Automatic detection of prostate cancer grades and chronic prostatitis in biparametric MRI.

BACKGROUND AND OBJECTIVE: With emerging evidence to improve prostate cancer (PCa) screening, multiparametric magnetic prostate imaging is becoming an essential noninvasive component of the diagnostic routine. Computer-aided diagnostic (CAD) tools powered by deep learning can help radiologists interpret multiple volumetric images. In this work, our objective was to examine promising methods recently proposed in the multigrade prostate cancer detection task and to suggest practical considerations regarding model training in this context. METHODS: We collected 1647 fine-grained biopsy-confirmed findings, including Gleason scores and prostatitis, to form a training dataset. In our experimental framework for lesion detection, all models utilized 3D nnU-Net architecture that accounts for anisotropy in the MRI data. First, we explore an optimal range of b-values for diffusion-weighted imaging (DWI) modality and its effect on the detection of clinically significant prostate cancer (csPCa) and prostatitis using deep learning, as the optimal range is not yet clearly defined in this domain. Next, we propose a simulated multimodal shift as a data augmentation technique to compensate for the multimodal shift present in the data. Third, we study the effect of incorporating the prostatitis class alongside cancer-related findings at three different granularities of the prostate cancer class (coarse, medium, and fine) and its impact on the detection rate of the target csPCa. Furthermore, ordinal and one-hot encoded (OHE) output formulations were tested. RESULTS: An optimal model configuration with fine class granularity (prostatitis included) and OHE has scored the lesion-wise partial Free-Response Receiver Operating Characteristic (FROC) area under the curve (AUC) of 1.94 (CI 95%: 1.76-2.11) and patient-wise ROC AUC of 0.874 (CI 95%: 0.793-0.938) in the detection of csPCa. Inclusion of the auxiliary prostatitis class has demonstrated a stable relative improvement in specificity at a false positive rate (FPR) of 1.0 per patient, with an increase of 3%, 7%, and 4% for coarse, medium, and fine class granularities. CONCLUSIONS: This paper examines several configurations for model training in the biparametric MRI setup and proposes optimal value ranges. It also shows that the fine-grained class configuration, including prostatitis, is beneficial for detecting csPCa. The ability to detect prostatitis in all low-risk cancer lesions suggests the potential to improve the quality of the early diagnosis of prostate diseases. It also implies an improved interpretability of the results by the radiologist.

Effect of Past Pharmacotherapy for Attention-Deficit/Hyperactivity Disorder on Substance Use Disorder.

BACKGROUND: Substance use disorders (SUDs) are a considerable public health problem. Attention-deficit/hyperactivity disorder (ADHD) frequently occurs in patients with SUD. Several studies demonstrated that ADHD constitutes a significant risk factor for the development of SUDs and suggest that childhood ADHD pharmacotherapy might help prevent development of SUD. OBJECTIVES: The study aimed to explore the effect of childhood ADHD pharmacotherapy on later life's functional impairment and substance use patterns. METHODS: Treatment-seeking SUD patients with ADHD (n = 52) were recruited from various rehabilitation facilities in South Africa. Adult ADHD individuals without SUD (n = 48) were recruited from clinicians, retail pharmacies, and the general public. SUD participants in rehabilitation facilities were screened for and diagnosed with ADHD. Lifetime substance use was assessed using self-report. ADHD-related functional impairment was assessed by the Weiss Functional Impairment Rating Scale (WFIRS). Information on present and lifetime use of ADHD medication was obtained. Clinical outcomes between those with and without a history of ADHD pharmacotherapy were compared. RESULTS: Medicated participants (n = 59) showed lower levels of ADHD-related impairment across all functional domains (p < 0.001), compared to non-medicated participants (n = 41). They also consumed less alcohol (p = 0.04), cannabis (p < 0.001), and illicit drugs (p = 0.006) compared to the non-medicated group. Furthermore, medicated participants had a lower frequency of tobacco use compared to non-medicated participants (p = 0.04). ADHD patients without SUD also more often received medication (100% vs. 18.6%; p < 0.001) and for a longer time (121.10 vs. 9.52 months; p < 0.001). CONCLUSION: Childhood ADHD pharmacotherapy might be associated with a decreased risk for substance use in adulthood and lower ADHD-related impairment. Despite study limitations, these findings underline the importance of early ADHD detection and treatment, which might prevent SUD.

