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There is a clinical need to develop anatomic phantoms for simulation-based learning in gynecological brachytherapy. Here, we provide a step-by-step approach to build a life-sized gynecological training phantom based on magnetic resonance imaging (MRI) of an individual patient. Our hypothesis is that this phantom can generate convincing ultrasound (US) images that are similar to patient scans.Organs-at-risk were manually segmented using patient scans (MRI). The gynecological phantom was constructed using positive molds from 3D printing and polyvinyl chloride (PVC) plastisol. Tissue texture/acoustic properties were simulated using different plastic softener/hardener ratios and microbead densities. Nine readers (residents) were asked to evaluate 10 cases (1 ultrasound image per case) and categorize each as a "patient" or "phantom" image. To evaluate whether the phantom and patient images were equivalent, we used a multireader, multicase equivalence study design with two composite null hypotheses with proportion (pReaders correctly classified "patient" and "phantom" scans at pWe have outlined a manufacturing process to create a life-sized, gynecological phantom that is compatible with multi-modality imaging and can be used to simulate clinical scenarios in image-guided brachytherapy procedures.

This document contains suplementary data (Figure S1, Figure S2, Table S1, and Table S2). Each of these Figures and Tables has a detailed explanation for their calculations

Purpose:In glioma surgery, it is critical to maximize tumor resection without compromising adjacent noncancerous brain tissue. Optical coherence tomography (OCT) is a noninvasive, label-free, real-time, high-resolution imaging modality that has been explored for glioma infiltration detection. Here, we report a novel artificial intelligence (AI)-assisted method for automated, real-time, in situ detection of glioma infiltration at high spatial resolution.Experimental Design: Volumetric OCT datasets were intraoperatively obtained from resected brain tissue specimens of 21 patients with glioma tumors of different stages and labeled as either noncancerous or glioma-infiltrated on the basis of histopathology evaluation of the tissue specimens (gold standard). Labeled OCT images from 12 patients were used as the training dataset to develop the AI-assisted OCT-based method for automated detection of glioma-infiltrated brain tissue. Unlabeled OCT images from the other 9 patients were used as the validation dataset to quantify the method detection performance.Results:Our method achieved excellent levels of sensitivity (∼100%) and specificity (∼85%) for detecting glioma-infiltrated tissue with high spatial resolution (16 μm laterally) and processing speed (∼100,020 OCT A-lines/second).Conclusions:Previous methods for OCT-based detection of glioma-infiltrated brain tissue rely on estimating the tissue optical attenuation coefficient from the OCT signal, which requires sacrificing spatial resolution to increase signal quality, and performing systematic calibration procedures using tissue phantoms. By overcoming these major challenges, our AI-assisted method will enable implementing practical OCT-guided surgical tools for continuous, real-time, and accurate intraoperative detection of glioma-infiltrated brain tissue, facilitating maximal glioma resection and superior surgical outcomes for patients with glioma.

Sweep animation for a predicted cancer-free OCT volume

Sweep animation for a predicted cancer-infiltrated OCT volume

Rotation animation of a predicted cancer-infiltrated OCT volume

Rotation animation of a predicted cancer-free OCT volume

Case Presentation A 55-year-old man presented to the ED with a 3-week history of worsening cough and shortness of breath. He had blood-tinged sputum, fever, night sweats, and a 2.7 kg weight loss within the same period. For the past few days, he had taken amoxicillin-clavulanate for presumed sinusitis. Despite this, his symptoms persisted, prompting him to seek further evaluation. His medical history was significant for ulcerative colitis and he had some bloody diarrhea for the past few weeks. Medications included aspirin, mesalamine, multivitamins, folic acid, and herbal supplements including gingko biloba, ginseng, and turmeric-ginger. He never smoked and drank alcohol occasionally. Family history was notable for stroke and myocardial infarction.

Purpose: In glioma surgery, it is critical to maximize tumor resection without compromising adjacent noncancerous brain tissue. Optical coherence tomography (OCT) is a noninvasive, label-free, real-time, high-resolution imaging modality that has been explored for glioma infiltration detection. Here, we report a novel artificial intelligence (AI)-assisted method for automated, real-time, in situ detection of glioma infiltration at high spatial resolution. Experimental Design: Volumetric OCT datasets were intraoperatively obtained from resected brain tissue specimens of 21 patients with glioma tumors of different stages and labeled as either noncancerous or glioma-infiltrated on the basis of histopathology evaluation of the tissue specimens (gold standard). Labeled OCT images from 12 patients were used as the training dataset to develop the AI-assisted OCT-based method for automated detection of glioma-infiltrated brain tissue. Unlabeled OCT images from the other 9 patients were used as the validation dataset to quantify the method detection performance. Results: Our method achieved excellent levels of sensitivity (∼100%) and specificity (∼85%) for detecting glioma-infiltrated tissue with high spatial resolution (16 μm laterally) and processing speed (∼100,020 OCT A-lines/second). Conclusions: Previous methods for OCT-based detection of glioma-infiltrated brain tissue rely on estimating the tissue optical attenuation coefficient from the OCT signal, which requires sacrificing spatial resolution to increase signal quality, and performing systematic calibration procedures using tissue phantoms. By overcoming these major challenges, our AI-assisted method will enable implementing practical OCT-guided surgical tools for continuous, real-time, and accurate intraoperative detection of glioma-infiltrated brain tissue, facilitating maximal glioma resection and superior surgical outcomes for patients with glioma.

