Immune cell infiltrates in peritoneal metastases from colorectal cancer.

Background: The presence of peritoneal metastases (PMs) in patients with colorectal cancer (CRC) confers a poor prognosis and only a minority of patients will benefit from the available treatment options. In primary CRC tumors, it is well established that a high infiltration of CD8+ effector T cells correlates to a favorable patient outcome. In contrast, the immune response induced in PMs from CRC and how it relates to patient survival is still unknown. In this study, we characterized the immune infiltrates and the distribution of immune checkpoint receptors on T cells from PMs from CRC, in order to evaluate the potential benefit of checkpoint blockade immunotherapy for this patient group. Methods: Surgically resected PM tissue from CRC patients (n=22) and synchronous primary tumors (n=8) were processed fresh to single cell suspensions using enzymatic digestion. Surface markers and cytokine production were analyzed using flow cytometry. Results: T cells dominated the leukocyte infiltrate in the PM specimens analyzed, followed by monocytes and B cells. Comparing two different PMs from the same patient usually showed a similar distribution of immune cells in both samples. The T cell infiltrate was characterized by an activated phenotype and markers of exhaustion were enriched compared with matched circulating T cells, in particular the checkpoint receptors PD-1 and TIGIT. In functional assays most cytotoxic and helper T cells produced INF-γ and TNF following polyclonal stimulation, while few produced IL-17, indicating a dominance of Th1-type responses in the microenvironment of PMs. Conclusion: Immune cells were present in all PMs from CRC examined. Although infiltrating T cells express markers of exhaustion, they produce Th1-type cytokines when stimulated. These results indicate the possibility to augment tumor-specific immune responses within PMs using checkpoint blockade inhibitors.

Retinal vessel architecture and geometry are not impaired in normal-tension glaucoma.

To investigate the associations between retinal vessel parameters and normal-tension glaucoma (NTG). We conducted a case-control study with a prospective cohort, allowing to record 23 cases of NTG. We matched NTG patient with one primary open-angle glaucoma (POAG) and one control per case by age, systemic hypertension, diabetes, and refraction. Central retinal artery equivalent (CRAE), central retinal venule equivalent (CRVE), Arteriole-To-Venule ratio (AVR), Fractal Dimension and tortuosity of the vascular network were measured using VAMPIRE software. Our sample consisted of 23 NTG, 23 POAG, and 23 control individuals, with a median age of 65 years (25-75th percentile, 56-74). No significant differences were observed in median values for CRAE (130.6 µm (25-75th percentile, 122.8; 137.0) for NTG, 128.4 µm (124.0; 132.9) for POAG, and 135.3 µm (123.3; 144.8) for controls, P = .23), CRVE (172.1 µm (160.0; 188.3), 172.8 µm (163.3; 181.6), and 175.9 µm (167.6; 188.4), P = .43), AVR (0.76, 0.75, 0.74, P = .71), tortuosity and fractal parameters across study groups. Vascular morphological parameters were not significantly associated with retinal nerve fiber layer thickness or mean deviation for the NTG and POAG groups. Our results suggest that vascular dysregulation in NTG does not modify the architecture and geometry of the retinal vessel network.

Association Between Retinal Features From Multimodal Imaging and Schizophrenia.