Predicting 4D liver MRI for MR-guided interventions.

Organ motion poses an unresolved challenge in image-guided interventions like radiation therapy, biopsies or tumor ablation. In the pursuit of solving this problem, the research field of time-resolved volumetric magnetic resonance imaging (4D MRI) has evolved. However, current techniques are unsuitable for most interventional settings because they lack sufficient temporal and/or spatial resolution or have long acquisition times. In this work, we propose a novel approach for real-time, high-resolution 4D MRI with large fields of view for MR-guided interventions. To this end, we propose a network-agnostic, end-to-end trainable, deep learning formulation that enables the prediction of a 4D liver MRI with respiratory states from a live 2D navigator MRI. Our method can be used in two ways: First, it can reconstruct high quality fast (near real-time) 4D MRI with high resolution (209×128×128 matrix size with isotropic 1.8mm voxel size and 0.6s/volume) given a dynamic interventional 2D navigator slice for guidance during an intervention. Second, it can be used for retrospective 4D reconstruction with a temporal resolution of below 0.2s/volume for motion analysis and use in radiation therapy. We report a mean target registration error (TRE) of 1.19±0.74mm, which is below voxel size. We compare our results with a state-of-the-art retrospective 4D MRI reconstruction. Visual evaluation shows comparable quality. We compare different network architectures within our formulation. We show that small training sizes with short acquisition times down to 2 min can already achieve promising results and 24 min are sufficient for high quality results. Because our method can be readily combined with earlier time reducing methods, acquisition time can be further decreased while also limiting quality loss. We show that an end-to-end, deep learning formulation is highly promising for 4D MRI reconstruction.

Differences in alcohol and cannabis use amongst substance use disorder patients with and without comorbid attention-deficit/hyperactivity disorder.

Background: Substance use disorders (SUDs) continue to be a public health problem. Attention-deficit/hyperactivity disorder (ADHD) is seen as a risk factor for SUD. Prevalence of alcohol and cannabis use amongst adults with SUD and comorbid ADHD impacts both disorders cognitively and behaviourally. Aim: Our study aimed to compare alcohol and cannabis use between treatment-seeking SUD patients with ADHD and SUD patients without ADHD symptomatology. Setting: Various rehabilitation centres, including the South African National Council on Alcoholism and Drug Dependence (SANCA) Centres, and Private and Provincial Government Substance Abuse Treatment Centres. Methods: A cross-sectional study of adults on drug rehabilitation was conducted. Data on socio-demographic information and alcohol and cannabis use from 185 post-detox inpatients were collected. Diagnoses were based on DSM-IV criteria. Attention-deficit/hyperactivity disorder diagnosis was confirmed by the Diagnostic-Interview for ADHD in Adults (DIVA 2.0). SUD+ADHD (n = 52) and SUD-ADHD (n = 128) groups were compared on alcohol and cannabis use as a function of gender. Results: No significant differences in the use of alcohol between the SUD+ADHD and SUD-ADHD groups were found. However, the SUD+ADHD group showed increased cannabis consumption. Especially, the SUD+ADHD females showed an earlier age of onset of cannabis use than the SUD-ADHD females and revealed that they use cannabis for a longer period compared with the SUD-ADHD females and SUD+ADHD and SUD-ADHD males. Conclusion: The results revealed the relationship between ADHD and cannabis use, especially amongst females with ADHD and reinforce the need to consider ADHD in cannabis use SUD in clinical interventions.

Working memory and set-shifting in school-aged children classified as having attention-deficit hyperactivity disorder.

