Conventional methods for intraoperative histopathologic diagnosis are labour- and time-intensive, and may delay decision-making during brain-tumour surgery. Stimulated Raman scattering (SRS) microscopy, a label-free optical process, has been shown to rapidly detect brain-tumour infiltration in fresh, unprocessed human tissues. Here, we demonstrate the first application of SRS microscopy in the operating room by using a portable fibre-laser-based microscope and unprocessed specimens from 101 neurosurgical patients. We also introduce an image-processing method – stimulated Raman histology (SRH) – which leverages SRS images to create virtual haematoxylin-and-eosin-stained slides, revealing essential diagnostic features. In a simulation of intraoperative pathologic consultation in 30 patients, we found a remarkable concordance of SRH and conventional histology for predicting diagnosis (Cohen's kappa, κ > 0.89), with accuracy exceeding 92%. We also built and validated a multilayer perceptron based on quantified SRH image attributes that predicts brain-tumour subtype with 90% accuracy. Our findings provide insight into how SRH can now be used to improve the surgical care of brain tumour patients.

Intraoperative diagnosis is essential for providing safe and effective care during cancer surgery 1. The existing workflow for intraoperative diagnosis based on hematoxylin and eosin-staining of processed tissue is time-, resource-, and labor-intensive 2,3. Moreover, interpretation of intraoperative histologic images is dependent on a contracting, unevenly distributed pathology workforce 4. Here, we report a parallel workflow that combines stimulated Raman histology (SRH) 5-7 , a label-free optical imaging method, and deep convolutional neural networks (CNN) to predict diagnosis at the bedside in near real-time in an automated fashion. Specifically, our CNN, trained on over 2.5 million SRH images, predicts brain tumor diagnosis in the operating room in under 150 seconds, an order of magnitude faster than conventional techniques (e.g., 20-30 minutes) 2. In a multicenter, prospective clinical trial (n = 278) we demonstrated that CNN-based diagnosis of SRH images was non-inferior to pathologist-based interpretation of conventional histologic images (overall accuracy, 94.6% vs. 93.9%). Our CNN learned a hierarchy of recognizable histologic feature representations to classify the major histopathologic classes of brain tumors. Additionally, 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 complimentary pathway for tissue diagnosis that is independent of a traditional pathology laboratory.

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 non-destructive, label-free optical method, to reveal glioma infiltration in animal models. Here 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. Importantly, 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.

Accurate histopathologic diagnosis is essential for providing optimal surgical management of pediatric brain tumors. Current methods for intraoperative histology are time- and labor-intensive and often introduce artifact that limit interpretation. Stimulated Raman histology (SRH) is a novel label-free imaging technique that provides intraoperative histologic images of fresh, unprocessed surgical specimens. Here we evaluate the capacity of SRH for use in the intraoperative diagnosis of pediatric type brain tumors. SRH revealed key diagnostic features in fresh tissue specimens collected from 33 prospectively enrolled pediatric type brain tumor patients, preserving tumor cytology and histoarchitecture in all specimens. We simulated an intraoperative consultation for 25 patients with specimens imaged using both SRH and standard hematoxylin and eosin histology. SRH-based diagnoses achieved near-perfect diagnostic concordance (Cohen's kappa, > 0.90) and an accuracy of 92% to 96%. We then developed a quantitative histologic method using SRH images based on rapid image feature extraction. Nuclear density, tumor-associated macrophage infiltration, and nuclear morphology parameters from 3337 SRH fields of view were used to develop and validate a decision-tree machine-learning model. Using SRH image features, our model correctly classified 25 fresh pediatric type surgical specimens into normal versus lesional tissue and low-grade versus high-grade tumors with 100% accuracy. Our results provide insight into how SRH can deliver rapid diagnostic histologic data that could inform the surgical management of pediatric brain tumors. A new imaging method simplifies diagnosis and informs decision making during pediatric brain tumor surgery. .

