tumors had difficult-to-determine proximal margins. No tumors were found in the proximal resection margins of any patients.ConclusionsOur tumor localization method is a promising and accurate method for securing a sufficient resection margin during TLDG.

TH-AB-202-06: BEST IN PHYSICS (JOINT IMAGING-THERAPY): A Real-Time Tumor Tracking Using Novel Scatter Imaging Modality During Lung SBRT

Purpose: Compared to traditional radiotherapy techniques, stereotactic body radiation therapy (SBRT) provides more favorable outcomes during the treatment of certain lung tumors. Despite advancements in image guidance, accurate target localization still remains a challenge. In this work, we expand our knowledge of a novel scatter imaging modality in order to develop a real-time tumor localization method using scattered photons from the patient during treatment. Methods: Images of the QUASAR™ Respiratory Motion Phantom were taken by irradiating it on a Varian TrueBeam accelerator. The scattered radiation was detected using a flat panel-based pinhole camera detection system. Two motion settings were investigated: static and dynamic. In the former, the lung tumor was manually shifted between imaging. In the latter, the lung tumor was set to move at a certain frequency and amplitude while the images were acquired continuously for one minute. The accuracy of tumor localization and the irradiation time required to distinguish the lung tumor were studied. Results: The comparison of measured and expected location of the lung tumor during static motion was shown to be under standard deviation (STD) of 0.064 with a mean STD of 0.031cm. The dynamic motion was taken at a rate of 1400 MU/min for one minute and the measured location of the lung tumor was then compared with the QUASAR phantom’s sinusoidal motion pattern and the agreement found to be at an average STD of 0.275cm. The location of the lung tumor was investigated using aggregate images consisting of 1 or 2 frames/image and the change was below STD of 0.30cm. The lung tumor also appeared to be blurrier in images consisting of two frames. Conclusion: Based on our preliminary results real-time image guidance using the scatter imaging modality to localize and track tumors during lung SBRT has the potential to become clinical reality.

A novel endoscopic fluorescent band ligation method for tumor localization.

Accurate tumor localization is essential for minimally invasive surgery. This study describes the development of a novel endoscopic fluorescent band ligation method for the rapid and accurate identification of tumor sites during surgery. The method utilized a fluorescent rubber band, made of indocyanine green (ICG) and a liquid rubber solution mixture, as well as a near-infrared fluorescence laparoscopic system with a dual light source using a high-powered light-emitting diode (LED) and a 785-nm laser diode. The fluorescent rubber bands were endoscopically placed on the mucosae of porcine stomachs and colons. During subsequent conventional laparoscopic stomach and colon surgery, the fluorescent bands were assayed using the near-infrared fluorescence laparoscopy system. The locations of the fluorescent clips were clearly identified on the fluorescence images in real time. The system was able to distinguish the two or three bands marked on the mucosal surfaces of the stomach and colon. Resection margins around the fluorescent bands were sufficient in the resected specimens obtained during stomach and colon surgery. These novel endoscopic fluorescent bands could be rapidly and accurately localized during stomach and colon surgery. Use of these bands may make possible the excision of exact target sites during minimally invasive gastrointestinal surgery.

A comparison between two methods for tumor localization during totally laparoscopic distal gastrectomy in patients with gastric cancer.

PurposeThe aim of this study was to compare two methods of tumor localization during totally laparoscopic distal gastrectomy (TLDG) in patients with gastric cancer.MethodsFrom March 2014 to November 2014, patients in whom TLDG had been engaged for middle third gastric cancer enrolled in this study. The patients were allocated to either the radiography or endoscopy group based on the type of tumor localization technique. Clinicopathologic outcomes were compared between the 2 groups.ResultsThe accrual was suspended in November 2014 when 39 patients had been enrolled because a failed localization happened in the radiography group. The radiography and endoscopy groups included 17 (43.6 %) and 22 patients (56.4 %), respectively. Mean length of the proximal resection margin did not differ between the radiography and endoscopy groups (4.0 ± 2.6 and 2.8 ± 1.2 cm, respectively; P = 0.077). Mean localization time was longer in the radiography group than in the endoscopy group (22.7 ± 11.4 and 6.9 ± 1.8 minutes, respectively, P < 0.001). There were no statistically significant differences in the incidence of severe complications between the 2 groups (5.9% and 4.5%, respectively, P = 0.851).ConclusionAs an intraoperative tumor localization for TLDG, radiologic method was unsafe even though other comparable parameters were not different from that of endoscopy group. Moreover, intraoperative endoscopic localization may be advantageous because it is highly accurate and contributes to reducing operation time.