OBJECTIVE Subependymomas are low-grade ependymal tumors whose clinical characteristics, radiographic features, and postsurgical outcomes are incompletely characterized due to their rarity. The authors present an institutional case series and a systematic literature review to achieve a better understanding of subependymomas. METHODS Adult patients with histologically confirmed subependymoma or mixed subependymoma-ependymoma surgically treated at a tertiary hospital between 1992 and 2020 were identified. A systematic literature review of the PubMed, Embase, Web of Science, and Google Scholar databases from inception until December 4, 2020, was conducted according to PRISMA guidelines. Data extracted from both groups included demographics, radiographic features, tumor characteristics, management, and follow-up variables. RESULTS Forty-eight unique patients with subependymoma were identified by chart review; of these patients, 8 (16.7%) had mixed subependymoma-ependymoma tumors. The median age at diagnosis was 49 years (IQR 19.8 years), and 26 patients (54.2%) were male. Forty-two patients (87.5%) had intracranial subependymomas, and 6 (12.5%) had spinal tumors. The most common presentation was headache (n = 20, 41.7%), although a significant number of tumors were diagnosed incidentally (n = 16, 33.3%). Among the 42 patients with intracranial tumors, 15 (35.7%) had hydrocephalus, and the most common surgical strategy was a suboccipital approach with or without C1 laminectomy (n = 26, 61.9%). Gross-total resection (GTR) was achieved in 33 cases (68.7%), and 2 patients underwent adjuvant radiotherapy. Most patients had no major postsurgical complications (n = 34, 70.8%), and only 1 (2.1%) had recurrence after GTR. Of 2036 reports initially identified in the systematic review, 39 were eligible for inclusion, comprising 477 patients. Of 462 patients for whom tumor location was reported, 406 (87.9%) were intracranial, with the lateral ventricle as the most common location (n = 214, 46.3%). Spinal subependymomas occurred in 53 patients (11.5%), with 3 cases (0.6%) in multiple locations. Similar to the case series at the authors’ institution, headache was the most common presenting symptom (n = 231, 54.0%) among the 428 patients whose presentation was reported. Twenty-seven patients (6.3%) were diagnosed incidentally, and 36 cases (8.4%) were found at autopsy. Extent of resection was reported for 350 patients, and GTR was achieved in 250 (71.4%). Fifteen of 337 patients (4.5%) had recurrence or progression. CONCLUSIONS The authors’ case series and literature review demonstrate that patients with subependymoma are well managed with resection and generally have a favorable prognosis.

Background: Frozen section and smear preparation are the current standard for intraoperative histopathology during cancer surgery. However, these methods are time-consuming and subject to limited sampling. Multiphoton microscopy (MPM) is a high-resolution non-destructive imaging technique capable of optical sectioning in real time with subcellular resolution. In this report, we systematically investigated the feasibility and translation potential of MPM for rapid histopathological assessment of label- and processing-free surgical specimens. Methods: We employed a customized MPM platform to capture architectural and cytological features of biological tissues based on two-photon excited NADH and FAD autofluorescence and second harmonic generation from collagen. Infiltrating glioma, an aggressive disease that requires subcellular resolution for definitive characterization during surgery, was chosen as an example for this validation study. MPM images were collected from resected brain specimens of 19 patients and correlated with histopathology. Deep learning was introduced to assist with image feature recognition. Results: MPM robustly captures diagnostic features of glioma including increased cellularity, cellular and nuclear pleomorphism, microvascular proliferation, necrosis, and collagen deposition. Preliminary application of deep learning to MPM images achieves high accuracy in distinguishing gray from white matter and cancer from non-cancer. We also demonstrate the ability to obtain such images from intact brain tissue with a multiphoton endomicroscope for intraoperative application. Conclusion: Multiphoton imaging correlates well with histopathology and is a promising tool for characterization of cancer and delineation of infiltration within seconds during brain surgery.