Importance: The potential association of schizophrenia with distinct retinal changes is of clinical interest but has been challenging to investigate because of a lack of sufficiently large and detailed cohorts. Objective: To investigate the association between retinal biomarkers from multimodal imaging (oculomics) and schizophrenia in a large real-world population. Design, Setting, and Participants: This cross-sectional analysis used data from a retrospective cohort of 154 830 patients 40 years and older from the AlzEye study, which linked ophthalmic data with hospital admission data across England. Patients attended Moorfields Eye Hospital, a secondary care ophthalmic hospital with a principal central site, 4 district hubs, and 5 satellite clinics in and around London, United Kingdom, and had retinal imaging during the study period (January 2008 and April 2018). Data were analyzed from January 2022 to July 2022. Main Outcomes and Measures: Retinovascular and optic nerve indices were computed from color fundus photography. Macular retinal nerve fiber layer (RNFL) and ganglion cell-inner plexiform layer (mGC-IPL) thicknesses were extracted from optical coherence tomography. Linear mixed-effects models were used to examine the association between schizophrenia and retinal biomarkers. Results: A total of 485 individuals (747 eyes) with schizophrenia (mean [SD] age, 64.9 years [12.2]; 258 [53.2%] female) and 100 931 individuals (165 400 eyes) without schizophrenia (mean age, 65.9 years [13.7]; 53 253 [52.8%] female) were included after images underwent quality control and potentially confounding conditions were excluded. Individuals with schizophrenia were more likely to have hypertension (407 [83.9%] vs 49 971 [48.0%]) and diabetes (364 [75.1%] vs 28 762 [27.6%]). The schizophrenia group had thinner mGC-IPL (-4.05 µm, 95% CI, -5.40 to -2.69; P = 5.4 × 10-9), which persisted when investigating only patients without diabetes (-3.99 µm; 95% CI, -6.67 to -1.30; P = .004) or just those 55 years and younger (-2.90 µm; 95% CI, -5.55 to -0.24; P = .03). On adjusted analysis, retinal fractal dimension among vascular variables was reduced in individuals with schizophrenia (-0.14 units; 95% CI, -0.22 to -0.05; P = .001), although this was not present when excluding patients with diabetes. Conclusions and Relevance: In this study, patients with schizophrenia had measurable differences in neural and vascular integrity of the retina. Differences in retinal vasculature were mostly secondary to the higher prevalence of diabetes and hypertension in patients with schizophrenia. The role of retinal features as adjunct outcomes in patients with schizophrenia warrants further investigation.

Lower fractal dimension of retinal vessel for patients with Birdshot chorioretinopathy.

PURPOSE: To identify the retinal vessel vasculature parameters associated with birdshot chorioretinopathy (BSCR). METHODS: This retrospective observational study included 28 prevalent cases of BSCR with a median time from diagnosis of 6 years and 28 controls matched for age, arterial hypertension, diabetes and refraction. Forty-five-degree fundus images of both dilated eyes were acquired with a fundus camera (Canon CR-2, Tokyo, Japan). The summary diameter of the arterial retinal vessels (central retinal artery equivalent, CRAE), venous retinal vessels (central retinal vein equivalent, CRVE), vascular tortuosity and fractal dimension (FD) were measured using VAMPIRE software. Retinal vasculitis was characterized using fluorescein angiography and active choroiditis using indocyanine green angiography. RESULTS: At baseline, BSCR was associated with lower FD compared with matched controls (mean difference, -0.04; 95% confidence interval [CI], -0.06 to -0.02, p < 0.001). No other VAMPIRE parameters (CRAE, CRVE, arterial and venous tortuosity) differed. Among BSCR patients, retinal vein vasculitis was associated with higher CRAE (mean difference, 21 µ; 95% CI, 2.6-40, p = 0.03), venous tortuosity (geometric mean ratio, 1.79; 95% CI, 1.18-2.72, p = 0.007) and FD (mean difference, -0.04; 95% CI, -0.06 to -0.01, p = 0.007). Resolution of retinal vein vasculitis during follow-up was paralleled by decrease in CRAE, CRVE and venous tortuosity values and increase in venous FD, respectively. CONCLUSION: BSCR is associated with lower FD value, suggesting that chronic retinal inflammation induces microvascular remodelling. Efficient treatment of retinal vasculitis may reverse changes in retinal vascular parameters. Changes in retinal vascular parameters could be potentially useful for assessing patients with BSCR disease.

Concordance between SIVA, IVAN, and VAMPIRE Software Tools for Semi-Automated Analysis of Retinal Vessel Caliber.

