Comprehensive Imaging Characterization of Colorectal Liver Metastases

Colorectal liver metastases (CRLM) have heterogenous histopathological and immunohistochemical phenotypes, which are associated with variable responses to treatment and outcomes. However, this information is usually only available after resection, and therefore of limited value in treatment planning. Improved techniques for in vivo disease assessment, which can characterise the variable tumour biology, would support further personalization of management strategies. Advanced imaging of CRLM including multiparametric MRI and functional imaging techniques have the potential to provide clinically-actionable phenotypic characterisation. This includes assessment of the tumour-liver interface, internal tumour components and treatment response. Advanced analysis techniques, including radiomics and machine learning now have a growing role in assessment of imaging, providing high-dimensional imaging feature extraction which can be linked to clinical relevant tumour phenotypes, such as a the Consensus Molecular Subtypes (CMS). In this review, we outline how imaging techniques could reproducibly characterize the histopathological features of CRLM, with several matched imaging and histology examples to illustrate these features, and discuss the oncological relevance of these features. Finally, we discuss the future challenges and opportunities of CRLM imaging, with a focus on the potential value of advanced analytics including radiomics and artificial intelligence, to help inform future research in this rapidly moving field

Bayesian penalised likelihood reconstruction (Q.Clear) of 18F-fluciclovine PET for imaging of recurrent prostate cancer: semi-quantitative and clinical evaluation

Objective: 18F-Fluciclovine (FACBC) is an amino acid PET radiotracer approved for recurrent prostate cancer imaging. We investigate the use of Bayesian penalised likelihood (BPL) reconstruction for 18F-fluciclovine PET. Methods: 15 18F-fluciclovine scans were reconstructed using ordered subset expectation maximisation (OSEM), OSEM + point spread function (PSF) modelling and BPL using β-values 100–600. Lesion maximum standardised uptake value (SUVmax), organ SUVmean and standard deviation were measured. Deidentified reconstructions (OSEM, PSF, BPL using β200–600) from 10 cases were visually analysed by two readers who indicated their most and least preferred reconstructions, and scored overall image quality, noise level, background marrow image quality and lesion conspicuity. Results: Comparing BPL to OSEM, there were significant increments in lesion SUVmax and signal-to-background up to β400, with highest gain in β100 reconstructions (mean ΔSUVmax 3.9, p < 0.0001). Organ noise levels increased on PSF, β100 and β200 reconstructions. Across BPL reconstructions, there was incremental reduction in organ noise with increasing β, statistically significant beyond β300–500 (organ-dependent). Comparing with OSEM and PSF, lesion signal-to-noise was significantly increased in BPL reconstructions where β ≥ 300 and ≥ 200 respectively. On visual analysis, β 300 had the first and second highest scores for image quality, β500 and β600 equal highest scores for marrow image quality and least noise, PSF and β 200 had first and second highest scores for lesion conspicuity. For overall preference, one reader preferred β 300 in 9/10 cases and the other preferred β 200 in all cases. Conclusion: BPL reconstruction of 18F-fluciclovine PET images improves signal-to-noise ratio, affirmed by overall reader preferences. On balance, β300 is suggested for 18F-fluciclovine whole body PET image reconstruction using BPL. Advances in knowledge: The optimum β is different to that previously published for 18F-fluorodeoxyglucose, and has practical implications for a relatively new tracer in an environment with modern reconstruction technologies

COVID-19 pneumonia and the masquerades

During the COVID-19 pandemic, chest CT is frequently used to help with the diagnosis. The classic CT patterns of COVID-19 pneumonia are well-published and recognised among radiologists. However, when there are pre-existing conditions particularly in the elderly population that could mask or result in similar patterns of disease, then the diagnosis is more difficult. This imaging essay highlights the commonly encountered situations including patients with heart failure, other possible infections particularly in the immunodeficient, and when there is trauma to the thorax. We illustrate imaging clues available to the radiologist to either make the diagnosis or at least reduce the differential diagnosi