Lymphopenia is associated with decreased survival outcomes in head and neck squamous cell carcinoma (HNSCC). This is a significant concern especially for frail individuals who are more vulnerable to immunological dysregulations. A robust analysis is needed to understand whether we should expend efforts to limit treatment-related hematological toxicities in HNSCC. First, we would like to understand the prognostic significance for baseline (BL) vs. treatment-related lymphopenia (TRL). We want to know if lymphopenia is merely a reflection of the patient’s frailty at baseline, or if this is iatrogenic and therefore can be a target for treatment modifications in a bid to improve survival. Here, we identified 222 newly diagnosed M0 HNSCC patients treated with radiation ± systemic therapy in 2015-2018 at our institution. Clinical frailty is defined by age ≥ 65 or KPS ≤ 70. Using Kaplan Meier estimates and Cox regression with dichotomous variables, we performed multivariate analysis for both overall survival (OS) and progression-free survival (PFS). Important predictors included frailty (p ≤ 0.002) and ≥ 2K/mm3 decrease in absolute lymphocyte counts (ALC) (p ≤ 0.006). BL did not significantly impact OS or PFS (p ≤ 0.37). For TRL, ALC decrease had greater prognostic significance compared with ALC nadirs (p ≤ 0.45). Next, we simplified our survival model to include only frailty and TRL. Overall, fit patients with modest ALC decline (< 2K/mm3) achieved excellent survival outcomes while frail patients with severe ALC decline (≥ 2K/mm3) had inferior outcomes (3-year OS 95% vs. 56%, p < 0.0001; 3-year PFS 84% vs. 42%, p = 0.002). On subgroup analyses, similar outcomes were also identified for HPV+ HNSCC (n = 172, 3-year OS 96% vs. 71%, p = 0.002; 3-year PFS 89% vs. 54% p = 0.03). Finally, we want to know if ALC decline is determined primarily by treatment intensity, or if frail patients are naturally predisposed to greater ALC decline during treatment. In our data, frail patients had more modest ALC decline when compared to fit patients (1.26 ± 0.57 vs. 1.54 ± 0.58 K/mm3 p = 0.0006). In our survival model, we did not observe any first-order interactions between frailty and ALC decline (p = 0.54). The extent of ALC decline was also higher for patients with concurrent administrations of cisplatin (as opposed to radiation alone, p < 0.0001). Thus, we postulate that the extent of ALC decline is determined primarily by treatment intensity. It is possible that frail patients with severe ALC decline have inferior survival outcomes because they cannot maintain immunological balance and respond poorly when there is significant TRL. This opens opportunities to re-evaluate if the risk of TRL is modifiable by limiting the number of concurrent cycles of chemotherapy administered, and by considering radiation dose de-intensification especially for HPV-associated HNSCC. Lastly, TRL becomes an important consideration when immunotherapeutics are grafted onto existing CRT treatment paradigms. Citation Format: Carmen Kut, Todd McNutt, Carole Fakhry, Theodore DeWeese, Harry Quon. Lymphocyte kinetics, frailty and survival outcomes in HNSCC [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1971.

We present a 60-year-old man with recurrent follicular thyroid cancer (initially staged pT4aN0M0) with multiple high-risk features including poorly differentiated histology with insular component, extrathyroidal extension with involvement of the cricoid, trachea and esophagus, and recurrence after prior radioactive iodine treatment. He underwent extensive surgical resection including total laryngectomy, bilateral neck dissection, tracheal shave resection, and cricopharyngeal myotomy. A tracheoesophageal puncture (TEP) was performed with placement of a voice prosthesis. He was treated with adjuvant external beam radiotherapy (EBRT) to the neck. Subsequent systemic therapies included the antiangiogenic multi-kinase inhibitors lenvatinib and pazopanib. Over time, he developed a tracheoesophageal fistula requiring multiple surgical interventions, enteral feeding, and therapy changes. In this case report, we discuss risk factors for fistularization including TEP prosthesis, adjuvant EBRT, and antiangiogenic therapy, and we discuss strategies to minimize and manage treatment-related toxicities.