BACKGROUND: Attention-deficit hyperactivity disorder (ADHD) is a common psychiatric disorder reported in both children and adults; it is often associated with a variety of executive functioning deficits. AIM: This study investigated the extent to which working memory and set-shifting are impaired in school children with and without ADHD. SETTING: This included primary schools in Lepelle-Nkumpi Municipality in Limpopo province, South Africa. METHODS: A total of 216 children (108 screened positive for ADHD and 108 matched controls without ADHD symptoms), aged between 6 and 15 years, participated in the study. The performance of the two groups was compared on tests of working memory (Forward and Backward Digit Span subtests of the Wechsler Intelligence Scale for Children - Fourth Edition) and set-shifting (Trail Making Test Part B). The scores were analysed as a function of gender and age. RESULTS: The group with possible ADHD performed worse than the neurotypical control group on tasks of working memory and set-shifting. The results did not indicate that gender affected performance. However, the younger age group performed worse than the older children. CONCLUSION: Children classified as ADHD showed significantly more impairments in working memory and set-shifting than neurotypical controls. Neither test showed any significant difference between male and female performance, whilst age was shown to affect performance on both tests. Early identification and treatment of children with attention-deficit hyperactivity disorder are crucial to their well-being.

Domain adaptation for segmentation of critical structures for prostate cancer therapy.

Preoperative assessment of the proximity of critical structures to the tumors is crucial in avoiding unnecessary damage during prostate cancer treatment. A patient-specific 3D anatomical model of those structures, namely the neurovascular bundles (NVB) and the external urethral sphincters (EUS), can enable physicians to perform such assessments intuitively. As a crucial step to generate a patient-specific anatomical model from preoperative MRI in a clinical routine, we propose a multi-class automatic segmentation based on an anisotropic convolutional network. Our specific challenge is to train the network model on a unique source dataset only available at a single clinical site and deploy it to another target site without sharing the original images or labels. As network models trained on data from a single source suffer from quality loss due to the domain shift, we propose a semi-supervised domain adaptation (DA) method to refine the model's performance in the target domain. Our DA method combines transfer learning and uncertainty guided self-learning based on deep ensembles. Experiments on the segmentation of the prostate, NVB, and EUS, show significant performance gain with the combination of those techniques compared to pure TL and the combination of TL with simple self-learning ([Formula: see text] for all structures using a Wilcoxon's signed-rank test). Results on a different task and data (Pancreas CT segmentation) demonstrate our method's generic application capabilities. Our method has the advantage that it does not require any further data from the source domain, unlike the majority of recent domain adaptation strategies. This makes our method suitable for clinical applications, where the sharing of patient data is restricted.

Uncertainty-aware temporal self-learning (UATS): Semi-supervised learning for segmentation of prostate zones and beyond.

Various convolutional neural network (CNN) based concepts have been introduced for the prostate's automatic segmentation and its coarse subdivision into transition zone (TZ) and peripheral zone (PZ). However, when targeting a fine-grained segmentation of TZ, PZ, distal prostatic urethra (DPU) and the anterior fibromuscular stroma (AFS), the task becomes more challenging and has not yet been solved at the level of human performance. One reason might be the insufficient amount of labeled data for supervised training. Therefore, we propose to apply a semi-supervised learning (SSL) technique named uncertainty-aware temporal self-learning (UATS) to overcome the expensive and time-consuming manual ground truth labeling. We combine the SSL techniques temporal ensembling and uncertainty-guided self-learning to benefit from unlabeled images, which are often readily available. Our method significantly outperforms the supervised baseline and obtained a Dice coefficient (DC) of up to 78.9%, 87.3%, 75.3%, 50.6% for TZ, PZ, DPU and AFS, respectively. The obtained results are in the range of human inter-rater performance for all structures. Moreover, we investigate the method's robustness against noise and demonstrate the generalization capability for varying ratios of labeled data and on other challenging tasks, namely the hippocampus and skin lesion segmentation. UATS achieved superiority segmentation quality compared to the supervised baseline, particularly for minimal amounts of labeled data.

