Phase 1, placebo-controlled, single ascending dose trial to evaluate the safety, pharmacokinetics and effect on altered states of consciousness of intranasal BPL-003 (5-methoxy-N,N-dimethyltryptamine benzoate) in healthy participants.

AIMS: To investigate the safety, tolerability, pharmacokinetics (PK) and pharmacodynamics (PD) of BPL-003, a novel intranasal benzoate salt formulation of 5-methoxy-N,N-dimethyltryptamine (5-MeO-DMT), in healthy participants. METHODS: In all, 44 psychedelic-naïve participants enrolled in the double-blind, placebo-controlled single ascending dose study (1-12 mg BPL-003). Concentrations of 5-MeO-DMT and its pharmacologically active metabolite, bufotenine, were determined in plasma and urine. PD endpoints included subjective drug intensity (SDI) rating, the Mystical Experience Questionnaire (MEQ-30) and the Ego Dissolution Inventory (EDI). RESULTS: BPL-003 was well tolerated at doses up to 12 mg. There were no serious adverse events (AEs), and most AEs were mild; the most common being nasal discomfort, nausea, headache and vomiting. 5-MeO-DMT was rapidly absorbed and eliminated; the median time to peak plasma concentration was approximately 8-10 min and the mean terminal elimination half-life was <27 min. 5-MeO-DMT systemic exposure increased approximately dose-proportionally, while plasma bufotenine concentrations and urinary excretion of 5-MeO-DMT and bufotenine were negligible. The intensity of the SDI ratings was associated with plasma 5-MeO-DMT concentrations. MEQ-30 and EDI scores generally increased with the BPL-003 dose; 60% of participants had a 'complete mystical experience' at 10 and 12 mg doses. Profound and highly emotional consciousness-altering effects were observed with BPL-003, with a rapid onset and short-lasting duration. CONCLUSION: The novel intranasal formulation of BPL-003 was well tolerated with dose-proportional increases in PK and PD effects. The short duration of action and induction of mystical experiences suggest clinical potential, warranting further trials. CLINICAL TRIAL REGISTRATION: NCT05347849.

Take a break: should breaks be enforced during digital breast tomosynthesis reading sessions?

OBJECTIVES: Digital breast tomosynthesis (DBT) can improve diagnostic accuracy compared to 2D mammography, but DBT reporting is time-consuming and potentially more fatiguing. Changes in diagnostic accuracy and subjective and objective fatigue were evaluated over a DBT reporting session, and the impact of taking a reporting break was assessed. MATERIALS AND METHODS: Forty-five National Health Service (NHS) mammography readers from 6 hospitals read a cancer-enriched set of 40 DBT cases whilst eye tracked in this prospective cohort study, from December 2020 to April 2022. Eye-blink metrics were assessed as objective fatigue measures. Twenty-one readers had a reporting break, 24 did not. Subjective fatigue questionnaires were completed before and after the session. Diagnostic accuracy and subjective and objective fatigue measures were compared between the cohorts using parametric and non-parametric significance testing. RESULTS: Readers had on average 10 years post-training breast screening experience and took just under 2 h (105.8 min) to report all cases. Readers without a break reported greater levels of subjective fatigue (44% vs. 33%, p = 0.04), which related to greater objective fatigue: an increased average blink duration (296 ms vs. 286 ms, p < 0.001) and a reduced eye-opening velocity (76 mm/s vs. 82 mm/s, p < 0.001). Objective fatigue increased as the trial progressed for the no break cohort only (ps < 0.001). No difference was identified in diagnostic accuracy between the groups (accuracy: 87% vs. 87%, p = 0.92). CONCLUSIONS: Implementing a break during a 2-h DBT reporting session resulted in lower levels of subjective and objective fatigue. Breaks did not impact diagnostic accuracy, which may be related to the extensive experience of the readers. CLINICAL RELEVANCE STATEMENT: DBT is being incorporated into many mammography screening programmes. Recognising that reporting breaks are required when reading large volumes of DBT studies ensures this can be factored in when setting up reading sessions. TRIAL REGISTRATION: Clinical trials registration number: NCT03733106 KEY POINTS: • Use of digital breast tomosynthesis (DBT) in breast screening programmes can cause significant reader fatigue. • The effectiveness of incorporating reading breaks into DBT reporting sessions, to reduce mammography reader fatigue, was investigated using eye tracking. • Integrating breaks into DBT reporting sessions reduced reader fatigue; however, diagnostic accuracy was unaffected.