We aimed to compare measurements from three of the most widely used software packages in the literature and to generate conversion algorithms for measurement of the central retinal artery equivalent (CRAE) and central retinal vein equivalent (CRVE) between SIVA and IVAN and between SIVA and VAMPIRE. We analyzed 223 retinal photographs from 133 human participants using both SIVA, VAMPIRE and IVAN independently for computing CRAE and CRVE. Agreement between measurements was assessed using Bland-Altman plots and intra-class correlation coefficients. A conversion algorithm between measurements was carried out using linear regression, and validated using bootstrapping and root-mean-square error. The agreement between VAMPIRE and IVAN was poor to moderate: The mean difference was 20.2 µm (95% limits of agreement, LOA, -12.2-52.6 µm) for CRAE and 21.0 µm (95% LOA, -17.5-59.5 µm) for CRVE. The agreement between VAMPIRE and SIVA was also poor to moderate: the mean difference was 36.6 µm (95% LOA, -12.8-60.4 µm) for CRAE, and 40.3 µm (95% LOA, 5.6-75.0 µm) for CRVE. The agreement between IVAN and SIVA was good to excellent: the mean difference was 16.4 µm (95% LOA, -4.25-37.0 µm) for CRAE, and 19.3 µm (95% LOA, 0.09-38.6 µm) for CRVE. We propose an algorithm converting IVAN and VAMPIRE measurements into SIVA-estimated measurements, which could be used to homogenize sets of vessel measurements obtained with different software packages.

Clinical features of patients hospitalised with COVID-19 from February to October 2020, during the early waves of the pandemic in New Zealand.

AIM: As New Zealand transitions towards endemic SARS-CoV-2, understanding patient factors predicting severity, as well as hospital resourcing requirements will be essential for future planning. METHODS: We retrospectively enrolled patients hospitalised with COVID-19 from 26 February to 5 October 2020 as part of the COVID-19 HospitalisEd Patient SeverIty Observational Study NZ (COHESION). Data on demographics, clinical course and outcomes were collected and analysed as a descriptive case series. RESULTS: Eighty-four patients were identified across eight district health boards. Forty-one (49%) were male. The median age was 58 years [IQR: 41.7-70.3 years]. By ethnicity, hospitalisations included 38 NZ European (45%), 19 Pasifika (23%), 13 Maori (15%), 12 Asian (14%) and 2 Other (2%). Pre-existing co-morbidities included hypertension (26/82, 32%), obesity (16/66, 24%) and diabetes (18/81, 22%). The median length of stay was four days [IQR: 2-15 days]. Twelve patients (12/83, 14%) were admitted to an intensive care unit or high dependency unit (ICU/HDU). Ten (10/83, 12%) patients died in hospital of whom seven (70%) were not admitted to ICU/HDU; the median age at death was 83 years. CONCLUSION: Despite initially low case numbers in New Zealand during 2020, hospitalisation with COVID-19 was associated with a high mortality and hospital resource requirements.

Comparing Measurements of Vascular Diameter Using Adaptative Optics Imaging and Conventional Fundus Imaging.

The aim of this prospective study was to compare retinal vascular diameter measurements taken from standard fundus images and adaptive optics (AO) images. We analysed retinal images of twenty healthy subjects with 45-degree funduscopic colour photographs (CR-2 Canon fundus camera, Canon™) and adaptive optics (AO) fundus images (rtx1 camera, Imagine Eyes®). Diameters were measured using three software applications: the VAMPIRE (Vessel Assessment and Measurement Platform for Images of the REtina) annotation tool, IVAN (Interactive Vessel ANalyzer) for funduscopic colour photographs, and AO_Detect_Artery™ for AO images. For the arterial diameters, the mean difference between AO_Detect_Artery™ and IVAN was 9.1 µm (-27.4 to 9.2 µm, p = 0.005) and the measurements were significantly correlated (r = 0.79). The mean difference between AO_Detect_Artery™ and VAMPIRE annotation tool was 3.8 µm (-34.4 to 26.8 µm, p = 0.16) and the measurements were poorly correlated (r = 0.12). For the venous diameters, the mean difference between the AO_Detect_Artery™ and IVAN was 3.9 µm (-40.9 to 41.9 µm, p = 0.35) and the measurements were highly correlated (r = 0.83). The mean difference between the AO_Detect_Artery™ and VAMPIRE annotation tool was 0.4 µm (-17.44 to 25.3 µm, p = 0.91) and the correlations were moderate (r = 0.41). We found that the VAMPIRE annotation tool, an entirely manual software, is accurate for the measurement of arterial and venular diameters, but the correlation with AO measurements is poor. On the contrary, IVAN, a semi-automatic software tool, presents slightly greater differences with AO imaging, but the correlation is stronger. Data from arteries should be considered with caution, since IVAN seems to significantly under-estimate arterial diameters.