BackgroundThe role of husbands in maternal health is often overlooked by health programmes in developing countries and is an under-researched area of study globally. This study examines the role of husbands in maternity care and safe childbirth, their perceptions of the needs of women and children, the factors which influence or discourage their participation, and how women feel about male involvement around childbirth. It also identifies considerations that should be taken into account in the development of health education for husbands.MethodsThis qualitative study was conducted in four rural hill villages in the Gorkha district of Nepal. Semi-structured, in-depth interviews were conducted with husbands (n = 17), wives (n = 15), mothers-in-law (n = 3), and health workers (n = 7) in Nepali through a translator. Interviews were transcribed and analysed using axial coding.ResultsWe found that, in rural Nepal, male involvement in maternal health and safe childbirth is complex and related to gradual and evolving changes in attitudes taking place. Traditional beliefs are upheld which influence male involvement, including the central role of women in the domain of pregnancy and childbirth that cannot be ignored. That said, husbands do have a role to play in maternity care. For example, they may be the only person available when a woman goes into labour. Considerable interest for the involvement of husbands was also expressed by both expectant mothers and fathers. However, it is important to recognise that the husbands’ role is shaped by many factors, including their availability, cultural beliefs, and traditions.ConclusionsThis study shows that, although complex, expectant fathers do have an important role in maternal health and safe childbirth. Male involvement needs to be recognised and addressed in health education due to the potential benefits it may bring to both maternal and child health outcomes. This has important implications for health policy and practice, as there is a need for health systems and maternal health interventions to adapt in order to ensure the appropriate and effective inclusion of expectant fathers.Electronic supplementary materialThe online version of this article (doi:10.1186/s12884-015-0599-8) contains supplementary material, which is available to authorized users.

Despite advances in the surgical management of brain tumors, achieving optimal surgical results and identification of tumor remains a challenge. Raman spectroscopy, a laser-based technique that can be used to nondestructively differentiate molecules based on the inelastic scattering of light, is being applied toward improving the accuracy of brain tumor surgery. Here, the authors systematically review the application of Raman spectroscopy for guidance during brain tumor surgery. Raman spectroscopy can differentiate normal brain from necrotic and vital glioma tissue in human specimens based on chemical differences, and has recently been shown to differentiate tumor-infiltrated tissues from noninfiltrated tissues during surgery. Raman spectroscopy also forms the basis for coherent Raman scattering (CRS) microscopy, a technique that amplifies spontaneous Raman signals by 10,000-fold, enabling real-time histological imaging without the need for tissue processing, sectioning, or staining. The authors review the relevant basic and translational studies on CRS microscopy as a means of providing real-time intraoperative guidance. Recent studies have demonstrated how CRS can be used to differentiate tumor-infiltrated tissues from noninfiltrated tissues and that it has excellent agreement with traditional histology. Under simulated operative conditions, CRS has been shown to identify tumor margins that would be undetectable using standard bright-field microscopy. In addition, CRS microscopy has been shown to detect tumor in human surgical specimens with near-perfect agreement to standard H & E microscopy. The authors suggest that as the intraoperative application and instrumentation for Raman spectroscopy and imaging matures, it will become an essential component in the neurosurgical armamentarium for identifying residual tumor and improving the surgical management of brain tumors.

Early experience suggests that lung volume reduction surgery improves exercise tolerance as measured by the 6-min walk distance in patients with emphysema. To identify the physiologic mechanism(s) by which lung volume reduction surgery improved exercise, we performed progressive cardiopulmonary exercise testing, including rest and peak exercise blood gas determinations, on 21 consecutive patients before and 3 mo after lung volume reduction surgery. Maximal work (median, range, % change) increased 17.5 watts (-13 to +44 watts, 46%, p < 0.05), maximal oxygen consumption increased 0.16 L/min (-0.17 to +0.48, 25%, p < 0.05), maximal ventilation increased 6.6 L/min (-7 to +26 L/min, 27%, p < 0.05), and the dead space/tidal volume ratio at peak exercise decreased 0.07 (-0.22 to +0.09, 12%, p < 0.05), exclusively as a result of an increase in the tidal volume. After lung volume reduction surgery heart rate decreased at the point of isowatt exercise, from 115 to 111 beats/min (p < 0.05). No difference was observed in the other physiologic variables measured at isowatt exercise. In 13 patients exercised while breathing room air, the alveolar-to-arterial O2 difference increased, and the arterial O2 tension decreased from rest to peak exercise both before and after the operation, but significant changes in this response were not observed after surgery. The primary problem limiting exercise performance in these patients was the limited ventilatory capacity as 16 and 13 of the 21 subjects developed acute respiratory acidemia at peak exercise before and after surgery, respectively. Lung volume reduction surgery in patients with severe emphysema improved maximal ventilation, thereby improving maximal exercise performance.

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