Evaluation of radiological and clinical efficacy of ^{90}Y-DOTATATE} therapy in patients with progressive metastatic midgut neuroendocrine carcinomas

Background: To evaluate the radiological and clinical therapeutic effectiveness of ^{90}Y-octreotate [DOTATATE] inpatients with progressive somatostatin receptor-positive midgut neuroendocrine carcinomas (GEPNETs). Material/Methods: The study group: 34 patients, with histological proven extensive non-resectable and progressive midgut GEP-NETs. Radionuclide therapy (^{90}Y-DOTATATE) was given i.v. with a mean activity per administration 3,82 GBq. Initial clinical tumor responses were assessed 6-7 weeks after therapy completion and then once 3-monthly. The objective tumor response was classified according to the RECIST, initially between 4-6 months and then after each of the 6 months interval. Results: At 6 months after treatment completion, radiological tumor response was observed in 6 subjects with PR (19%), 25 presented SD (78%) and single had PD (3%). Overall clinical response to therapy at 6 months follow-up was observed in 23 patients (68%), SD in 5 patients (15%) and PD in 6 (18%). A year after therapy radiological tumour response was seen in 11 patients (44%), SD had 12 subjects (44%) and DP was noted in 2 patients. Two years after completed therapy PR was seen in 6 patients (33%), SD in additional 11 subjects (61%), single patient had PD. Clinical response to treatment in terms of PR and SD were noted in 22 patients (88%) after 1 year and in 14 patients (87%) after 2 years. Median PFS was 20 months, while the median OS was 23 months. In the 6 patients with clinical PD within initial 6 months the median PFS was 6 months and OS 11 months, while in those with SD or PR PFS was 22 months and OS 26 months (P<0.05). Conclusions: Therapy with ^{90}Y-DOTATATE} is effective in terms of clinical response, however the radiological response measured by the RECIST criteria underestimates benefits of this type of therapy in patients with progressive somatostatin receptor-positive midgut neuroendocrine carcinomas

Copula Ordinal Regression for Joint Estimation of Facial Action Unit Intensity

Joint modeling of the intensity of facial action units (AUs) from face images is challenging due to the large number of AUs (30+) and their intensity levels (6). This is in part due to the lack of suitable models that can efficiently handle such a large number of outputs/classes simultaneously, but also due to the lack of labelled target data. For this reason, majority of the methods proposed so far resort to independent classifiers for the AU intensity. This is suboptimal for at least two reasons: the facial appearance of some AUs changes depending on the intensity of other AUs, and some AUs co-occur more often than others. Encoding this is expected to improve the estimation of target AU intensities, especially in the case of noisy image features, head-pose variations and imbalanced training data. To this end, we introduce a novel modeling framework, Copula Ordinal Regression (COR), that leverages the power of copula functions and CRFs, to detangle the probabilistic modeling of AU dependencies from the marginal modeling of the AU intensity. Consequently, the COR model achieves the joint learning and inference of intensities of multiple AUs, while being computationally tractable. We show on two challenging datasets of naturalistic facial expressions that the proposed approach consistently outperforms (i) independent modeling of AU intensities, and (ii) the state-ofthe-art approach for the target task

Deep learning model for detection of pain intensity from facial expression

Many people who are suffering from a chronic pain face pe- riods of acute pain and resulting problems during their illness and ade- quate reporting of symptoms is necessary for treatment. Some patients have difficulties in adequately alerting caregivers to their pain or describ- ing the intensity which can impact on effective treatment. Pain and its intensity can be noticeable in ones face. Movements in facial muscles can depict ones current emotional state. Machine learning algorithms can detect pain intensity from facial expressions. The algorithm can ex- tract and classify facial expression of pain among patients. In this paper, we propose a new deep learning model for detection of pain intensity from facial expressions. This automatic pain detection system may help clinicians to detect pain and its intensity in patients and by doing this healthcare organizations may have access to more complete and more regular information of patients regarding their pain