Automatic correction of performance drift under acquisition shift in medical image classification.

Image-based prediction models for disease detection are sensitive to changes in data acquisition such as the replacement of scanner hardware or updates to the image processing software. The resulting differences in image characteristics may lead to drifts in clinically relevant performance metrics which could cause harm in clinical decision making, even for models that generalise in terms of area under the receiver-operating characteristic curve. We propose Unsupervised Prediction Alignment, a generic automatic recalibration method that requires no ground truth annotations and only limited amounts of unlabelled example images from the shifted data distribution. We illustrate the effectiveness of the proposed method to detect and correct performance drift in mammography-based breast cancer screening and on publicly available histopathology data. We show that the proposed method can preserve the expected performance in terms of sensitivity/specificity under various realistic scenarios of image acquisition shift, thus offering an important safeguard for clinical deployment.

Performance of a Breast Cancer Detection AI Algorithm Using the Personal Performance in Mammographic Screening Scheme.

Background The Personal Performance in Mammographic Screening (PERFORMS) scheme is used to assess reader performance. Whether this scheme can assess the performance of artificial intelligence (AI) algorithms is unknown. Purpose To compare the performance of human readers and a commercially available AI algorithm interpreting PERFORMS test sets. Materials and Methods In this retrospective study, two PERFORMS test sets, each consisting of 60 challenging cases, were evaluated by human readers between May 2018 and March 2021 and were evaluated by an AI algorithm in 2022. AI considered each breast separately, assigning a suspicion of malignancy score to features detected. Performance was assessed using the highest score per breast. Performance metrics, including sensitivity, specificity, and area under the receiver operating characteristic curve (AUC), were calculated for AI and humans. The study was powered to detect a medium-sized effect (odds ratio, 3.5 or 0.29) for sensitivity. Results A total of 552 human readers interpreted both PERFORMS test sets, consisting of 161 normal breasts, 70 malignant breasts, and nine benign breasts. No difference was observed at the breast level between the AUC for AI and the AUC for human readers (0.93% and 0.88%, respectively; P = .15). When using the developer's suggested recall score threshold, no difference was observed for AI versus human reader sensitivity (84% and 90%, respectively; P = .34), but the specificity of AI was higher (89%) than that of the human readers (76%, P = .003). However, it was not possible to demonstrate equivalence due to the size of the test sets. When using recall thresholds to match mean human reader performance (90% sensitivity, 76% specificity), AI showed no differences inperformance, with a sensitivity of 91% (P =. 73) and a specificity of 77% (P = .85). Conclusion Diagnostic performance of AI was comparable with that of the average human reader when evaluating cases from two enriched test sets from the PERFORMS scheme. © RSNA, 2023 See also the editorial by Philpotts in this issue.

Why do we evaluate 30-day readmissions in general medicine? A historical perspective and contemporary data.

Reducing preventable readmissions is important to help manage current strains on healthcare systems. The metric of 30-day readmissions is commonly cited in discussions regarding this topic. While such thresholds have contemporary funding implications, the rationale for individual cut-off points is partially historical in nature. Through the examination of the basis for the analysis of 30-day readmissions, greater insight into the possible benefits and limitations of such a metric may be obtained.

Comparing Prognostic Factors of Cancers Identified by Artificial Intelligence (AI) and Human Readers in Breast Cancer Screening.

Invasiveness status, histological grade, lymph node stage, and tumour size are important prognostic factors for breast cancer survival. This evaluation aims to compare these features for cancers detected by AI and human readers using digital mammography. Women diagnosed with breast cancer between 2009 and 2019 from three UK double-reading sites were included in this retrospective cohort evaluation. Differences in prognostic features of cancers detected by AI and the first human reader (R1) were assessed using chi-square tests, with significance at p < 0.05. From 1718 screen-detected cancers (SDCs) and 293 interval cancers (ICs), AI flagged 85.9% and 31.7%, respectively. R1 detected 90.8% of SDCs and 7.2% of ICs. Of the screen-detected cancers detected by the AI, 82.5% had an invasive component, compared to 81.1% for R1 (p-0.374). For the ICs, this was 91.5% and 93.8% for AI and R1, respectively (p = 0.829). For the invasive tumours, no differences were found for histological grade, tumour size, or lymph node stage. The AI detected more ICs. In summary, no differences in prognostic factors were found comparing SDC and ICs identified by AI or human readers. These findings support a potential role for AI in the double-reading workflow.