In brain cancer surgery, maximal tumor resection improves overall survival and quality of life survival in low-grade and high-grade glioma. Different technologies such as intraoperative magnetic resonance imaging and computed tomography have made major contributions; however, these technologies do not provide quantitative, real-time and three-dimensional continuous guidance. Optical Coherence Tomography (OCT) is a non-invasive, label-free, real-time, high-resolution imaging modality that has been explored for glioma infiltration detection. Here we report a novel Artificial Neural Network (ANN)-based computer-aided diagnosis (CAD) method for automated, real-time, in situ detection of glioma-infiltrated tumor margins. Near 500 volumetric OCT samples were intraoperatively obtained from resected brain tissue specimens of 21 patients with glioma tumors of different stages and labeled as either non-cancerous or glioma-infiltrated based on histopathology evaluation (gold standard). Labeled OCT images from 12 patients were used as training dataset to develop the artificial neural network. Unlabeled OCT images from the other 9 patients were used as a validation dataset to quantify the method detection performance. The CAD system achieved excellent levels of both sensitivity and specificity (~90%) for detecting glioma-infiltrated tissue with high spatial resolution (~16 μm laterally). Previous methods for OCT-based detection of glioma-infiltrated brain tissue rely on underlying optical properties such as attenuation coefficient from the OCT signal requiring sacrificing spatial resolution and cumbersome calibration procedures. By overcoming these major challenges, our novel ANN-assisted CAD system will enable implementing practical OCT-guided surgical tools for continuous, real-time and accurate intra-operative detection of glioma-infiltrated brain tissue, facilitating maximal glioma resection and superior surgical outcomes for glioma patients.

PURPOSE/OBJECTIVE(S) Severe lymphopenia during chemoradiation is often associated with higher risk of death, disease progression and distant metastases. Recent data has shown that head and neck cancer (HNC) patients with lymphopenia has a decreased 5-year overall survival of 70 vs 90%. While both radiation and chemotherapy have been associated with lymphopenia, the mechanism of action remains unclear. Here, we propose a spatially-defined model that evaluates the combined effects of lymphotoxic radiation doses to head and neck organs-at-risk (HN-OARs) which include the cervical bone marrow and the circulating blood pool. Our objective is to investigate the spatial dose relationships related to treatment-related lymphopenia (TRL) in HNC patients. MATERIALS/METHODS We have identified a prospectively acquired dataset of 40 HNC patients treated at our institution with 31 oropharynx, 3 oral cavity, 4 nasopharynx and 2 larynx cases. Weekly lymphocyte counts were extracted at baseline and for 8 weeks since initiation of radiotherapy. Chemotherapy timing, dosage and regimens were documented. HN-OARs were manually contoured on CT simulation scans. To generate the spatially-defined linear regression model, we included these inputs (x): internal jugular veins (IJVs), carotid arteries (CAs), capillary bed (CB) and vertebral bodies (VBs). The output (y) is defined by % decrease between baseline and nadir lymphocyte counts. Then, we segmented VBs by vertebral levels, and other HN-OARs by disease laterality (ipsilateral vs contralateral). IJVs and CAs are further segmented by anatomic zones (zone 1: C1 to hyoid, zone 2: hyoid to cricoid, and zone 3: cricoid to C7). Stepwise selection was used to identify influential HN-OARs. Finally, we proposed spatial dose parameters associated with high risk lymphopenia (defined as ≥70% decrease) and performed sensitivity/specificity (Se/Sp) analyses. RESULTS Using stepwise (forward) selection, we identified IJVs as potential targets to spare low dose bath parameters Dmin and D90 (P-values 0.028 to 0.056), and VBs as potential targets to spare point max doses Dmax and D10 (P-values < 0.001 to 0.020). To avoid overfitting, we also performed backward selection with a more liberal P-value criterion of 0.50 which showed similar results. Key anatomic zones for potential dose sparing include C1-3 VBs and contralateral zone 1 IJVs. Overall, we proposed these dose parameters to limit TRL risks: Dmax ≤ 60 Gy for VBs (Se/Sp: 76%/86%, AUC 0.84) and D90 ≤ 13 Gy for contralateral IJVs (Se/Sp: 72%/86%, AUC 0.79). CONCLUSION The risk of treatment-related lymphopenia (TRL) appears to be spatially related to radiation doses to the VBs and IJVs. Better understanding of the spatial dose relationship with HN-OARs may lead to insights in reducing TRL risks and improving oncologic outcomes, especially as we consider the benefits of recent dose de-escalation studies (to reduce point max doses) and proton treatment techniques (to reduce low dose baths) in the management of head and neck cancers.

Gliomas are CNS neoplasms that infiltrate the surrounding brain parenchyma, complicating their treatment. Tools that increase extent of resection while preventing neurological deficit are essential to improve prognosis of patients diagnosed with gliomas. Tools such as intraoperative MRI, ultrasound and fluorescence-guided microsurgery have been used in the surgical resection of CNS gliomas with the goal of maximizing extent of resection to improve patient outcomes. In addition, emerging experimental techniques, for example, optical coherence tomography and Raman spectroscopy are promising techniques which could 1 day add to the increasing armamentarium used in the surgical resection of CNS gliomas. Here, we present the potential advantages and limitations of these imaging techniques for the purposes of identifying gliomas in the operating room.

