Lung cancer patient who had declined conventional cancer treatment: could the self-administration of 'CBD oil' be contributing to the observed tumour regression?

Conventional lung cancer treatments include surgery, chemotherapy and radiotherapy; however, these treatments are often poorly tolerated by patients. Cannabinoids have been studied for use as a primary cancer treatment. Cannabinoids, which are chemically similar to our own body's endocannabinoids, can interact with signalling pathways to control the fate of cells, including cancer cells. We present a patient who declined conventional lung cancer treatment. Without the knowledge of her clinicians, she chose to self-administer 'cannabidiol (CBD) oil' orally 2-3 times daily. Serial imaging shows that her cancer reduced in size progressively from 41 mm to 10 mm over a period of 2.5 years. Previous studies have failed to agree on the usefulness of cannabinoids as a cancer treatment. This case appears to demonstrate a possible benefit of 'CBD oil' intake that may have resulted in the observed tumour regression. The use of cannabinoids as a potential cancer treatment justifies further research.

COVID-19: mobilising CT as a frontline management tool.

As the COVID-19 pandemic has spread across the globe, questions have arisen about the approach healthcare systems should adopt in order to optimally manage patient influx. With a focus on the impact of COVID-19 on the NHS, we describe the frontline experience of a severely affected hospital in close proximity to London. We highlight a protocol-driven approach, incorporating the use of CT in the rapid triage, assessment and cohorting of patients, in an environment where there was a lack of readily available, onsite RT-PCR testing facilities. Furthermore, the effects of the protocol on the effective streamlining of patient flow within the hospital are discussed, as are the resultant improvements in clinical management decisions within the acute care service. This model may help other healthcare systems in managing this pandemic whilst assessing their own needs and resources.

Detection and quantification of coronary atherosclerotic plaque by 64-slice multidetector CT: a systematic head-to-head comparison with intravascular ultrasound.

OBJECTIVE: We evaluated the ability of 64-slice multidetector computed tomography (MDCT)-derived plaque parameters to detect and quantify coronary atherosclerosis, using intravascular ultrasound (IVUS) as the reference standard. METHODS: In 32 patients, IVUS and 64-MDCT was performed. The MDCT and IVUS datasets of 44 coronary arteries were co-registered using a newly developed fusion technique and quantitative parameters were derived from both imaging modalities. The threshold of >0.5 mm of maximum wall thickness was used to establish plaque presence on MDCT and IVUS. RESULTS: We analyzed 1364 coregistered 1-mm coronary cross-sections and 255 segments of 5-mm length. Compared with IVUS, 64-MDCT enabled correct detection in 957 of 1109 cross-sections containing plaque (sensitivity 86%). In 180 of 255 cross-sections atherosclerosis was correctly excluded (specificity 71%). On the segmental level, MDCT detected 213 of 220 segments with any atherosclerotic plaque (sensitivity 96%), whereas the presence of any plaque was correctly ruled out in 28 of 32 segments (specificity 88%). Interobserver agreement for the detection of atherosclerotic cross-sections was moderate (Cohen's kappa coefficient K=0.51), but excellent for the atherosclerotic segments (K=1.0). Pearson's correlation coefficient for vessel plaque volumes measured by MDCT and IVUS was r=0.91 (p<0.001). Bland-Altman analysis showed a slight non-significant underestimation of any plaque volume by MDCT (p=0.5), with a trend to underestimate noncalcified and overestimate mixed/calcified plaque volumes (p=0.22 and p=0.87 respectively). CONCLUSION: MDCT is able to detect and quantify atherosclerotic plaque. Further improvement in CT resolution is necessary for more reliable assessment of very small and distal coronary plaques.

Robust shape regression for supervised vessel segmentation and its application to coronary segmentation in CTA.

This paper presents a vessel segmentation method which learns the geometry and appearance of vessels in medical images from annotated data and uses this knowledge to segment vessels in unseen images. Vessels are segmented in a coarse-to-fine fashion. First, the vessel boundaries are estimated with multivariate linear regression using image intensities sampled in a region of interest around an initialization curve. Subsequently, the position of the vessel boundary is refined with a robust nonlinear regression technique using intensity profiles sampled across the boundary of the rough segmentation and using information about plausible cross-sectional vessel shapes. The method was evaluated by quantitatively comparing segmentation results to manual annotations of 229 coronary arteries. On average the difference between the automatically obtained segmentations and manual contours was smaller than the inter-observer variability, which is an indicator that the method outperforms manual annotation. The method was also evaluated by using it for centerline refinement on 24 publicly available datasets of the Rotterdam Coronary Artery Evaluation Framework. Centerlines are extracted with an existing method and refined with the proposed method. This combination is currently ranked second out of 10 evaluated interactive centerline extraction methods. An additional qualitative expert evaluation in which 250 automatic segmentations were compared to manual segmentations showed that the automatically obtained contours were rated on average better than manual contours.

Impact of heart rate frequency and variability on radiation exposure, image quality, and diagnostic performance in dual-source spiral CT coronary angiography.