Prediction of Major Adverse Cardiovascular Events From Retinal, Clinical, and Genomic Data in Individuals With Type 2 Diabetes: A Population Cohort Study.

OBJECTIVE: Improved identification of individuals with type 2 diabetes at high cardiovascular (CV) risk could help in selection of newer CV risk-reducing therapies. The aim of this study was to determine whether retinal vascular parameters, derived from retinal screening photographs, alone and in combination with a genome-wide polygenic risk score for coronary heart disease (CHD PRS) would have independent prognostic value over traditional CV risk assessment in patients without prior CV disease. RESEARCH DESIGN AND METHODS: Patients in the Genetics of Diabetes Audit and Research Tayside Scotland (GoDARTS) study were linked to retinal photographs, prescriptions, and outcomes. Retinal photographs were analyzed using VAMPIRE (Vascular Assessment and Measurement Platform for Images of the Retina) software, a semiautomated artificial intelligence platform, to compute arterial and venous fractal dimension, tortuosity, and diameter. CHD PRS was derived from previously published data. Multivariable Cox regression was used to evaluate the association between retinal vascular parameters and major adverse CV events (MACE) at 10 years compared with the pooled cohort equations (PCE) risk score. RESULTS: Among 5,152 individuals included in the study, a MACE occurred in 1,017 individuals. Reduced arterial fractal dimension and diameter and increased venous tortuosity each independently predicted MACE. A risk score combining these parameters significantly predicted MACE after adjustment for age, sex, PCE, and the CHD PRS (hazard ratio 1.11 per SD increase, 95% CI 1.04-1.18, P = 0.002) with similar accuracy to PCE (area under the curve [AUC] 0.663 vs. 0.658, P = 0.33). A model incorporating retinal parameters and PRS improved MACE prediction compared with PCE (AUC 0.686 vs. 0.658, P < 0.001). CONCLUSIONS: Retinal parameters alone and in combination with genome-wide CHD PRS have independent and incremental prognostic value compared with traditional CV risk assessment in type 2 diabetes.

Retinal Vessel Phenotype in Patients with a History of Retinal Vein Occlusion.

INTRODUCTION: The aim of the study was to estimate the phenotype of retinal vessels using central retinal artery equivalent (CRAE), central retinal vein equivalent (CRVE), tortuosity, and fractal analysis in the unaffected contralateral eye of patients with central or branch retinal vein occlusion (CRVO or BRVO). METHODS: Thirty-four patients suffering from CRVO, 15 suffering from BRVO, and 49 controlled matched subjects had a fundus image analyzed using the VAMPIRE software. The intraclass correlation coefficient and a Bland-Altman plot were done for the reproducibility study. RESULTS: There was a lack of evidence of difference between the control group and the CRVO group for CRAE (p = 0.06), CRVE (p = 0.3), and arterio-venule ratio (AVR, p = 0.6). Contralateral eyes of CRVO exhibited a significantly higher arterial and minimum arterial tortuosity values (p = 0.012), as compared with control eyes. Contralateral eyes of patients with a history of BRVO had a significantly higher CRAE (p = 0.02), AVR (p = 0.006), and minimal arterial tortuosity (p = 0.05). Fractal analysis showed that contralateral eyes of BRVO had higher values of fractal parameters (D0a, p = 0.005). CONCLUSION: This study suggests that CVRO or BRVO is not triggered by the same retinal vascular phenotypes in the contralateral eye. The morphology of retinal vasculature may be associated with the occurrence of RVO, independently of known risk factors.

Effect of a comprehensive deep-learning model on the accuracy of chest x-ray interpretation by radiologists: a retrospective, multireader multicase study.

