•LITT is difficult after craniectomy due to lack of bony surface to anchor the bolt.•A 3D-printed implant was used to enable LITT targeting of a posterior fossa lesion.•The customized plate had a ...built-in bolt trajectory that aligned with the tumor.•The customized plate was implemented under the FDA expanded access pathway.•This strategy enables use of LITT in patients who would not otherwise be candidates.
Laser interstitial thermal therapy (LITT) is a minimally invasive neurosurgical technique that has been demonstrated to successfully ablate intracranial tumors. While LITT for supratentorial lesions can often be straightforward, ablation of infratentorial lesions can be difficult with current targeting technologies and instrumentation. The anatomical difficulty of targeting posterior fossa masses can be further complicated in patients who have had a prior craniectomy or other procedure that removed the bone that is required to set the surgical trajectory. This article describes use of a three-dimensional (3D)–printed customized surgical implant to improve and enable targeting of posterior fossa lesions using LITT, particularly in the setting of prior craniectomy. A 3D-printed implant was customized for a patient with a history of metastatic lung cancer and prior posterior fossa craniectomy who presented for treatment of a progressively enlarging contrast-enhancing lesion in the right cerebellar hemisphere. The device included a built-in bolt trajectory for LITT ablation. The temporary implant was successfully fabricated for use with laser ablation of a right cerebellar mass. Three potential trajectories for the LITT bolt were incorporated into the temporary implant, but only the primary trajectory was utilized. Laser ablation was performed with the implant and a SideFire laser probe. Customized 3D-printed implants can enable the use of LITT for patients who would not otherwise be candidates.
Differentiating tumor from normal brain is a major barrier to achieving optimal outcome in brain tumor surgery. New imaging techniques for visualizing tumor margins during surgery are needed to ...improve surgical results. We recently demonstrated the ability of stimulated Raman scattering (SRS) microscopy, a nondestructive, label-free optical method, to reveal glioma infiltration in animal models. We show that SRS reveals human brain tumor infiltration in fresh, unprocessed surgical specimens from 22 neurosurgical patients. SRS detects tumor infiltration in near-perfect agreement with standard hematoxylin and eosin light microscopy (κ = 0.86). The unique chemical contrast specific to SRS microscopy enables tumor detection by revealing quantifiable alterations in tissue cellularity, axonal density, and protein/lipid ratio in tumor-infiltrated tissues. To ensure that SRS microscopic data can be easily used in brain tumor surgery, without the need for expert interpretation, we created a classifier based on cellularity, axonal density, and protein/lipid ratio in SRS images capable of detecting tumor infiltration with 97.5% sensitivity and 98.5% specificity. Quantitative SRS microscopy detects the spread of tumor cells, even in brain tissue surrounding a tumor that appears grossly normal. By accurately revealing tumor infiltration, quantitative SRS microscopy holds potential for improving the accuracy of brain tumor surgery.
One important function of endothelial cells in glioblastoma multiforme (GBM) is to create a niche that helps promote self-renewal of cancer stem-like cells (CSLC). However, the underlying molecular ...mechanism for this endothelial function is not known. Since activation of NOTCH signaling has been found to be required for propagation of GBM CSLCs, we hypothesized that the GBM endothelium may provide the source of NOTCH ligands. Here, we report a corroboration of this concept with a demonstration that NOTCH ligands are expressed in endothelial cells adjacent to NESTIN and NOTCH receptor-positive cancer cells in primary GBMs. Coculturing human brain microvascular endothelial cells (hBMEC) or NOTCH ligand with GBM neurospheres promoted GBM cell growth and increased CSLC self-renewal. Notably, RNAi-mediated knockdown of NOTCH ligands in hBMECs abrogated their ability to induce CSLC self-renewal and GBM tumor growth, both in vitro and in vivo. Thus, our findings establish that NOTCH activation in GBM CSLCs is driven by juxtacrine signaling between tumor cells and their surrounding endothelial cells in the tumor microenvironment, suggesting that targeting both CSLCs and their niche may provide a novel strategy to deplete CSLCs and improve GBM treatment.