Diagnostic imaging of neuroendocrine tumours

Guzy neuroendokrynne (NET) stanowią heterogenną grupę nowotworów posiadających mechanizmy gromadzenia prekursorów amin biogennych oraz ekspresję specyficznych białek receptorowych na swojej błonie komórkowej, które pomagają w lokalizacji oraz w leczeniu. Guzy typu NET różnią się między sobą substancjami wydzielanymi przez komórki, obecnością czynności hormonalnej lub jej brakiem, objawami klinicznymi, cechami histopatologicznymi oraz rokowaniem. Pochodzą one z gruczołów wydzielania wewnętrznego (przysadka, przytarczyce, rdzeń nadnercza) oraz dodatkowo z komórek rozlanego systemu endokrynnego o lokalizacji w ścianie przewodu pokarmowego, trzustce, tarczycy, grasicy czy w oskrzelach. Guzy NET o pochodzeniu GEP-NET stanowią większość tego typu guzów (> 70% wszystkich NET). Badania obrazowe i ocena swoistych markerów guzów NET umożliwiają identyfikację i ocenę stadium zaawansowania tych rzadkich nowotworów, a ponadto mają wartość prognostyczną. Najbardziej uniwersalną techniką obrazową wykorzystywaną w badaniu NET jest SRS. Innych badań obrazowych, takich jak spiralna wielorzędowa CT, MRI, endoskopowe oraz śródoperacyjne badanie USG, używa się do precyzyjnej anatomicznej lokalizacji zmian patologicznych. Kolejnym badaniem czynnościowym wykorzystywanym w diagnostyce NET jest scyntygrafia MIBG (metajodobenzyloguanidyna). Badanie to pozwala identyfikować przede wszystkim guz chromochłonny oraz MTC. W postaciach złośliwych guza chromochłonnego oraz raka rdzeniastego tarczycy znaczenie ma również badanie SRS. Bardzo ważnym aspektem wykorzystania technik obrazowych (zwłaszcza CT, SRS i MRI) jest ocena odpowiedzi na leczenie. Coraz większe znaczenie kliniczne w lokalizacji guzów NET ma badanie PET z użyciem nowych ligandów receptorowych wyznakowanych 68Ga. Wykorzystanie standardowego FDG PET stosuje się w guzach NET o wysokiej złośliwości.Neuroendocrine tumours (NET) consists of a heterogeneous group of neoplasms, that are able to express cell membrane neuroamine uptake mechanisms and/or specific receptors, such as somatostatin receptors, which can be used in the localization and treatment of these tumours. Conventionally NETs may present with a wide variety of functional or nonfunctional endocrine syndromes and may be familial and have other associated tumors, also they have different histology pattern and prognosis. They originate from endocrine glands such as the pituitary, the parathyroids, and the (neuroendocrine) adrenal, as well as endocrine islets within glandular tissue (thyroid or pancreatic) and cells dispersed between exocrine cells, such as endocrine cells of the digestive system (gastroenteropancreatic GEP-NET) and respiratory tracts. GEP-NET are the most common including more then 70% of all NETs.Imaging modalities and assessment of specific tumor markers offers high sensitivity in establishing the diagnosis and can also have prognostic significance. Most important single imaging technique in terms of initial identification and staging of GEP-NET seems to be somatostatin receptor scintigraphy (SRS). Other investigations like helical computed tomography (CT), magnetic resonance imaging (MRI), endoscopic and/or peri-operative ultrasonography are used for the precise localization of NET. Another one functional approach include MIBG (meta-iodobenzylguanidine scintigraphy). This technique is sensitive in the identification of chromaffin cell tumours pheochromocytoma, and also medullary thyroid carcinoma (MTC), although SRS seems to be very useful in the localization of malignant chromaffin cell tumours and MTC as well. The further localization and monitoring of the response to treatment CT, SRS and MRI are used with high diagnostic accuracy. More recently, positron emission tomography (PET) scanning is being increasingly used for the localization of NETs, due to develop new PET tracers (68Ga), the standard one FDG PET is currently used in groups of high malignant NET

Sexual dimorphism in cancer.