BACKGROUND: Chest x-rays are widely used in clinical practice; however, interpretation can be hindered by human error and a lack of experienced thoracic radiologists. Deep learning has the potential to improve the accuracy of chest x-ray interpretation. We therefore aimed to assess the accuracy of radiologists with and without the assistance of a deep-learning model. METHODS: In this retrospective study, a deep-learning model was trained on 821 681 images (284 649 patients) from five data sets from Australia, Europe, and the USA. 2568 enriched chest x-ray cases from adult patients (≥16 years) who had at least one frontal chest x-ray were included in the test dataset; cases were representative of inpatient, outpatient, and emergency settings. 20 radiologists reviewed cases with and without the assistance of the deep-learning model with a 3-month washout period. We assessed the change in accuracy of chest x-ray interpretation across 127 clinical findings when the deep-learning model was used as a decision support by calculating area under the receiver operating characteristic curve (AUC) for each radiologist with and without the deep-learning model. We also compared AUCs for the model alone with those of unassisted radiologists. If the lower bound of the adjusted 95% CI of the difference in AUC between the model and the unassisted radiologists was more than -0·05, the model was considered to be non-inferior for that finding. If the lower bound exceeded 0, the model was considered to be superior. FINDINGS: Unassisted radiologists had a macroaveraged AUC of 0·713 (95% CI 0·645-0·785) across the 127 clinical findings, compared with 0·808 (0·763-0·839) when assisted by the model. The deep-learning model statistically significantly improved the classification accuracy of radiologists for 102 (80%) of 127 clinical findings, was statistically non-inferior for 19 (15%) findings, and no findings showed a decrease in accuracy when radiologists used the deep-learning model. Unassisted radiologists had a macroaveraged mean AUC of 0·713 (0·645-0·785) across all findings, compared with 0·957 (0·954-0·959) for the model alone. Model classification alone was significantly more accurate than unassisted radiologists for 117 (94%) of 124 clinical findings predicted by the model and was non-inferior to unassisted radiologists for all other clinical findings. INTERPRETATION: This study shows the potential of a comprehensive deep-learning model to improve chest x-ray interpretation across a large breadth of clinical practice. FUNDING: Annalise.ai.

A review of machine learning methods for retinal blood vessel segmentation and artery/vein classification.

The eye affords a unique opportunity to inspect a rich part of the human microvasculature non-invasively via retinal imaging. Retinal blood vessel segmentation and classification are prime steps for the diagnosis and risk assessment of microvascular and systemic diseases. A high volume of techniques based on deep learning have been published in recent years. In this context, we review 158 papers published between 2012 and 2020, focussing on methods based on machine and deep learning (DL) for automatic vessel segmentation and classification for fundus camera images. We divide the methods into various classes by task (segmentation or artery-vein classification), technique (supervised or unsupervised, deep and non-deep learning, hand-crafted methods) and more specific algorithms (e.g. multiscale, morphology). We discuss advantages and limitations, and include tables summarising results at-a-glance. Finally, we attempt to assess the quantitative merit of DL methods in terms of accuracy improvement compared to other methods. The results allow us to offer our views on the outlook for vessel segmentation and classification for fundus camera images.

Retinal Vessel Phenotype in Patients with Nonarteritic Anterior Ischemic Optic Neuropathy.