Headache and migraine in mitochondrial disease and its impact on life-results from a cross-sectional, questionnaire-based study.

Headache is frequent in patients with mitochondrial disorders. Previous studies point to a higher prevalence of headache in these patients than in the general population. As mitochondrial disorders often present a variety of other symptoms, the question arises how much the presence of headache really influences daily life. We performed a cross-sectional, questionnaire-based study investigation with 61 patients with a genetically proved mitochondrial disease mainly composed of CPEO phenotype. Headache was examined using a standardized questionnaire, and classified according to ICHD-2. Headache-related disability was evaluated by the Headache-Impact-Test-6 (HIT-6). Additionally, depression and anxiety were examined using the Hospital Anxiety and Depression Scale (HADS) and Short-Form-Health Survey (SF-12) was used to investigate the health-related quality of life. Headache was reported by 43/61 (70.5%) of the patients. 35/61 patients (57.4%) described a Tension-type headache (TTH) and 26 patients (42.6%) a migraine. Patients reporting headache had a significantly higher HIT-6 score than those without (mean: 54.47 vs. 38.47, p < 0.001). The HIT-6 score was significantly higher in patients reporting a migraine compared to those with a tension-type headache (mean: 62.13 vs. 46.18, p < 0.001). In the HADS score and in the SF-12 were not significantly influenced by the occurrence of headache. This study confirms the previously reported frequent occurrence of headache in a large cohort of patients with a confirmed mitochondrial disease. Migraine had the greatest impact on daily living, which appeared not to be confounded by depression and anxiety. Thus, we conclude that Migraine may be a substantial contributor for burden of disease in patients with mitochondrial diseases.

Anisotropic 3D Multi-Stream CNN for Accurate Prostate Segmentation from Multi-Planar MRI.

BACKGROUND AND OBJECTIVE: Accurate and reliable segmentation of the prostate gland in MR images can support the clinical assessment of prostate cancer, as well as the planning and monitoring of focal and loco-regional therapeutic interventions. Despite the availability of multi-planar MR scans due to standardized protocols, the majority of segmentation approaches presented in the literature consider the axial scans only. In this work, we investigate whether a neural network processing anisotropic multi-planar images could work in the context of a semantic segmentation task, and if so, how this additional information would improve the segmentation quality. METHODS: We propose an anisotropic 3D multi-stream CNN architecture, which processes additional scan directions to produce a high-resolution isotropic prostate segmentation. We investigate two variants of our architecture, which work on two (dual-plane) and three (triple-plane) image orientations, respectively. The influence of additional information used by these models is evaluated by comparing them with a single-plane baseline processing only axial images. To realize a fair comparison, we employ a hyperparameter optimization strategy to select optimal configurations for the individual approaches. RESULTS: Training and evaluation on two datasets spanning multiple sites show statistical significant improvement over the plain axial segmentation (p<0.05 on the Dice similarity coefficient). The improvement can be observed especially at the base (0.898 single-plane vs. 0.906 triple-plane) and apex (0.888 single-plane vs. 0.901 dual-plane). CONCLUSION: This study indicates that models employing two or three scan directions are superior to plain axial segmentation. The knowledge of precise boundaries of the prostate is crucial for the conservation of risk structures. Thus, the proposed models have the potential to improve the outcome of prostate cancer diagnosis and therapies.

Internalising comorbidities in primary school children with attention-deficit hyperactivity disorder (ADHD): sex and age differences.

