38 research outputs found
GenSelfDiff-HIS: Generative Self-Supervision Using Diffusion for Histopathological Image Segmentation
Histopathological image segmentation is a laborious and time-intensive task,
often requiring analysis from experienced pathologists for accurate
examinations. To reduce this burden, supervised machine-learning approaches
have been adopted using large-scale annotated datasets for histopathological
image analysis. However, in several scenarios, the availability of large-scale
annotated data is a bottleneck while training such models. Self-supervised
learning (SSL) is an alternative paradigm that provides some respite by
constructing models utilizing only the unannotated data which is often
abundant. The basic idea of SSL is to train a network to perform one or many
pseudo or pretext tasks on unannotated data and use it subsequently as the
basis for a variety of downstream tasks. It is seen that the success of SSL
depends critically on the considered pretext task. While there have been many
efforts in designing pretext tasks for classification problems, there haven't
been many attempts on SSL for histopathological segmentation. Motivated by
this, we propose an SSL approach for segmenting histopathological images via
generative diffusion models in this paper. Our method is based on the
observation that diffusion models effectively solve an image-to-image
translation task akin to a segmentation task. Hence, we propose generative
diffusion as the pretext task for histopathological image segmentation. We also
propose a multi-loss function-based fine-tuning for the downstream task. We
validate our method using several metrics on two publically available datasets
along with a newly proposed head and neck (HN) cancer dataset containing
hematoxylin and eosin (H\&E) stained images along with annotations. Codes will
be made public at
https://github.com/PurmaVishnuVardhanReddy/GenSelfDiff-HIS.git
Intra-operative mechanical ventilation in amebic liver abscess surgery: Another paradigm
Intraoperative low tidal volume ventilation strategy has no benefits during laparoscopic cholecystectomy
Background and Aims: Benefits of intraoperative low tidal volume ventilation during laparoscopic surgery are not conclusively proven, even though its advantages were seen in other situations with intraoperative respiratory compromise such as one-lung ventilation. The present study compared the efficacy of intraoperative low tidal volume ventilatory strategy (6 ml/kg along with positive end-expiratory pressure [PEEP] of 10 cmH2O) versus one with higher tidal volume (10 ml/kg with no PEEP) on various clinical parameters and plasma levels of interleukin (IL)-6 in patients undergoing laparoscopic cholecystectomy.
Material and Methods: A total of 58 adult patients with American Society of Anesthesiologists physical status I or II, undergoing laparoscopic cholecystectomy were randomized to receive the low or higher tidal volume strategy as above (n = 29 each). The primary outcome measure was postoperative PaO2. Systemic levels of IL-6 along with clinical indices of intraoperative gas exchange, pulmonary mechanics, and hemodynamic consequences were measured as secondary outcome measures.
Results: There was no statistically significant difference in oxygenation; intraoperative dynamic compliance, peak airway pressures, or hemodynamic parameters, or the IL-6 levels between the two groups (P > 0.05). Low tidal volume strategy was associated with significantly higher mean airway pressure, lower airway resistance, greater respiratory rates, and albeit clinically similar, higher PaCO2and lower pH (P < 0.05).
Conclusion: Strategy using 6 ml/kg tidal volume along with 10 cmH2O of PEEP was not associated with any significant improvement in gas exchange, hemodynamic parameters, or systemic inflammatory response over ventilation with 10 ml/kg volume without PEEP during laparoscopic cholecystectomy
Primary anaplastic astrocytoma of the brain after prophylactic cranial irradiation in a case of acute lymphoblastic leukemia: Case report and review of the literature
Sarcomatoid carcinoma of lung - A case report and review of epidermal growth factor receptor mutation status
Effect of intravenous phenylephrine infusion on dose requirement of intrathecal plain levobupivacaine for cesarean section: A placebo-controlled preliminary study
Background: Phenylephrine infusion has been shown to decrease rostral spread of plain and hyperbaric local anesthetic (LA) when compared to ephedrine infusion. However, it does not result in higher dose requirement of hyperbaric LA for cesarean section. There is no trial evaluating the effect of phenylephrine infusion on ED50 of a plain intrathecal LA.
Methods: Pregnant patients with term uncomplicated singleton pregnancy undergoing elective cesarean section were given combined spinal-epidural anesthesia. They received intrathecal plain levobupivacaine 0.5% in a dose decided by up-and-down sequential allocation method along with 25 μg fentanyl. Intravenous infusion of phenylephrine (100 μg/ml) or normal saline was initiated immediately after intrathecal injection. Systolic arterial pressure ≤0.8 times baseline was treated using rescue boluses of phenylephrine 50 μg.
Results: Demographic, other patient and surgical characteristics were similar in the two groups. ED50 of intrathecal plain levobupivacaine was significantly greater in phenylephrine group (5.5 mg [95% confidence interval (CI): 5.1–5.9 mg]) compared to saline group (4.2 mg [95% CI: 3.4–5.1 mg]) (P = 0.01). Maximum sensory level, time to achieve adequate block, Apgar scores, and umbilical artery pH were similar in both groups. Total phenylephrine dose and patients having significant bradycardia were lesser in the saline group.
Conclusions: Intrathecal dose requirement of plain levobupivacaine is greater using phenylephrine infusion as compared to saline infusion with rescue phenylephrine boluses. When using phenylephrine as a variable dose regimen titrated to maintain blood pressure within 20% of baseline, the ED50 of plain levobupivacaine is 5.5 mg (95% CI: 5.1–5.9 mg)