PURPOSE: In glioma surgery, it is critical to maximize tumor resection without compromising adjacent non-cancerous brain tissue. Optical Coherence Tomography (OCT) is a non-invasive, label-free, real-time, high-resolution imaging modality that has been explored for glioma infiltration detection. Here we report a novel artificial intelligence (AI) assisted method for automated, real-time, in situ detection of glioma infiltration at high spatial resolution. EXPERIMENTAL DESIGN: Volumetric OCT datasets were intraoperatively obtained from resected brain tissue specimens of 21 patients with glioma tumors of different stages and labeled as either non-cancerous or glioma-infiltrated based on histopathology evaluation of the tissue specimens (gold standard). Labeled OCT images from 12 patients were used as the training dataset to develop the AI assisted OCT-based method for automated detection of glioma-infiltrated brain tissue. Unlabeled OCT images from the other 9 patients were used as the validation dataset to quantify the method detection performance. RESULTS: Our method achieved excellent levels of sensitivity (~100%) and specificity (~85%) for detecting glioma-infiltrated tissue with high spatial resolution (16 μm laterally) and processing speed (~100,020 OCT A-lines/second). CONCLUSIONS: Previous methods for OCT-based detection of glioma-infiltrated brain tissue rely on estimating the tissue optical attenuation coefficient from the OCT signal, which requires sacrificing spatial resolution to increase signal quality, and performing systematic calibration procedures using tissue phantoms. By overcoming these major challenges, our AI-assisted method will enable implementing practical OCT-guided surgical tools for continuous, real-time and accurate intra-operative detection of glioma-infiltrated brain tissue, facilitating maximal glioma resection and superior surgical outcomes for glioma patients.

In brain cancer surgery, it is critical to achieve extensive resection without compromising adjacent healthy, non-cancerous regions. Various technological advances have made major contributions in imaging, including intraoperative magnetic imaging (MRI) and computed tomography (CT). However, these technologies have pros and cons in providing quantitative, real-time and three-dimensional (3D) continuous guidance in brain cancer detection. Optical Coherence Tomography (OCT) is a non-invasive, label-free, cost-effective technique capable of imaging tissue in three dimensions and real time. The purpose of this study is to reliably and efficiently discriminate between non-cancer and cancer-infiltrated brain regions using OCT images. To this end, a mathematical model for quantitative evaluation known as the Blind End- Member and Abundances Extraction method (BEAE). This BEAE method is a constrained optimization technique which extracts spatial information from volumetric OCT images. Using this novel method, we are able to discriminate between cancerous and non-cancerous tissues and using logistic regression as a classifier for automatic brain tumor margin detection. Using this technique, we are able to achieve excellent performance using an extensive cross-validation of the training dataset (sensitivity 92.91% and specificity 98.15%) and again using an independent, blinded validation dataset (sensitivity 92.91% and specificity 86.36%). In summary, BEAE is well-suited to differentiate brain tissue which could support the guiding surgery process for tissue resection.

We present recent updates on quantitative OCT for guiding brain cancer surgery in real time. Results from pilot intra-operative imaging of more than 20 human subject will be discussed.

Cancer is known to alter the local optical properties of tissues. The detection of OCT-based optical attenuation provides a quantitative method to efficiently differentiate cancer from non-cancer tissues. In particular, the intraoperative use of quantitative OCT is able to provide a direct visual guidance in real time for accurate identification of cancer tissues, especially these without any obvious structural layers, such as brain cancer. However, current methods are suboptimal in providing high-speed and accurate OCT attenuation mapping for intraoperative brain cancer detection. In this paper, we report a novel frequency-domain (FD) algorithm to enable robust and fast characterization of optical attenuation as derived from OCT intensity images. The performance of this FD algorithm was compared with traditional fitting methods by analyzing datasets containing images from freshly resected human brain cancer and from a silica phantom acquired by a 1310 nm swept-source OCT (SS-OCT) system. With graphics processing unit (GPU)-based CUDA C/C++ implementation, this new attenuation mapping algorithm can offer robust and accurate quantitative interpretation of OCT images in real time during brain surgery.

Summary Background During laparoscopic or robotic assisted laparoscopic prostatectomy, the surgeon lacks tactile feedback which can help him tailor the size of the excision. Ultrasound elastography (USE) is an emerging imaging technology which maps the stiffness of tissue. In the paper we are evaluating USE as a palpation equivalent tool for intraoperative image guided robotic assisted laparoscopic prostatectomy. Material/Methods Two studies were performed: 1) A laparoscopic ultrasound probe was used in a comparative study of manual palpation versus USE in detecting tumor surrogates in synthetic and ex-vivo tissue phantoms; N=25 participants (students) were asked to provide the presence, size and depth of these simulated lesions, and 2) A standard ultrasound probe was used for the evaluation of USE on ex-vivo human prostate specimens (N=10 lesions in N=6 specimens) to differentiate hard versus soft lesions with pathology correlation. Results were validated by pathology findings, and also by in-vivo and ex-vivo MR imaging correlation. Results In the comparative study, USE displayed higher accuracy and specificity in tumor detection (sensitivity=84%, specificity=74%). Tumor diameters and depths were better estimated using USE versus with manual palpation. USE also proved consistent in identification of lesions in ex-vivo prostate specimens; hard and soft, malignant and benign, central and peripheral. Conclusions USE is a strong candidate for assisting surgeons by providing palpation equivalent evaluation of the tumor location, boundaries and extra-capsular extension. The results encourage us to pursue further testing in the robotic laparoscopic environment.