Objectives: Studies suggest that females with ADHD display more symptoms of anxiety and depression than their male counterparts. This study attempted to determine comorbid anxiety and depression in children with ADHD. Further, we aimed to establish whether there are sex and age differences in the expression of comorbid symptoms. Method: The Beck Anxiety Inventory and Beck Depression scale from the Beck Youth Inventory were administered to 216 participants (108 with ADHD and 108 matched controls without ADHD symptoms). Participants included children aged 6 to 15 years, resident in the Limpopo Province of South Africa. The groups were compared for comorbid anxiety and depression symptoms and analysed as a function of sex and age. Results: The ADHD group showed significantly more symptoms of anxiety and depression than the neurotypical control group. However, no sex differences were observed in the expression of anxiety symptoms. Nonetheless, girls did show significantly higher levels of depression than boys. No age differences were detected in respect of anxiety symptoms. Conclusion: Children with ADHD displayed more symptoms of anxiety and depression compared to controls without ADHD. Age and sex did not affect anxiety symptoms, however girls showed more symptoms of depression than boys.

Attention-deficit/hyperactivity disorder and behavioural planning deficiencies in South African primary school children.

BACKGROUND: Attention-deficit/hyperactivity disorder (ADHD) is defined as a cognitive or behavioural developmental disorder. Inattentiveness, overactivity and impulsivity are regarded as the main clinical symptoms of ADHD. These symptoms may occur together or separately resulting in three recognised presentations: predominantly inattentive, predominantly hyperactive-impulsive and combined presentations. AIM: This study investigated deficiencies in behavioural planning in South African primary school children with and without ADHD. SETTING: Tzaneen area in Limpopo province, South Africa. METHODS: A total of 156 children (78 with ADHD and 78 matched controls without ADHD) of both genders, who were medication naïve and aged 6-15 years, participated in the study. The performance of the two groups was compared on a test of planning and problem-solving, the Tower of London (ToL) task. The results were analysed as a function of gender, age and ADHD presentation. RESULTS: Children with ADHD especially ADHD-PI and ADHD-C used significantly more moves and took a longer time to complete the task than the controls (p < 0.001). There were no significant differences in the number of moves and time taken by the predominantly hyperactive-impulsive presentations of ADHD when compared to the controls. Gender and age did not influence the performance. CONCLUSION: The results showed that children with ADHD showed significantly more deficits mainly the ADHD-PI and ADHD-C presentations, which indicates that inattention is mainly responsible for deficiencies in behaviour planning. The ADHD-HI presentations and the control group were not affected.

Prevalence and characteristics of South African treatment-seeking patients with substance use disorder and co-occurring attention-deficit/hyperactivity disorder.

BACKGROUND: Attention-Deficit/Hyperactivity Disorder (ADHD) constitutes a significant risk factor for the development of Substance Use Disorders (SUDs). Individuals with both conditions use more substances, and the pattern of substance use seems to differ between individuals with and without ADHD. RESEARCH AIM AND OBJECTIVES: To establish the prevalence of ADHD symptoms in adult South African treatment-seeking patients with SUD, and the pattern of substance use and presence of previous ADHD diagnoses and pharmacotherapy. METHODS: Adult patients (N = 360) were recruited from rehabilitation facilities and screened using the ADHD Self-Report Scale Symptom Checklist (ASRS-v1.1). Questions included demographics, substance consumption and current/historical use of ADHD-indicated medication. RESULTS: A third (36.0%) of patients with SUD screened positive for ADHD - 14.6% had been diagnosed with ADHD prior to admission, and indicated pharmacotherapy, while 68.5% of those screened positive were not hitherto diagnosed with ADHD (p < 0.001). A statistical difference was found for polysubstance use with the ADHD group significantly being treated more frequently for use of more than one substance (p = 0.04). CONCLUSIONS AND IMPLICATIONS: High rates of untreated and unrecognized ADHD were found among treatment-seeking SUD patients. Preventative strategies are crucial to reduce substance use and the development of SUD in individuals affected by ADHD.

Translation of the Adult Attention-Deficit/Hyperactivity Disorder Self-Report Scale into an African Language: An Exploratory Study.