Preoperative diagnosis of ductal carcinoma in situ of the breast over a 24-year period.

AIMS: The method of diagnosis of ductal carcinoma in situ (DCIS) has changed since the 1980s. The aim of this audit was to assess changes in the preoperative diagnosis of DCIS since the introduction of needle core biopsy, particularly the proportion with a preoperative biopsy diagnosis of DCIS. METHODS AND RESULTS: The preoperative diagnoses of patients with a final diagnosis of DCIS in the surgical specimen were reviewed (i) in 809 patients who presented through breast screening from 1997 to 2021, and (ii) in all patients in 5 individual years at 5-year intervals from 2000 to 2020 (254 in total). For screening-detected DCIS the proportion with a preoperative diagnosis of DCIS increased from 75% to 98% over the study period. In a detailed analysis of all cases of DCIS in 5 separate years the proportion with a preoperative diagnosis of DCIS increased from 68% in 2000 to 96% in 2020. For high-grade DCIS the proportion increased from 87% to 97%, and for low- or intermediate-grade DCIS from 48% to 93%. The proportion of women who had vacuum-assisted biopsy increased from 7% in 2000 to 58% in 2015. There was a small increase in the number of biopsies that had basal cytokeratin and oestrogen receptor immunohistochemistry to aid diagnosis. CONCLUSION: There has been an increase in the preoperative diagnosis of DCIS, particularly of low- or intermediate-grade, over the last two decades. The increasing use of vacuum-assisted biopsy is likely to be a major contributory factor to this increase.

Multi-vendor evaluation of artificial intelligence as an independent reader for double reading in breast cancer screening on 275,900 mammograms.

BACKGROUND: Double reading (DR) in screening mammography increases cancer detection and lowers recall rates, but has sustainability challenges due to workforce shortages. Artificial intelligence (AI) as an independent reader (IR) in DR may provide a cost-effective solution with the potential to improve screening performance. Evidence for AI to generalise across different patient populations, screening programmes and equipment vendors, however, is still lacking. METHODS: This retrospective study simulated DR with AI as an IR, using data representative of real-world deployments (275,900 cases, 177,882 participants) from four mammography equipment vendors, seven screening sites, and two countries. Non-inferiority and superiority were assessed for relevant screening metrics. RESULTS: DR with AI, compared with human DR, showed at least non-inferior recall rate, cancer detection rate, sensitivity, specificity and positive predictive value (PPV) for each mammography vendor and site, and superior recall rate, specificity, and PPV for some. The simulation indicates that using AI would have increased arbitration rate (3.3% to 12.3%), but could have reduced human workload by 30.0% to 44.8%. CONCLUSIONS: AI has potential as an IR in the DR workflow across different screening programmes, mammography equipment and geographies, substantially reducing human reader workload while maintaining or improving standard of care. TRIAL REGISTRATION: ISRCTN18056078 (20/03/2019; retrospectively registered).

Measuring reader fatigue in the interpretation of screening digital breast tomosynthesis (DBT).

OBJECTIVES: The interpretation of digital breast tomosynthesis (DBT) screening examinations is a complex task for an already overstretched workforce which has the potential to increase pressure on readers leading to fatigue and patient safety issues. Studies in non-medical and medical settings have suggested that changes in blink characteristics can reflect fatigue. The purpose of this study is to investigate the use of blink characteristics as an objective marker of fatigue in readers interpreting DBT breast screening examinations. METHODS: Twenty-six DBT readers involved in the UK PROSPECTS trial interpreted a test set of 40 DBT cases while being observed by an eye tracking device from November 2019 to February 2021. Raw data from the eye tracker were collected and automated processing software was used to produce eye blinking characteristics data which were analysed using multiple linear regression statistical models. RESULTS: Of the 26 DBT readers recruited, eye tracking data from 23 participants were analysed due to missing data rendering 3 participants' data uninterpretable. The mean reading time per DBT case was 2.81 min. There was a statistically significant increase in blinking duration of 0.38 ms/case as the reading session progressed (p < 0.0001). This was the result of a significant decrease in the number of ultra-short blinks lasting ≤50 ms (p = 0.0005) and a significant increase in longer blinks lasting 51-100 ms (p = 0.008). CONCLUSION: Changes in blinking characteristics could serve as objective measures of reader fatigue and may prove useful in the development of DBT reading protocols. ADVANCES IN KNOWLEDGE: Blink characteristics can be used as an objective measure of fatigue; however there is limited evidence of their use in radiological settings. Our study suggests that changes in blink duration and frequency could be used to monitor fatigue in DBT reading sessions.