PURPOSE: The pathophysiology of nonarteritic anterior ischemic optic neuropathy (NAION) is not completely understood. Studies of the retinal vasculature phenotype in patients with NAION could help us to understand vascular abnormalities associated with the disease. DESIGN: Retrospective case series with matched control subjects. METHODS: Study population: 57 patients with NAION and 57 control subjects matched to NAION patients for sex, age, systemic hypertension, diabetes, and obstructive sleep apnea syndrome between September 2007 and July 2017. MAIN OUTCOME MEASURES: All patients and control subjects underwent a complete ocular examination and 45° funduscopic color photographs. The widths of the 6 largest arteries in zone B (between 0.5 and 1 optic disc diameter from the optic disc), summarized by the central retinal artery equivalent (CRAE), the widths of the 6 largest veins in zone B, summarized by the central retinal vein equivalent (CRVE), the arteriole to venule ratio, tortuosity, and fractal dimension were measured on the 2 groups using Vessel Assessment and Measurement Platform for Images of the Retina, a software tool for efficient semiautomatic quantification of the retinal vasculature morphology in fundus camera images. The Wilcoxon signed-rank test and MacNemar χ2 test for paired sample and generalized estimating equations for modeling the Vessel Assessment and Measurement Platform for Images of the Retina parameters as dependent variables were used. RESULTS: CRVE and fractal dimension (D0a) were significantly higher in the NAION group when compared with the control group, whereas the arteriole to venule ratio and vascular tortuosity were significantly lower. Compared with control subjects, acute NAION yielded an increased CRAE value (174 ± 33 vs 160 ± 13 µm) while resolution NAION yielded a decreased CRAE value (152 ± 12 vs 156 ± 33 µm). Acute NAION yielded an increased CRVE value (244 ± 35 vs 210 ± 21 µm) while resolution NAION yielded an unchanged CRVE value. We found no difference between groups for age, refraction, optic disc diameter, CRAE, or fractal dimension. CONCLUSIONS: Retinal vascular parameters were different in our sample between NAION and control patients, especially at the acute stage of the disease. Our results suggest a normalization of the same parameters at the resolution stage.

A multimodal approach to cardiovascular risk stratification in patients with type 2 diabetes incorporating retinal, genomic and clinical features.

Cardiovascular diseases are a public health concern; they remain the leading cause of morbidity and mortality in patients with type 2 diabetes. Phenotypic information available from retinal fundus images and clinical measurements, in addition to genomic data, can identify relevant biomarkers of cardiovascular health. In this study, we assessed whether such biomarkers stratified risks of major adverse cardiac events (MACE). A retrospective analysis was carried out on an extract from the Tayside GoDARTS bioresource of participants with type 2 diabetes (n = 3,891). A total of 519 features were incorporated, summarising morphometric properties of the retinal vasculature, various single nucleotide polymorphisms (SNPs), as well as routine clinical measurements. After imputing missing features, a predictive model was developed on a randomly sampled set (n = 2,918) using L1-regularised logistic regression (lasso). The model was evaluated on an independent set (n = 973) and its performance associated with overall hazard rate after censoring (log-rank p < 0.0001), suggesting that multimodal features were able to capture important knowledge for MACE risk assessment. We further showed through a bootstrap analysis that all three sources of information (retinal, genetic, routine clinical) offer robust signal. Particularly robust features included: tortuousity, width gradient, and branching point retinal groupings; SNPs known to be associated with blood pressure and cardiovascular phenotypic traits; age at imaging; clinical measurements such as blood pressure and high density lipoprotein. This novel approach could be used for fast and sensitive determination of future risks associated with MACE.

Nonlinearity from stress corrosion cracking as a function of chloride exposure time using the time reversed elastic nonlinearity diagnostic.

The Time Reversed Elastic Nonlinearity Diagnostic (TREND) has a long history of successful nondestructive detection of cracks in solids using nonlinear indicators. Recent research implemented TREND to find stress corrosion cracking (SCC) in the heat-affected zone adjacent to welds in stainless steel. SCC development around welds is likely to occur due to the temperature and chemical exposure of steel canisters housing spent nuclear fuel. The ideal SCC detection technique would quantify the size and extent of the SCC, rather than just locating it, as TREND has been used for in the past. The current paper explores TREND's ability to detect an assumed increase in SCC over time using 13 samples exposed to a magnesium chloride (MgCl2) bath for different lengths of time. The samples are then scanned with TREND and nonlinearity is quantified for each scan point and each sample. The results suggest that TREND can be used to not only locate SCC in the heat-affected zone, but also track an increase in nonlinearity, and thereby an increase in damage, in samples exposed to the MgCl2 solution for a longer duration.

Retinal microvascular parameters are not associated with reduced renal function in a study of individuals with type 2 diabetes.