BACKGROUND: Attention-Deficit/Hyperactivity Disorder (ADHD) is commonly perceived as a cultural construct due to its disproportionate global representation, however limited data is available from Africa. Standardisation of screening tools in epidemiological studies is essential for global prevalence comparison, but tools such as the Adult ADHD Self-Report Scale (ASRS) have not been translated into African languages. OBJECTIVE: To assess the translation process followed in attempting to adapt the ASRS into an indigenous African language widely spoken within South Africa for cross-cultural research. METHOD: Xhosa was selected as an appropriate target language for translation. An exploratory approach was used to assess linguistic considerations for adaptation of the ASRS. Blind translation was applied by two independent bilingual translators. A translational studies expert translated the ASRS into Xhosa. The translated document was back-translated into English by a bilingual pharmacist. KEY FINDINGS: Side-by-side comparison of the original and back-translated English versions revealed 13 content queries. Each query was discussed with the back translator, revealing common themes which complicated the effective Xhosa ASRS translation. Appropriate contextualisation of questions and removal or explanation of idiomatic terms were identified as key requirements to improve properties for Xhosa translation. CONCLUSION: Suitability of the original instrument for Xhosa translation was problematic and further investigation into appropriate cross-cultural translation techniques is needed to improve ASRS translation properties and assess its Xhosa translation. Development of a suitable Xhosa version of the ASRS is considered to be an important step towards broadening the scope of ADHD research in South Africa.

Combining convolutional neural networks and star convex cuts for fast whole spine vertebra segmentation in MRI.

BACKGROUND AND OBJECTIVE: We propose an automatic approach for fast vertebral body segmentation in three-dimensional magnetic resonance images of the whole spine. Previous works are limited to the lower thoracolumbar section and often take minutes to compute, which is problematic in clinical routine, for study data sets with numerous subjects or when the cervical or upper thoracic spine is to be analyzed. METHODS: We address these limitations by a novel graph cut formulation based on vertebra patches extracted along the spine. For each patch, our formulation incorporates appearance and shape information derived from a task-specific convolutional neural network as well as star-convexity constraints that ensure a topologically correct segmentation of each vertebra. When segmenting vertebrae individually, ambiguities will occur due to overlapping segmentations of adjacent vertebrae. We tackle this problem by novel non-overlap constraints between neighboring patches based on so-called encoding swaps. The latter allow us to obtain a globally optimal multi-label segmentation of all vertebrae in polynomial time. RESULTS: We validated our approach on two data sets. The first contains T1- and T2-weighted whole spine images of 64 subjects with varying health conditions. The second comprises 23 T2-weighted thoracolumbar images of young healthy adults and is publicly available. Our method yielded Dice coefficients of 93.8 â€¯±â€¯ 2.6% and 96.0 â€¯±â€¯ 1.0% for both data sets with a run time of 1.35 â€¯±â€¯ 0.08 s and 0.90 â€¯±â€¯ 0.03 s per vertebra on consumer hardware. A complete whole spine segmentation took 32.4 ±â€¯1.92 s on average. CONCLUSIONS: Our results are superior to those of previous works at a fraction of their run time, which illustrates the efficiency and effectiveness of our whole spine segmentation approach.

A pilot study: Use of the Adult Attention-Deficit/Hyperactivity Disorder Self-Report Scale in a South African patient population.

BACKGROUND: Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder which typically presents in childhood. This diagnosis may often be overlooked in adulthood, particularly in psychiatric populations. The Adult ADHD Self-Report Scale (ASRS) is an internationally used and reliable screener; however, studies investigating its use in African populations are limited. AIM: To investigate the application of the ASRS in a South African setting. SETTING: A patient population in Port Elizabeth, South Africa, was identified as representing a developing or low- and middle-income country population. METHODS: A convenience sample of acutely presenting psychiatric participants admitted for stabilisation was used. Fieldworkers administered the ASRS; collected information relating to demographics, differential diagnoses, substance use disorder (SUD) presence and substance consumption; and prescribed medication relating to current or historical treatment of ADHD. RESULTS: The study sample included 30 participants, with black people representing the majority of participants. Adult ADHD Self-Report Scale completion revealed the rate of ADHD within the study population to be 43.3%, a contrast to the initially presumed prevalence of 6.7% which was based on reported methylphenidate therapy. A difference in SUD prevalence was identified between subjects screening positively and negatively for ADHD with a greater tendency towards SUDs seen for ASRS-positive individuals. Significant differences were identified in relation to cannabis- and polysubstance use for ASRS-positive individuals. CONCLUSION: Despite limitations related to the sample used and challenges in ASRS administration, investigation findings support recommendations for ADHD screening inclusion in acute inpatient settings in South Africa and ASRS translation into indigenous African languages.