More complete brain cancer resection can prolong survival and delay recurrence. However, it is challenging to distinguish cancer from noncancer tissues intraoperatively, especially at the transitional, infiltrative zones. This is especially critical in eloquent regions (for example, speech and motor areas). This study tested the feasibility of label-free, quantitative optical coherence tomography (OCT) for differentiating cancer from noncancer in human brain tissues. Fresh ex vivo human brain tissues were obtained from 32 patients with grade II to IV brain cancer and 5 patients with noncancer brain pathologies. On the basis of volumetric OCT imaging data, pathologically confirmed brain cancer tissues (both high- and low-grade) had significantly lower optical attenuation values at both cancer core and infiltrated zones when compared with noncancer white matter, and OCT achieved high sensitivity and specificity at an attenuation threshold of 5.5 mm(-1) for brain cancer patients. We also used this attenuation threshold to confirm the intraoperative feasibility of performing in vivo OCT-guided surgery using a murine model harboring human brain cancer. Our OCT system was capable of processing and displaying a color-coded optical property map in real time at a rate of 110 to 215 frames per second, or 1.2 to 2.4 s for an 8- to 16-mm(3) tissue volume, thus providing direct visual cues for cancer versus noncancer areas. Our study demonstrates the translational and practical potential of OCT in differentiating cancer from noncancer tissue. Its intraoperative use may facilitate safe and extensive resection of infiltrative brain cancers and consequently lead to improved outcomes when compared with current clinical standards.

The purpose of this critical review is to explore the controversy regarding the relationship between radiation dose to the neural progenitor cell (NPC) niches and patient outcomes, in terms of both toxicity and tumor control. NPCs in the subventricular zone (SVZ) and hippocampus are paradoxically associated with long-term neurocognitive sequelae of brain irradiation, as well as resistance to therapy and tumor recurrence. The reconciliation of these somewhat opposing functions is challenging. Current literature suggests that radiation and other treatments against the NPC in the hippocampus and the SVZ may influence patient outcome. As a result, both the SVZ and the hippocampus could have important implications on radiation treatment planning strategies, and future laboratory and clinical evaluations will be critical in designing studies to optimize treatment outcome, effectiveness, and safety.

This study uses OCT and optical property mapping to detect brain tumors in vivo in mice bearing human glioblastoma and in fresh ex vivo brain tissues from 32 patients with high sensitivity and specificity.

Aim: To assess the potential for injury to normal tissues in mice due to heating systemically delivered magnetic nanoparticles in an alternating magnetic field (AMF). Materials & methods: Twenty three male nude mice received intravenous injections of dextran–superparamagnetic iron oxide nanoparticles on days 1–3. On day 6, they were exposed to AMF. On day 7, blood, liver and spleen were harvested and analyzed. Results: Iron deposits were detected in the liver and spleen. Mice that had received a high-particle dose and a high AMF experienced increased mortality, elevated liver enzymes and significant liver and spleen necrosis. Mice treated with low-dose superparamagnetic iron oxide nanoparticles and a low AMF survived, but had elevated enzyme levels and local necrosis in the spleen. Conclusion: Magnetic nanoparticles producing only modest heat output can cause damage, and even death, when sequestered in sufficient concentrations. Dextran–superparamagnetic iron oxide nanoparticles are deposited in the liver and spleen, making these the sites of potential toxicity. Original submitted 16 August 2011; Revised submitted 21 March 2012; Published online 26 July 2012

Ex vivo human brain tissues from 8 glioma patients and 5 controls are imaged using SS-OCT, with higher glioma attenuation values and easily detectable and specific tumor features (microcyst, necrosis and pallisading) for intraoperative resections.