Performance of Radiologists and Radiographers in Double Reading Mammograms: The UK National Health Service Breast Screening Program.

Background Double reading can be used in screening mammography, but it is labor intensive. There is limited evidence on whether trained radiographers (ie, technologists) may be used to provide double reading. Purpose To compare the performance of radiologists and radiographers double reading screening mammograms, considering reader experience level. Materials and Methods In this retrospective study, performance and experience data were obtained for radiologists and radiographer readers of all screening mammograms in England from April 2015 to March 2016. Cancer detection rate (CDR), recall rate (RR), and positive predictive value (PPV) of recall based on biopsy-proven findings were calculated for first readers. Performance metrics were analyzed according to reader professional group and years of reading experience using the analysis of variance test. P values less than .05 were considered to indicate statistically significant difference. Results During the study period, 401 readers (224 radiologists and 177 radiographers) double read 1 404 395 screening digital mammograms. There was no difference in CDR between radiologist and radiographer readers (mean, 7.84 vs 7.53 per 1000 examinations, respectively; P = .08) and no difference for readers with more than 10 years of experience compared with 5 years or fewer years of experience, regardless of professional group (mean, 7.75 vs 7.71 per 1000 examinations respectively, P = .87). No difference in the mean RR was observed between radiologists and radiographer readers (5.0% vs 5.2%, respectively, P = .63). A lower RR was seen for readers with more than 10 years of experience compared with 5 years or fewer, regardless of professional group (mean, 4.8% vs 5.8%, respectively; P = .001). No variation in PPV was observed between them (P = .42), with PPV values of 17.1% for radiologists versus 16.1% for radiographers. A higher PPV was seen for readers with more than 10 years of experience compared with 5 years or less, regardless of professional group (mean, 17.5% and 14.9%, respectively; P = .02). Conclusion No difference in performance was observed between radiographers and radiologists reading screening mammograms in a program that used double reading. Published under a CC BY 4.0 license Online supplemental material is available for this article. See also the editorial by Hooley and Durand in this issue.

Artificial Intelligence as Supporting Reader in Breast Screening: A Novel Workflow to Preserve Quality and Reduce Workload.

OBJECTIVE: To evaluate the effectiveness of a new strategy for using artificial intelligence (AI) as supporting reader for the detection of breast cancer in mammography-based double reading screening practice. METHODS: Large-scale multi-site, multi-vendor data were used to retrospectively evaluate a new paradigm of AI-supported reading. Here, the AI served as the second reader only if it agrees with the recall/no-recall decision of the first human reader. Otherwise, a second human reader made an assessment followed by the standard clinical workflow. The data included 280 594 cases from 180 542 female participants screened for breast cancer at seven screening sites in two countries and using equipment from four hardware vendors. The statistical analysis included non-inferiority and superiority testing of cancer screening performance and evaluation of the reduction in workload, measured as arbitration rate and number of cases requiring second human reading. RESULTS: Artificial intelligence as a supporting reader was found to be superior or noninferior on all screening metrics compared with human double reading while reducing the number of cases requiring second human reading by up to 87% (245 395/280 594). Compared with AI as an independent reader, the number of cases referred to arbitration was reduced from 13% (35 199/280 594) to 2% (5056/280 594). CONCLUSION: The simulation indicates that the proposed workflow retains screening performance of human double reading while substantially reducing the workload. Further research should study the impact on the second human reader because they would only assess cases in which the AI prediction and first human reader disagree.

Put your FTSE down: Wealth shocks and road traffic collisions.