Abstract 5116: Detection of pancreatic cancer using acidic pH targeted probes detected using multispectral optoacoustic tomography

Abstract Introduction: The use of theranostic nanoparticles for simultaneous tumor imaging and drug delivery is of great research interest. The tumor extracellular environment is significantly more acidic than physiologic pH, often in the range of pH 6.0-6.8. Exploitation the acidic extracellular tumor environment is a promising method of tumor localization with pH sensitive probes and targets. Further, the use of multispectral optoacoustic tomography (MSOT) allows in vivo 3D tumor imaging via gold nanoparticles or near-infrared dyes conjugated to a targeting molecule. Gemzar is used for first-line treatment of pancreatic adenocarcinoma, a malignancy with less than 5% survival at 5 years. We have created chitosan-capped mesoporous silica gold nanorods (C-MS-GNRs) to serve as pH sensitive theranostic nanoparticles for in vivo tumor imaging and targeted drug delivery. Methods: The chemical nature of all particles were characterized by electron microscopy, UV-Vis, and zeta-potential. Acidic pH specific Gemzar release was measured from C-MS-GNRs by UV-Vis. Cell viability assays on S2VP10 pancreatic adenocarcinoma cells with G-C-MS-GNR and Gemzar alone were performed at pH 6.5 and 7.4. S2VP10 cells were treated in pH 6.5 or 7.4 media with C-MS-GNR loaded with Indocyanin green (ICG) to demonstrate pH-sensitive cell targeting. ICG uptake was read on an Odyssey imaging system. Results: Particle characterization demonstrated appropriate chemical composition. A drug release assay of G-C-MS-GNR demonstrated 1/10 as much drug release at pH7.4 compared to in pH 6.4 or 6.0 media. Cell viability assays demonstrated enhanced cytotoxicity with Gemzar loaded C-MS-GNR at pH 6.5 and 7.4 compared to Gemzar alone. In vitro treatment of S2VP10 cells with C-MS-ICG in pH 6.5 media demonstrated 8X greater ICG delivery by C-MS-ICG than observed at pH 7.4. Conclusions: C-MS-GNR provides an efficacious means of targeting the acidic tumor environment for in vivo tumor imaging and drug delivery. C-MS-GNRs may be a suitable vehicle for tumor-targeted, pH-sensitive drug delivery to this currently untreatable tumor. Citation Format: Matthew Zeiderman, Anil Khanal, Charles W. Kimbrough, Jorge Gomez, William E. Grizzle, Kelly M. McMasters, Lacey R. McNally. Detection of pancreatic cancer using acidic pH targeted probes detected using multispectral optoacoustic tomography. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 5116. doi:10.1158/1538-7445.AM2015-5116

Mid-gut ACTH-secreting neuroendocrine tumor unmasked with (18)F-dihydroxyphenylalanine-positron emission tomography.

SummaryEctopic ACTH Cushing's syndrome (EAS) is often caused by neuroendocrine tumors (NETs) of lungs, pancreas, thymus, and other less frequent locations. Localizing the source of ACTH can be challenging. A 64-year-old man presented with rapidly progressing fatigue, muscular weakness, and dyspnea. He was in poor condition and showed facial redness, proximal amyotrophy, and bruises. Laboratory disclosed hypokalemia, metabolic alkalosis, and markedly elevated ACTH and cortisol levels. Pituitary was normal on magnetic resonance imaging (MRI), and bilateral inferior petrosal sinus blood sampling with corticotropin-releasing hormone stimulation showed no significant central-to-periphery gradient of ACTH. Head and neck, thoracic and abdominal computerized tomography (CT), MRI, somatostatin receptor scintigraphy (SSRS), and 18F-deoxyglucose-positron emission tomography (FDG-PET) failed to identify the primary tumor. 18F-dihydroxyphenylalanine (F-DOPA)-PET/CT unveiled a 20-mm nodule in the jejunum and a metastatic lymph node. Segmental jejunum resection showed two adjacent NETs, measuring 2.0 and 0.5 cm with a peritoneal metastasis. The largest tumor expressed ACTH in 30% of cells. Following surgery, after a transient adrenal insufficiency, ACTH and cortisol levels returned to normal values and remain normal over a follow-up of 26 months. Small mid-gut NETs are difficult to localize on CT or MRI, and require metabolic imaging. Owing to low mitotic activity, NETs are generally poor candidates for FDG-PET, whereas SSRS shows poor sensitivity in EAS due to intrinsically low tumor concentration of type-2 somatostatin receptors (SST2) or to receptor down regulation by excess cortisol. However, F-DOPA-PET, which is related to amine precursor uptake by NETs, has been reported to have high positive predictive value for occult EAS despite low sensitivity, and constitutes a useful alternative to more conventional methods of tumor localization.Learning points Uncontrolled high cortisol levels in EAS can be lethal if untreated.Surgical excision is the keystone of NETs treatment, thus tumor localization is crucial.Most cases of EAS are caused by NETs, which are located mainly in the lungs. However, small gut NETs are elusive to conventional imaging and require metabolic imaging for detection.FDG-PET, based on tumor high metabolic rate, may not detect NETs that have low mitotic activity. SSRS may also fail, due to absent or low concentration of SST2, which may be down regulated by excess cortisol.F-DOPA-PET, based on amine-precursor uptake, can be a useful method to localize the occult source of ACTH in EAS when other methods have failed.