Lung cancer prediction by Deep Learning to identify benign lung nodules

INTRODUCTION: Deep Learning has been proposed as promising tool to classify malignant nodules. Our aim was to retrospectively validate our Lung Cancer Prediction Convolutional Neural Network (LCP-CNN), which was trained on US screening data, on an independent dataset of indeterminate nodules in an European multicentre trial, to rule out benign nodules maintaining a high lung cancer sensitivity. METHODS: The LCP-CNN has been trained to generate a malignancy score for each nodule using CT data from the U.S. National Lung Screening Trial (NLST), and validated on CT scans containing 2106 nodules (205 lung cancers) detected in patients from from the Early Lung Cancer Diagnosis Using Artificial Intelligence and Big Data (LUCINDA) study, recruited from three tertiary referral centers in the UK, Germany and Netherlands. We pre-defined a benign nodule rule-out test, to identify benign nodules whilst maintaining a high sensitivity, by calculating thresholds on the malignancy score that achieve at least 99 % sensitivity on the NLST data. Overall performance per validation site was evaluated using Area-Under-the-ROC-Curve analysis (AUC). RESULTS: The overall AUC across the European centers was 94.5 % (95 %CI 92.6-96.1). With a high sensitivity of 99.0 %, malignancy could be ruled out in 22.1 % of the nodules, enabling 18.5 % of the patients to avoid follow-up scans. The two false-negative results both represented small typical carcinoids. CONCLUSION: The LCP-CNN, trained on participants with lung nodules from the US NLST dataset, showed excellent performance on identification of benign lung nodules in a multi-center external dataset, ruling out malignancy with high accuracy in about one fifth of the patients with 5-15 mm nodules

Effect of 18F-fluciclovine positron emission tomography on the management of patients with recurrence of prostate cancer: Results from the FALCON Trial

Purpose: Early and accurate localization of lesions in patients with biochemical recurrence (BCR) of prostate cancer may guide salvage therapy decisions. The present study, 18F-Fluciclovine PET/CT in biochemicAL reCurrence Of Prostate caNcer (FALCON; NCT02578940), aimed to evaluate the effect of 18F-fluciclovine on management of men with BCR of prostate cancer. Methods and Materials: Men with a first episode of BCR after curative-intent primary therapy were enrolled at 6 UK sites. Patients underwent 18F-fluciclovine positron emission tomography/computed tomography (PET/CT) according to standardized procedures. Clinicians documented management plans before and after scanning, recording changes to treatment modality as major and changes within a modality as other. The primary outcome measure was record of a revised management plan postscan. Secondary endpoints were evaluation of optimal prostate specific antigen (PSA) threshold for detection, salvage treatment outcome assessment based on 18F-fluciclovine-involvement, and safety. Results: 18F-Fluciclovine was well tolerated in the 104 scanned patients (median PSA = 0.79 ng/mL). Lesions were detected in 58 out of 104 (56%) patients. Detection was broadly proportional to PSA level; ≤1 ng/mL, 1 out of 3 of scans were positive, and 93% scans were positive at PSA &gt;2.0 ng/mL. Sixty-six (64%) patients had a postscan management change (80% after a positive result). Major changes (43 out of 66; 65%) were salvage or systemic therapy to watchful waiting (16 out of 66; 24%); salvage therapy to systemic therapy (16 out of 66; 24%); and alternative changes to treatment modality (11 out of 66, 17%). The remaining 23 out of 66 (35%) management changes were modifications of the prescan plan: most (22 out of 66; 33%) were adjustments to planned brachytherapy/radiation therapy to include a 18F-fluciclovine-guided boost. Where 18F-fluciclovine guided salvage therapy, the PSA response rate was higher than when 18F-fluciclovine was not involved (15 out of 17 [88%] vs 28 out of 39 [72%]). Conclusions: 18F-Fluciclovine PET/CT located recurrence in the majority of men with BCR, frequently resulting in major management plan changes. Incorporating 18F-fluciclovine PET/CT into treatment planning may optimize targeting of recurrence sites and avoid futile salvage therapy