This paper examines the impact of a key source of wealth (the stock market) on road traffic collisions. Using data on over 2 million road accidents we do not find a linear relationship between stock prices and road crashes (fatal or otherwise) in Great Britain. However, we do find a V-shaped effect - collisions respond to the absolute change in stock market returns. The results are robust to a series of falsification exercises that potentially support a causal interpretation. We also examine another source of wealth that has not previously been examined - house prices. Similarly, we do not find that changes in monthly house prices have an impact on accidents, but a symmetric V-shaped is also shown for slight and serious accidents.

Night skies through animals' eyes-Quantifying night-time visual scenes and light pollution as viewed by animals.

A large proportion of animal species enjoy the benefits of being active at night, and have evolved the corresponding optical and neural adaptations to cope with the challenges of low light intensities. However, over the past century electric lighting has introduced direct and indirect light pollution into the full range of terrestrial habitats, changing nocturnal animals' visual worlds dramatically. To understand how these changes affect nocturnal behavior, we here propose an animal-centered analysis method based on environmental imaging. This approach incorporates the sensitivity and acuity limits of individual species, arriving at predictions of photon catch relative to noise thresholds, contrast distributions, and the orientation cues nocturnal species can extract from visual scenes. This analysis relies on just a limited number of visual system parameters known for each species. By accounting for light-adaptation in our analysis, we are able to make more realistic predictions of the information animals can extract from nocturnal visual scenes under different levels of light pollution. With this analysis method, we aim to provide context for the interpretation of behavioral findings, and to allow researchers to generate specific hypotheses for the behavior of nocturnal animals in observed light-polluted scenes.

Promoting simulation-based training in radiology: a homemade phantom for the practice of ultrasound-guided procedures.

OBJECTIVE: Ultrasound-guided intervention is an essential skill for many radiologists and critical for accurate diagnosis and treatment in many radiology subspecialties. Simulation using phantoms have demonstrated statistically significant benefits for trainees within the literature. We propose a novel phantom model which the authors feel is ideal for training clinical radiology trainees in the performance of ultrasound-guided procedures. METHODS: The recipe to prepare a homemade phantom is described. Results of a local survey from trainees preparing and using the phantom are also presented. RESULTS: This realistic training simulation model can be adapted to suit a variety of biopsy devices and procedures including soft tissue biopsy and cyst aspiration. The phantom mimics the sonographic appearances of soft tissue and biopsy targets can be concealed within. The phantom was easily prepared by 22 trainees (Likert score 4.5) and it functioned well (Likert score of 4.7). CONCLUSION: In summary, our phantom model is ideal for training clinical radiology trainees in the performance of ultrasound-guided core biopsy. The availability and low cost of the model, combined with the ease of preparation and reproducibility, make this an efficient and effective addition to the training process. ADVANCES IN KNOWLEDGE: A low cost easily handmade phantom recipe is described that could be easily implemented in training schemes.

Real-time monitoring of epithelial barrier function by impedance spectroscopy in a microfluidic platform.

A multichannel microfluidic platform for real-time monitoring of epithelial barrier integrity by electrical impedance has been developed. Growth and polarization of human epithelial cells from the airway or gastrointestinal tract was continuously monitored over 5 days in 8 parallel, individually perfused microfluidic chips. Electrical impedance data were continuously recorded to monitor cell barrier formation using a low-cost bespoke impedance analyser. Data was analysed using an electric circuit model to extract the equivalent transepithelial electrical resistance and epithelial cell layer capacitance. The cell barrier integrity steadily increased overtime, achieving an average resistance of 418 ± 121 Ω cm2 (airway cells) or 207 ± 59 Ω cm2 (gastrointestinal cells) by day 5. The utility of the polarized airway epithelial barrier was demonstrated using a 24 hour challenge with double stranded RNA to mimic viral infection. This caused a rapid decrease in barrier integrity in association with disruption of tight junctions, whereas simultaneous treatment with a corticosteroid reduced this effect. The platform is able to measure barrier integrity in real-time and is scalable, thus has the potential to be used for drug development and testing.

Contrast-enhanced spectral mammography (CESM)-guided breast biopsy as an alternative to MRI-guided biopsy.