Fine motor deficits and attention deficit hyperactivity disorder in primary school children.

BACKGROUND: Many children with attention deficit hyperactivity disorder (ADHD) display motor deficiencies during their daily routine, which may have impact on their developmental course. Children with ADHD who experience motor deficiencies often display deficits in tasks requiring movements, such as handwriting. AIM: This study investigated deficiencies in fine motor skills in primary school children with ADHD. The study further sought to establish whether ADHD subtypes differ in deficiencies of fine motor performance, recorded for both the dominant and non-dominant hands. METHODS: The Disruptive Behavior Disorders Rating Scale, completed by educators and parents, was used to screen for ADHD symptoms. Researchers confirmed the diagnosis of ADHD. Motor functioning was assessed using the Grooved Pegboard and Maze Coordination. The children diagnosed with ADHD were matched for age and gender with controls without ADHD. The sample consisted of an ADHD group (160) and control group (160) of primary school children from the Moletjie area. RESULTS: Children with ADHD (predominantly inattentive subtype) and ADHD (combined subtype) performed significantly more poorly than the control group on the Grooved Pegboard (p < 0.05) with both the dominant and non-dominant hand. No significant difference between the hyperactivity and impulsiveness subtype and the controls were found. There was no difference on the Maze Coordination Task (p > 0.05) between the ADHD subtypes and the controls. CONCLUSION: Difficulties in fine motor skills are prevalent in children with ADHD, particularly in the ADHD-PI and ADHD-C. Problems are encountered in distal, complex, speeded tasks. The effect may lead to poor handwriting and academic performance.

Fine motor deficits and attention deficit hyperactivity disorder in primary school children

Background: Many children with attention deficit hyperactivity disorder (ADHD) display motor deficiencies during their daily routine, which may have impact on their developmental course. Children with ADHD who experience motor deficiencies often display deficits in tasks requiring movements, such as handwriting.Aim: This study investigated deficiencies in fine motor skills in primary school children with ADHD. The study further sought to establish whether ADHD subtypes differ in deficiencies of fine motor performance, recorded for both the dominant and non-dominant hands. Methods: The Disruptive Behavior Disorders Rating Scale, completed by educators and parents, was used to screen for ADHD symptoms. Researchers confirmed the diagnosis of ADHD. Motor functioning was assessed using the Grooved Pegboard and Maze Coordination. The children diagnosed with ADHD were matched for age and gender with controls without ADHD. The sample consisted of an ADHD group (160) and control group (160) of primary school children from the Moletjie area.Results: Children with ADHD (predominantly inattentive subtype) and ADHD (combined subtype) performed significantly more poorly than the control group on the Grooved Pegboard (p < 0.05) with both the dominant and non-dominant hand. No significant difference between the hyperactivity and impulsiveness subtype and the controls were found. There was no difference on the Maze Coordination Task (p > 0.05) between the ADHD subtypes and the controls.Conclusion: Difficulties in fine motor skills are prevalent in children with ADHD, particularly in the ADHD-PI and ADHD-C. Problems are encountered in distal, complex, speeded tasks. The effect may lead to poor handwriting and academic performance

Critical exploration of co-occurring Attention-Deficit/Hyperactivity Disorder, mood disorder and Substance Use Disorder.