Accurate specimen analysis of skull base tumors is essential for providing personalized surgical treatment strategies. Intraoperative specimen interpretation can be challenging because of the wide ...range of skull base pathologies and lack of intraoperative pathology resources.
To develop an independent and parallel intraoperative workflow that can provide rapid and accurate skull base tumor specimen analysis using label-free optical imaging and artificial intelligence.
We used a fiber laser-based, label-free, nonconsumptive, high-resolution microscopy method (<60 seconds per 1 × 1 mm2), called stimulated Raman histology (SRH), to image a consecutive, multicenter cohort of patients with skull base tumor. SRH images were then used to train a convolutional neural network model using 3 representation learning strategies: cross-entropy, self-supervised contrastive learning, and supervised contrastive learning. Our trained convolutional neural network models were tested on a held-out, multicenter SRH data set.
SRH was able to image the diagnostic features of both benign and malignant skull base tumors. Of the 3 representation learning strategies, supervised contrastive learning most effectively learned the distinctive and diagnostic SRH image features for each of the skull base tumor types. In our multicenter testing set, cross-entropy achieved an overall diagnostic accuracy of 91.5%, self-supervised contrastive learning 83.9%, and supervised contrastive learning 96.6%. Our trained model was able to segment tumor-normal margins and detect regions of microscopic tumor infiltration in meningioma SRH images.
SRH with trained artificial intelligence models can provide rapid and accurate intraoperative analysis of skull base tumor specimens to inform surgical decision-making.
•Serious adverse events (45.5%) occur after Normal Pressure Hydrocephalus surgery.•Many serious adverse events (SAEs) occur months after surgery is complete.•Normal Pressure Hydrocephalus surgery may ...have more risks than previously reported.
Recent Normal Pressure Hydrocephalus (NPH) practice guidelines describe a serious adverse event (SAE) rate following surgery of 11%.
We conducted a retrospective review of 162 consecutive patients who have undergone work-up at our center’s multidisciplinary NPH clinic over a 47 month time period (2/2014-12/2017). Of these, 22 ultimately underwent neurosurgical ventricular shunt surgery as treatment for NPH. Clinical records were reviewed for SAEs categorized as possibly/probably/definitely related to NPH surgery.
In 10/22 (45.5%) operated subjects, there were 11 qualifying SAEs over this 3-year period: 1 central nervous system infections, 4 subdural hematomas, 2 seizures resulting in hospitalization, 1 catheter malfunction, 2 perioperative AEs, and 1 death of uncertain cause. Eight SAEs were coded as probably/definitely related. Six occurred >3 months from the time of surgery.
SAEs following NPH surgery are common. Additional studies are needed to determine the long-term safety of NPH surgery in older adults.
Abstract
BACKGROUND
Research on age-related complications secondary to shunts in normal pressure hydrocephalus (NPH) is primarily limited to single-center studies and small cohorts.
OBJECTIVE
To ...determine the rates of hospital readmission and surgical complications, and factors that predict them, following shunt surgery for NPH in a large healthcare network.
METHODS
Surgical procedures, complications, and readmissions for adults undergoing ventricular shunting for NPH were determined using de-identified claims from a privately insured United States healthcare network in years 2007-2014. Univariate and multivariate statistics were used to determine factors that predict poor surgical outcomes. The primary outcome variable was surgical complications or readmissions (composite variable for any major perioperative complication or 30-d readmission).