Association of Serum Ustekinumab Levels With Clinical Response in Psoriasis

Importance: High-cost biologic therapies have transformed the management of immune-mediated inflammatory diseases. To optimize outcomes and reduce costs, dose adjustment informed by measurement of circulating drug levels has been shown to be effective in various settings. However, limited evidence exists for this approach with the interleukin 12 and interleukin 23 inhibitor ustekinumab. Objective: To evaluate clinical utility of therapeutic drug monitoring for ustekinumab in patients with psoriasis. Design, Setting, and Participants: A prospective observational cohort of 491 adults with psoriasis was recruited to the multicenter Biomarkers of Systemic Treatment Outcomes in Psoriasis study within the British Association of Dermatologists Biologic and Immunomodulators Register from June 2009 to December 2017; samples from some patients were taken between 2009 and 2011 as part of a pilot study with the same inclusion criteria. Exposure: Serum ustekinumab level measured at any point during the dosing cycle using an enzyme-linked immunosorbent assay. Main Outcomes and Measures@ Disease activity measured using the Psoriasis Area and Severity Index (PASI) score. Treatment response outcomes were PASI75 (75% reduction in PASI score from baseline [primary outcome]), PASI90 (90% reduction of PASI score from baseline), and absolute PASI score of 1.5 or less. Results: A total of 491 patients (171 women and 320 men; mean [SD] age, 45.7 [12.8] years) had 1 or more serum samples (total, 853 samples obtained 0-56 weeks from start of treatment) and 1 or more PASI scores within the first year of treatment. Antidrug antibodies were detected in only 17 of 490 patients (3.5%). Early measured drug levels (1-12 weeks after starting treatment) were associated with PASI75 response 6 months after starting treatment (odds ratio, 1.38; 95% CI, 1.11-1.71) when adjusted for baseline PASI score, age, and ustekinumab dose. However, this finding was not consistent across the other PASI outcomes (PASI90 and PASI score of ≤1.5). Conclusions and Relevance: This real-world study provides evidence that measurement of early serum ustekinumab levels could be useful to direct the treatment strategy for psoriasis. Adequate drug exposure early in the treatment cycle may be particularly important in determining clinical outcome

Propranolol in the treatment of infantile haemangiomas:lessons from the European Propranolol In the Treatment of Complicated Haemangiomas (PITCH) Taskforce survey

Oral propranolol is widely prescribed as first line treatment for infantile haemangiomas (IHs) and anecdotally prescribing practice differs widely between centres

Defining the therapeutic range for adalimumab and predicting response in psoriasis: a multicenter prospective observational cohort study

Biologics have transformed management of inflammatory diseases. To optimize outcomes and reduce costs, dose adjustment informed by circulating drug levels has been proposed. We aimed to determine the real-world clinical utility of therapeutic drug monitoring in psoriasis. Within a multicenter (n=60) prospective observational cohort, 544 psoriasis patients were included who were on adalimumab monotherapy, with at least one serum sample and PASI (Psoriasis Area and Severity Index) score available within the first year. We present models giving individualized probabilities of response for any given drug level: a minimally effective drug level of 3.2 μg/ml discriminates responders (PASI75: 75% improvement in baseline PASI) from non-responders and gives an estimated PASI75 probability of 65% (95% CI 60-71%). At 7ug/ml, PASI75 probability is 81% (95% CI 76-86%); beyond 7ug/ml, the drug level/response curve plateaus. Crucially, drug levels are predictive of response 6 months later, whether sampled early or at steady state. We confirm serum drug level to be the most important factor determining treatment response, highlighting the need to take drug levels into account when searching for biomarkers of response. This real-world study with pragmatic drug level sampling provides evidence to support the proactive measurement of adalimumab levels in psoriasis to direct treatment strategy, and is relevant to other inflammatory diseases