INTRODUCTION: Co-occurring disorders (CODs) describe a Substance Use Disorder (SUD) accompanied by a comorbid psychiatric disorder. Attention-Deficit/Hyperactivity Disorder (ADHD) and mood disorders are common CODs with high prevalence rates in SUD populations. It is proposed that literature on a tri-condition presentation of ADHD, mood disorder and SUD is limited. Areas covered: A literature search was conducted using a keyword search on EBSCOhost. Initially 2 799 records were identified, however, only two articles included all three conditions occurring concurrently in individuals. CODs constitute a major concern due to their overarching burden on society as a whole. Diagnosis and treatment of such patients is challenging. There is evidence that dysfunction of dopamine in the brain reward circuitry impacts the development or symptomology of all three disorders. Disparity exists regarding whether ADHD or mood disorders are greater modifiers for increased SUD severity. However, it has been reported that poor functional capacity may have a greater influence than comorbidities on SUD development. Expert commentary: Challenges exist which confound the clear distinction of CODs, however, with greater emergence of adult ADHD its screening in SUD populations should become standard practice to establish data on multi-condition presentations with the ultimate goal of improving clinical outcomes.

Behaviour planning and problem solving deficiencies in children with symptoms of attention deficit hyperactivity disorder from the Balobedu culture, Limpopo province, South Africa.

OBJECTIVE: To compare planning behaviour (frontal lobe functioning) in children with and without symptoms of attention deficit hyperactivity disorder (ADHD). METHOD: A total of 90 children (45 with symptoms of ADHD and 45 matched controls without ADHD symptoms) of both genders, who were medication naïve, from the Balobedu culture (Limpopo province, South Africa), aged 7-13 years, participated in the study. The performance of the two groups was compared on a test of planning and problem solving, the Tower of London (ToL) task. The results were analysed as a function of gender and ADHD subtype. The Finger Tapping test (testing fine motor skills) was used as a control test to verify that the expected differences were not due to poor motor skills. RESULTS: The children with ADHD symptoms scored significantly lower than the non-ADHD comparison group which indicated deficiency in frontal lobe functioning (p = 0.00). The difference in performance was not due to poor motor control (p = 0.70). CONCLUSION: Children with ADHD symptoms show deficits in behavioural planning which indicates impairment of functions of the frontal areas supplied by the mesocortical dopamine branch. More so than others, the ADHD Inattentive and Combined subtypes showed poor performance in the Tower of London task, indicating poor organisational and planning skills in these groups. The results also did show that the difference was not due to problems with motor control and that the ToL task is a culture-fair instrument for testing planning behaviour.

It takes two-coincidence coding within the dual olfactory pathway of the honeybee.

To rapidly process biologically relevant stimuli, sensory systems have developed a broad variety of coding mechanisms like parallel processing and coincidence detection. Parallel processing (e.g., in the visual system), increases both computational capacity and processing speed by simultaneously coding different aspects of the same stimulus. Coincidence detection is an efficient way to integrate information from different sources. Coincidence has been shown to promote associative learning and memory or stimulus feature detection (e.g., in auditory delay lines). Within the dual olfactory pathway of the honeybee both of these mechanisms might be implemented by uniglomerular projection neurons (PNs) that transfer information from the primary olfactory centers, the antennal lobe (AL), to a multimodal integration center, the mushroom body (MB). PNs from anatomically distinct tracts respond to the same stimulus space, but have different physiological properties, characteristics that are prerequisites for parallel processing of different stimulus aspects. However, the PN pathways also display mirror-imaged like anatomical trajectories that resemble neuronal coincidence detectors as known from auditory delay lines. To investigate temporal processing of olfactory information, we recorded PN odor responses simultaneously from both tracts and measured coincident activity of PNs within and between tracts. Our results show that coincidence levels are different within each of the two tracts. Coincidence also occurs between tracts, but to a minor extent compared to coincidence within tracts. Taken together our findings support the relevance of spike timing in coding of olfactory information (temporal code).