The eye provides an opportunistic "window" to view the microcirculation. There is published evidence of an association between retinal microvascular calibre and renal function measured by estimated glomerular filtration rate (eGFR) in individuals with diabetes mellitus. Beyond vascular calibre, few studies have considered other microvascular geometrical features. Here we report novel null findings for measures of vascular spread (vessel fractal dimension), tortuosity, and branching patterns and their relationship with renal function in type 2 diabetes over a mean of 3 years. We performed a nested case-control comparison of multiple retinal vascular parameters between individuals with type 2 diabetes and stable (non-progressors) versus declining (progressors) eGFR across two time points within a subset of 1072 participants from the GoDARTS study cohort. Retinal microvascular were measured using VAMPIRE 3.1 software. In unadjusted analyses and following adjustment for age, gender, systolic blood pressure, HbA1C, and diabetic retinopathy, no associations between baseline retinal vascular parameters and risk of eGFR progression were observed. Cross-sectional analysis of follow-up data showed a significant association between retinal arteriolar diameter and eGFR, but this was not maintained following adjustment. These findings are consistent with a lack of predictive capacity for progressive loss of renal function in type 2 diabetes.

Are SSRIs responsible for precipitating suicidal ideation in teenagers with 'subsyndromal' bipolar affective disorder who have been misdiagnosed with unipolar depression?

Concerns have recently been raised about a possible link between suicidal ideation and the use of SSRIs in teenagers diagnosed with unipolar depression, such that the USA FDA and UK CSM have issued warnings regarding the use of SSRIs in adolescents with depression. We investigated this phenomenon first by recognizing that the initial presentation of unipolar and bipolar depression may only differ in subtle ways and with the result being that a significant number of patients are misdiagnosed at the expense of patient outcomes. This is especially pertinent as patients with bipolar disorder have increased lifetime rates of suicide as compared with those patients with unipolar depression. The normal developmental trajectory of bipolar disorder often involves recurrent depressive episodes in early adolescence before the development of hypomanic/manic episodes. Therefore, a misdiagnosis of bipolar disorder as unipolar depression in teenagers could explain the failure of SSRIs to adequately treat depressive episodes. A suboptimal response to SSRIs and so a lack of control of the depression is a risk factor for suicide. One reason for this suboptimal response is the markedly different neurotransmission involved in bipolar depression as compared to the neurotransmitter systems operated on by SSRIs. In bipolar disorder, dopamine is the principal neurotransmitter disrupted and we marshal structural, pharmacological and biochemical evidence to support this claim. One important strand of evidence involves polymorphisms in D1 and D2 dopamine receptors being implicated in the pathogenesis of bipolar affective disorder. Serotonin neurotransmission is affected by SSRIs, however the role of serotonin in bipolar disorder is much more ambiguous. The conclusion we arrive at is that the link between suicidality and SSRI use in adolescents diagnosed with unipolar depression may in fact be due to inappropriate treatment of misdiagnosed bipolar disorder that has yet to manifest with hypomanic/manic symptoms.

Discrimination between parkinsonian syndrome and essential tremor using artificial neural network classification of quantified DaTSCAN data.

BACKGROUND: In the semi-quantitative assessment of DaTSCAN images, it has been suggested that the ratio of tracer accumulation in the putamen to that in the caudate nucleus may be helpful and could allow parkinsonian syndromes progression to be assessed. Separation of ratio values has been reported when early Parkinson's disease is compared with essential tremor. The separation is lost, however, when the Parkinson's disease is not early stage. OBJECTIVES: To evaluate whether a two-stage analysis can differentiate between parkinsonian syndromes, of various stages, and essential tremor, and whether such a two-stage analysis can be undertaken in a single step using artificial neural networks (ANNs). METHODS: Data from 18 patients were analysed. Quantification was undertaken by manually drawing irregular regions of interest (ROIs): over each caudate nucleus and putamen and over an occipital cortex area near the posterior edge of the brain. A two-stage analysis was undertaken and was repeated, in a single step, using an ANN. RESULTS: The first stage, of the two-stage analysis, identified 12 patients with non-early parkinsonian syndromes. The remaining six patients were then successfully classified into early parkinsonian syndromes and essential tremor. The ANN analysis successfully discriminated parkinsonian syndromes from essential tremor, in all patients, in a single step. CONCLUSIONS: The two-stage process provides a method for classifying early disease without being compromised by the noise from non-early disease. The results of the single stage ANN analysis were very definite and it may be considered to have potential in the quantification of DaTSCAN images for clinical use.