RESULTS
The 30-d readmission rate for 974 patients with NPH who underwent ventricular shunting was 7.29%; the most common reasons for readmission were shunt-related complications, infection, hemorrhage, altered mental status, and cardiopulmonary and musculoskeletal problems. The perioperative complication rate was 21.15%, including intraparenchymal hemorrhage (5.85%) and extra-axial (subdural or epidural) hematoma (5.54%). The overall rate of having a surgical complication or 30-d readmission was 25.15%. Age did not predict surgical complication or 30-d readmission. Preoperative comorbidities independently associated with poor outcome were myocardial infarction within 1 yr (OR = 3.984, 95% CI = 1.105-14.368); existing cerebrovascular disease (odds ratio OR = 2.206, 95% CI = 1.544-3.152); and moderate/severe renal disease (OR = 2.000, 95% CI = 1.155-3.464).
CONCLUSION
The rate of complications or readmission within 30 d of ventricular shunting for NPH is 25.15%. Preoperative comorbidities of myocardial infarction within 1 yr, cerebrovascular disease, and moderate/severe renal disease are independent risk factors for poor outcome.
Graphical Abstract
Graphical Abstract
Glioblastoma(GBM) is a lethal disease characterized by inevitable recurrence. Here we investigate the molecular pathways mediating resistance, with the goal of identifying novel therapeutic ...opportunities.
We developed a longitudinal in vivo recurrence model utilizing patient-derived explants to produce paired specimens(pre- and post-recurrence) following temozolomide(TMZ) and radiation(IR). These specimens were evaluated for treatment response and to identify gene expression pathways driving treatment resistance. Findings were clinically validated using spatial transcriptomics of human GBMs.
These studies reveal in replicate cohorts, a gene expression profile characterized by upregulation of mesenchymal and stem-like genes at recurrence. Analyses of clinical databases revealed significant association of this transcriptional profile with worse overall survival and upregulation at recurrence. Notably, gene expression analyses identified upregulation of TGFβ signaling, and more than one-hundred-fold increase in THY1 levels at recurrence. Furthermore, THY1-positive cells represented <10% of cells in treatment-naïve tumors, compared to 75-96% in recurrent tumors. We then isolated THY1-positive cells from treatment-naïve patient samples and determined that they were inherently resistant to chemoradiation in orthotopic models. Additionally, using image-guided biopsies from treatment-naïve human GBM, we conducted spatial transcriptomic analyses. This revealed rare THY1+ regions characterized by mesenchymal/stem-like gene expression, analogous to our recurrent mouse model, which co-localized with macrophages within the perivascular niche. We then inhibited TGFBRI activity in vivo which decreased mesenchymal/stem-like protein levels, including THY1, and restored sensitivity to TMZ/IR in recurrent tumors.
These findings reveal that GBM recurrence may result from tumor repopulation by pre-existing, therapy-resistant, THY1-positive, mesenchymal cells within the perivascular niche.
Intraoperative diagnosis is essential for providing safe and effective care during cancer surgery
. The existing workflow for intraoperative diagnosis based on hematoxylin and eosin staining of ...processed tissue is time, resource and labor intensive
. Moreover, interpretation of intraoperative histologic images is dependent on a contracting, unevenly distributed, pathology workforce
. In the present study, we report a parallel workflow that combines stimulated Raman histology (SRH)
, a label-free optical imaging method and deep convolutional neural networks (CNNs) to predict diagnosis at the bedside in near real-time in an automated fashion. Specifically, our CNNs, trained on over 2.5 million SRH images, predict brain tumor diagnosis in the operating room in under 150 s, an order of magnitude faster than conventional techniques (for example, 20-30 min)
. In a multicenter, prospective clinical trial (n = 278), we demonstrated that CNN-based diagnosis of SRH images was noninferior to pathologist-based interpretation of conventional histologic images (overall accuracy, 94.6% versus 93.9%). Our CNNs learned a hierarchy of recognizable histologic feature representations to classify the major histopathologic classes of brain tumors. In addition, we implemented a semantic segmentation method to identify tumor-infiltrated diagnostic regions within SRH images. These results demonstrate how intraoperative cancer diagnosis can be streamlined, creating a complementary pathway for tissue diagnosis that is independent of a traditional pathology laboratory.
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