OBJECTIVE: Contrast-enhanced spectral mammography (CESM) breast biopsy has been recently introduced into clinical practice. This short communication describes the technique and potential as an alternative to MRI-guided biopsy. METHODS AND MATERIALS: An additional abnormality was detected on a breast MRI examination in a patient with lobular carcinoma. The lesion was occult on conventional mammography, tomosynthesis and ultrasound and required histological diagnosis. Traditionally, this would have necessitated an MRI-guided breast biopsy, but was performed under CESM guidance. RESULTS: A diagnostic CESM study was performed to ensure the lesion visibility with CESM and then targeted under CESM guidance. A limited diagnostic study, CESM scout and paired images for stereotactic targeting were obtained within a 10 min window following a single injection of iodinated contrast agent. The time from positioning in the biopsy device to releasing compression after biopsy and marker clip placement was 15 min. The biopsy confirmed the presence of multifocal breast cancer. CONCLUSION: CESM-guided breast biopsy is a new technique that can be successfully used as an alternative to MRI-guided breast biopsy. ADVANCES IN KNOWLEDGE: CESM-guided biopsy can be used to sample breast lesions which remain occult on standard mammography and ultrasound.

Differential Potency of Venlafaxine, Paroxetine, and Atomoxetine to Inhibit Serotonin and Norepinephrine Reuptake in Patients With Major Depressive Disorder.

BACKGROUND: Venlafaxine is a dual serotonin (5-HT) and norepinephrine reuptake inhibitor. The specific dose at which it begins to efficiently engage the norepinephrine transporter (NET) remained to be determined. Paroxetine is generally considered as a selective 5-HT reuptake inhibitor but exhibits some affinity for NET. Atomoxetine is a NET inhibitor but also has some affinity for the 5-HT reuptake transporter (SERT). METHODS: This study examined the effects of forced titration of venlafaxine from 75 to 300 mg/d, paroxetine from 20 to 50 mg/d, or atomoxetine from 25 to 80 mg/d in 32 patients with major depressive disorder. Inhibition of SERT was estimated using the depletion of whole-blood 5-HT. Inhibition of NET was assessed using the attenuation of the systolic blood pressure produced by i.v. injections of tyramine. RESULTS: All 3 medications significantly reduced 5-HT levels at the initiating regimens: venlafaxine and paroxetine by approximately 60% and atomoxetine by 16%. The 3 subsequent regimens of venlafaxine and paroxetine reduced 5-HT levels by over 90%, but the highest dose of atomoxetine only reached a 40% inhibition. Atomoxetine dose dependently inhibited the tyramine pressor response from the lowest dose, venlafaxine from 225 mg/d, and paroxetine left it unaltered throughout. CONCLUSION: These results confirm that venlafaxine and paroxetine are potent SERT inhibitors over their usual therapeutic range but that venlafaxine starts inhibiting NET only at 225 mg/d, whereas paroxetine remains selective for SERT up to 50 mg/d. Atomoxetine dose dependently inhibits NET from a low dose but does not inhibit SERT to a clinically relevant degree.

Maternal stress during pregnancy and children's diet: Evidence from a population of low socioeconomic status.

OBJECTIVES: This study examined the relationship between maternal exposure to stress during pregnancy and children's food preferences and diet in a population of low socioeconomic status. METHODS: Indices of exposure to stress were constructed based on retrospective self-reported experience of stressful events during pregnancy (e.g., death of close family member, relationship difficulties, legal issues, health issues, financial issues, or other potentially stressful event[s]). Data were collected for >200 mothers of a low socioeconomic status with a child age 2 to 12 y. Data on mothers' body mass index, current exposure to stress, current diet, and diet during pregnancy were collected at the same time, as well as data on children's food preferences and current diet as reported by the mothers. Indices of the healthiness of food preferences and diet were constructed and used as outcome variables. RESULTS: Maternal exposure to stress during pregnancy significantly predicts children's food and taste preferences, as well as their diet, in regression models controlling for maternal diet, current maternal stress, and demographic characteristics of both the child and mother. Higher average stress during pregnancy is linked with significantly less healthy food preferences and diet, as well as with weaker preferences for sour and bitter foods. This relationship is observed across different age groups. CONCLUSIONS: Maternal exposure to stress during pregnancy could have long-term detrimental effects on dietary outcomes and thereby on health conditions related to diet. Prenatal care and preconception counseling could be critical to develop preventive strategies to improve public health.