Purpose To determine whether frameless thermoplastic mask-based immobilization is adequate for image-guided cranial radiosurgery. Methods and Materials Cone-beam CT localization data from patients with intracranial tumors were studied using daily pre- and posttreatment scans. The systems studied were ( 1 ) Type-S IMRT (head only) mask (Civco) with head cushion; ( 2 ) Uni-Frame mask (Civco) with head cushion, coupled with a BlueBag body immobilizer (Medical Intelligence); ( 3 ) Type-S head and shoulder mask with head and shoulder cushion (Civco); ( 4 ) same as previous, coupled with a mouthpiece. The comparative metrics were translational shift magnitude and average rotation angle; systematic inter-, random inter-, and random intrafraction positioning error was computed. For strategies 1–4, respectively, the analysis for interfraction variability included data from 20, 9, 81, and 11 patients, whereas that for intrafraction variability included a subset of 7, 9, 16, and 8 patients. The results were compared for statistical significance using an analysis of variance test. Results Immobilization system 4 provided the best overall accuracy and stability. The mean interfraction translational shifts (± SD) were 2.3 (± 1.4), 2.2 (± 1.1), 2.7 (± 1.5), and 2.1 (± 1.0) mm whereas intrafraction motion was 1.1 (± 1.2), 1.1 (± 1.1), 0.7 (± 0.9), and 0.7 (± 0.8) mm for devices 1–4, respectively. No significant correlation between intrafraction motion and treatment time was evident, although intrafraction motion was not purely random. Conclusions We find that all frameless thermoplastic mask systems studied are viable solutions for image-guided intracranial radiosurgery. With daily pretreatment corrections, symmetric PTV margins of 1 mm would likely be adequate if ideal radiation planning and targeting systems were available.

Purpose: To compare the accuracy of detecting tumor location and size in the prostate using both manual palpation and ultrasound elastography (UE). Methods: Tumors in the prostate were simulated using both synthetic and ex vivo tissue phantoms. 25 participants were asked to provide the presence, size and depth of these simulated lesions using manual palpation and UE. Ultrasound images were captured using a laparoscopic ultrasound probe, fitted with a Gore-Tetrad transducer with frequency of 7.5 MHz and a RF capture depth of 4-5 cm. A MATLAB GUI application was employed to process the RF data for ex vivo phantoms, and to generate UE images using a cross-correlation algorithm. Ultrasonix software was used to provide real time elastography during laparoscopic palpation of the synthetic phantoms. Statistical analyses were performed based on a two-tailed, student t-test with α = 0.05. Results: UE displays both a higher accuracy and specificity in tumor detection (sensitivity = 84%, specificity = 74%). Tumor diameters and depths are better estimated using ultrasound elastography when compared with manual palpation. Conclusions: Our results indicate that UE has strong potential in assisting surgeons to intra-operatively evaluate the tumor depth and size. We have also demonstrated that ultrasound elastography can be implemented in a laparoscopic environment, in which manual palpation would not be feasible. With further work, this application can provide accurate and clinically relevant information for surgeons during prostate resection.

Figure 1 in the above-referenced article was publishedwithout an acknowledgment in error. The figure should have been credited as follows:© 2006MediVisuals Inc. Reprintedwith permission fromBarani IJ, Benedict SH, Lin PS, “Neural stem cells: implications for the conventional radiotherapy of central nervous systemmalignancies,” Int J RadiatOncol Biol Phys 68(2):324-333, 2007.We regret the omission.

The blood-brain barrier (BBB), with its charged, lipid-based, continuous basement membrane and specialized transporters, is optimized to exclude potentially threatening compounds from the central nervous system (CNS). In the setting of CNS diseases, the careful construction of the BBB is thought to restrict access of therapeutic agents that may otherwise be effective, contributing to poorer outcomes. However, there is controversy in the neurotherapeutics community about the degree to which this hypothesis is true; some argue that the BBB is not the critical factor because it naturally opens in the setting of brain pathology and that techniques to circumvent the BBB do not improve drug efficacy in many instances.1 Moreover, some drugs do not need direct access to brain tissue in order to have their therapeutic effect. For example, fingolimod and bevacizumab are effective in patients with multiple sclerosis and glioblastoma, respectively, although their primary mechanism of action is systemic. Additionally, in some brain tumors, achieving target drug concentrations in the brain either fails to show efficacy or, in fact, causes toxicity.2 In these instances, the factor impeding success of neurotherapeutics is clearly not the BBB.