The incidence of many types of cancer arising in organs with non-reproductive functions is significantly higher in male populations than in female populations, with associated differences in survival. Occupational and/or behavioural factors are well-known underlying determinants. However, cellular and molecular differences between the two sexes are also likely to be important. In this Opinion article, we focus on the complex interplay that sex hormones and sex chromosomes can have in intrinsic control of cancer-initiating cell populations, the tumour microenvironment and systemic determinants of cancer development, such as the immune system and metabolism. A better appreciation of these differences between the two sexes could be of substantial value for cancer prevention as well as treatment

SEWA DB: A rich database for audio-visual emotion and sentiment research in the wild

Natural human-computer interaction and audio-visual human behaviour sensing systems, which would achieve robust performance in-the-wild are more needed than ever as digital devices are becoming indispensable part of our life more and more. Accurately annotated real-world data are the crux in devising such systems. However, existing databases usually consider controlled settings, low demographic variability, and a single task. In this paper, we introduce the SEWA database of more than 2000 minutes of audio-visual data of 398 people coming from six cultures, 50% female, and uniformly spanning the age range of 18 to 65 years old. Subjects were recorded in two different contexts: while watching adverts and while discussing adverts in a video chat. The database includes rich annotations of the recordings in terms of facial landmarks, facial action units (FAU), various vocalisations, mirroring, and continuously valued valence, arousal, liking, agreement, and prototypic examples of (dis)liking. This database aims to be an extremely valuable resource for researchers in affective computing and automatic human sensing and is expected to push forward the research in human behaviour analysis, including cultural studies. Along with the database, we provide extensive baseline experiments for automatic FAU detection and automatic valence, arousal and (dis)liking intensity estimation

Computed tomographic angiography criteria in the diagnosis of brain death—comparison of sensitivity and interobserver reliability of different evaluation scales

INTRODUCTION: The standardized diagnostic criteria for computed tomographic angiography (CTA) in diagnosis of brain death (BD) are not yet established. The aim of the study was to compare the sensitivity and interobserver agreement of the three previously used scales of CTA for the diagnosis of BD. METHODS: Eighty-two clinically brain-dead patients underwent CTA with a delay of 40 s after contrast injection. Catheter angiography was used as the reference standard. CTA results were assessed by two radiologists, and the diagnosis of BD was established according to 10-, 7-, and 4-point scales. RESULTS: Catheter angiography confirmed the diagnosis of BD in all cases. Opacification of certain cerebral vessels as indicator of BD was highly sensitive: cortical segments of the middle cerebral artery (96.3 %), the internal cerebral vein (98.8 %), and the great cerebral vein (98.8 %). Other vessels were less sensitive: the pericallosal artery (74.4 %), cortical segments of the posterior cerebral artery (79.3 %), and the basilar artery (82.9 %). The sensitivities of the 10-, 7-, and 4-point scales were 67.1, 74.4, and 96.3 %, respectively (p < 0.001). Percentage interobserver agreement in diagnosis of BD reached 93 % for the 10-point scale, 89 % for the 7-point scale, and 95 % for the 4-point scale (p = 0.37). CONCLUSIONS: In the application of CTA to the diagnosis of BD, reducing the assessment of vascular opacification scale from a 10- to a 4-point scale significantly increases the sensitivity and maintains high interobserver reliability

Comparing methods for assessment of facial dynamics in patients with major neurocognitive disorders

International audienceAssessing facial dynamics in patients with major neurocogni-tive disorders and specifically with Alzheimers disease (AD) has shown to be highly challenging. Classically such assessment is performed by clinical staff, evaluating verbal and non-verbal language of AD-patients, since they have lost a substantial amount of their cognitive capacity, and hence communication ability. In addition, patients need to communicate important messages, such as discomfort or pain. Automated methods would support the current healthcare system by allowing for telemedicine, i.e., lesser costly and logistically inconvenient examination. In this work we compare methods for assessing facial dynamics such as talking, singing, neutral and smiling in AD-patients, captured during music mnemotherapy sessions. Specifically, we compare 3D Con-vNets, Very Deep Neural Network based Two-Stream ConvNets, as well as Improved Dense Trajectories. We have adapted these methods from prominent action recognition methods and our promising results suggest that the methods generalize well to the context of facial dynamics. The Two-Stream ConvNets in combination with ResNet-152 obtains the best performance on our dataset, capturing well even minor facial dynamics and has thus sparked high interest in the medical community