Purpose: To improve the utility of in‐room video‐based system for continuous quantitative monitoring of patient motion independent of environmental changes in lighting and geometry. Method and Materials: A video‐based tracking system was developed using a webcam with 600 by 450 pixels and Microsoft Visual C++. It is mounted at the end of the treatment couch to constantly view a specified region on the patient's torso of 50 cm by 30 cm at 55 degrees viewing angle. Small high contrast “sticky” markers are placed within the viewing region for easy detection. Environmental disturbances such as changes in machine positions and lightings are minimized through appropriate real‐time image subtraction and processing techniques. An alarm is activated when the patient movement is deemed out‐of‐tolerance. For validation, a lead ball phantom and a flat “sticky” marker of 1 cm diameter each were used to determine detectable target displacements. Each tracking session was automatically recorded for further data analysis. Pre‐clinical evaluations were performed on two subjects. Results: Target displacements of (2, 2, 5) mm for the lead ball phantom and (4,4,7) mm for the flat phantom are readily detected in the lateral, superior‐inferior and vertical directions respectively. Most importantly, the system detects these changes in the presence of environmental disturbances which include large changes in room lighting, and couch and gantry positions. The system fails when the camera's view is obstructed. Conclusion: Our system provides an effective approach to track and monitor patient position after highly accurate setup, such as using cone‐beam CT. It is considerably lower in cost relative to existing commercial tracking systems. The use of more optimal markers and 2 cameras are under investigation to improve detection resolution. With further refinement, the system can be adapted for routine clinical use that is superior to present in‐room video‐monitoring systems.

INTRODUCTION: Tumor cells are passively carried by extracellular fluid flow to regional lymph nodes in most systemic cancers including breast cancer, melanoma and colorectal cancer. Although the brain does not contain lymphatics, cancer spread within the brain may be a function of extracellular fluid velocity. As malignant brain tumors are characterized by a disrupted blood-brain-barrier that leaks albumin from blood vessels into brain parenchyma, we hypothesize that this albumin influx will pull water in osmotically and increase flow rates and glioma cell dissemination down adjacent white matter tracts. High flow rates may increase tumor dissemination via the WMT. This study sought to determine if increasing intracranial albumin concentrations affect WMT flow rates. If true, restricting albumin extravasation (through steroids or VEGF inhibitors) has the potential to reduce glioma dissemination and may have implications for future radiation planning and steroid/VEGF inhibitor dosing. METHODS: Our study examines flow rates in white matter tracts after intracranial administration of albumin. 0.12-6 mg bovine albumin were mixed with 20 μL of 2% Evans Blue and injected stereotactically into the right frontal lobe at the gray-white matter junction over 80 minutes in 15 anesthetized Sprague-Dawley female rats. Seven hours later, the rats were sacrificed and the brains sectioned into 0.5mm coronal slices, and imaged to determine interstitial flow rates. RESULTS: Average anterior-posterior (AP) velocity for rats receiving 0.12 mg and 6.0 mg of albumin were 0.43 and 1.02 mm/hour respectively (p = 0.029). Correlation was observed between administered albumin dose and interstitial fluid velocity (R = 0.57). In vivo MRI results were consistent with ex vivo Evans blue results and demonstrate markedly increased edema (T2) in the hemisphere where albumin was injected. CONCLUSIONS: This study demonstrates higher interstitial fluid flow rates in adjacent white matter tracts in response to albumin-induced-edema. These observations provide insight into expected pathways for glioma dissemination which could be used to tailor radiation plans for individual patients. Furthermore, these findings provide a rationale for interventions to reduce glioma dissemination by limiting the extravasation of albumin through the blood-brain-barrier while local radiation is being administered. Citation Format: Carmen Kut, Vadappuram Chacko, Betty Tyler, Arvind P. Pathak, Zaver Bhujwalla, Elliot R. McVeigh, Xingde Li, Daniel A. Herzka, Stuart A. Grossman. Determining extracellular fluid velocity along white matter tracts with injections of increasing concentrations of intracranial albumin using both histological and radiological techniques. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 3931. doi:10.1158/1538-7445.AM2013-3931

Background Analysis and design of complex systems benefit from mathematically tractable models, which are often derived by approximating a nonlinear system with an effective equivalent linear system. Biological oscillators with coupled positive and negative feedback loops, termed hysteresis or relaxation oscillators, are an important class of nonlinear systems and have been the subject of comprehensive computational studies. Analytical approximations have identified criteria for sustained oscillations, but have not linked the observed period and phase to compact formulas involving underlying molecular parameters. Results We present, to our knowledge, the first analytical expressions for the period and amplitude of a classic model for the animal circadian clock oscillator. These compact expressions are in good agreement with numerical solutions of corresponding continuous ODEs and for stochastic simulations executed at literature parameter values. The formulas are shown to be useful by permitting quick comparisons relative to a negative-feedback represillator oscillator for noise (10× less sensitive to protein decay rates), efficiency (2× more efficient), and dynamic range (30 to 60 decibel increase). The dynamic range is enhanced at its lower end by a new concentration scale defined by the crossing point of the activator and repressor, rather than from a steady-state expression level. Conclusion Analytical expressions for oscillator dynamics provide a physical understanding for the observations from numerical simulations and suggest additional properties not readily apparent or as yet unexplored. The methods described here may be applied to other nonlinear oscillator designs and biological circuits.