PURPOSE: To investigate the effect of heart rate frequency (HRF) and heart rate variability (HRV) on radiation exposure, image quality, and diagnostic performance to help detect significant stenosis (> or =50% lumen diameter reduction) by using adaptive electrocardiographic (ECG) pulsing at dual-source (DS) spiral computed tomographic (CT) coronary angiography. MATERIALS AND METHODS: Institutional review committee approval and informed consent were obtained. No prescan beta-blockers were applied. Unenhanced CT and CT coronary angiography with adaptive ECG pulsing were performed in 927 consecutive patients (600 men, 327 women; mean age, 60.3 years +/- 11.0 [standard deviation]) divided in three HRF groups: low, intermediate, and high (< or =65, 66-79, and > or =80 beats/min, respectively), and four HRV groups given mean interbeat difference (IBD) during CT coronary angiography: normal, minor, moderate, and severe (IBDs of 0-1, 2-3, 4-10, and >10, respectively). Radiation exposure and image quality were also evaluated. In 444 of these, diagnostic performance was presented as sensitivity, specificity, positive predictive values (PPVs), and negative predictive values and likelihood ratios with corresponding 95% confidence intervals by using quantitative coronary angiography as the reference standard. RESULTS: CT coronary angiography yielded good image quality in 98% of patients and no significant differences in image quality were found among HRF and HRV groups. Radiation exposure was significantly higher in patients with low versus high HRF and in patients with severe versus normal HRV. No significant differences among HRF and HRV groups in image quality and diagnostic performance were found. A nonsignificant trend was found toward a lower specificity and PPV in patients with a high HRF or severe HRV when compared with low HRF or normal HRV in patients with a low calcium score (Agatston score <100). CONCLUSION: DS spiral CT coronary angiography performed with adaptive ECG pulsing results in preserved diagnostic image quality and performance independent of HRF or HRV at the cost of limited dose reduction in arrhythmic patients.

Patient specific 4D coronary models from ECG-gated CTA data for intra-operative dynamic alignment of CTA with X-ray images.

We present an approach to derive patient specific coronary models from ECG-gated CTA data and their application for the alignment of CTA with mono-plane X-ray imaging during interventional cardiology. A 4D (3D+t) deformation model of the coronary arteries is derived by (i) extraction of a 3D coronary model at an appropriate cardiac phase and (ii) non-rigid registration of the CTA images at different ECG phases to obtain a deformation model. The resulting 4D coronary model is aligned with the X-ray data using a novel 2D+t/3D+t registration approach. Model consistency and accuracy is evaluated using manually annotated coronary centerlines at systole and diastole as reference. Improvement of registration robustness by using the 2D+t/3D+t registration is successfully demonstrated by comparison of the actual X-ray cardiac phase with the automatically determined best matching phase in the 4D coronary model.

Dual-time-point 18F-FDG PET/CT versus dynamic breast MRI of suspicious breast lesions.

OBJECTIVE: The purpose of our study was to compare dual-time-point (18)F-FDG PET/CT, performed with the patient in the prone position, and contrast-enhanced MRI in patients with suspected breast malignancy. SUBJECTS AND METHODS: Forty-four patients with 55 breast lesions underwent two PET/CT scans (dual-time-point imaging) in the prone position and breast MRI. Sensitivity, specificity, and overall accuracy were calculated. In addition, the average percentage of change in standard uptake values (Delta%SUV(max)) between time point 1 and time point 2 was calculated for PET/CT. A final histopathologic diagnosis was available for all patients. RESULTS: MRI showed an overall accuracy of 95%, with sensitivity and specificity of 98% and 80%. Conversely, dual-time-point PET/CT showed an accuracy of 84% for lesions with an SUV(max) > or = 2.5 or with a positive Delta%SUV(max), with sensitivity and specificity of 80% and 100% versus 69% accuracy, 62% sensitivity (both, p < 0.001), and 100% specificity (p not significant) for single-time-point PET/CT. On PET/CT, malignant lesions showed an increase in FDG between time points 1 and 2, with a Delta%SUV(max) of 11 +/- 24. Benign lesions showed either no change or a decrease in SUV(max) between time points 1 and 2, with a Delta%SUV(max) of -21 +/- 7. CONCLUSION: A dual time point improves PET/CT accuracy in patients with a suspected breast malignancy over single-time-point PET/CT. On PET/CT, FDG is increasingly taken up over time in breast tumors; conversely, benign lesions show a decrease in FDG uptake over time. These changes in SUV might represent a reliable parameter that can be used to differentiate benign from malignant lesions of the breast on PET/CT examination.

Grey-scale analysis allows a quantitative evaluation of thyroid echogenicity in the patients with Hashimoto's thyroiditis.

OBJECTIVE: In the present study we have performed a grey-scale quantitative analysis of thyroid echogenicity in the patients affected by Hashimoto's thyroiditis (HT), obtaining a numerical estimate of the degree of hypoechogenicity associated with the appearance of thyroid dysfunction. MATERIALS AND METHODS: The study group included 89 patients with serum positivity for thyroglobulin (TgAb) and/or peroxidase (TPOAb) antibodies. Ultrasound (US) evaluation of thyroid gland and biochemical assay of serum thyrotropin (TSH), free-thyroxine (FT4) and free-triiodiothyronyne (FT3) were performed in all patients, and in 40 healthy subjects enrolled as control group. Thyroid echogenicity was compared with that of the surrounding neck muscles, using the grey-scale histogram analysis. The echogenicity was expressed in grey-scales (GWE). RESULTS: In HT patients, the mean of thyroid echogenicity was lower when compared to the normal thyroid (61.9 +/- 8.3 GWE vs. 71.9 +/- 3.1 GWE; P = 0.01). In all HT patients the lowest limit of thyroid echo distribution was in the echogenicity range of the surrounding muscle, the overlapping ranging between 3.4% and 95.0% (mean +/- SD 48.4 +/- 20.9%). The extension of like-muscle hypoechogenicity into the thyroid gland was significantly correlated with serum TSH values (r = 0.37; P < 0.001), serum FT4 values (r = -0.60; P < 0.001), and serum TPOAb values (r = 0.31; P = 0.004). Nobody was hypothyroid when the hypoechogenicity was less than 38.0%, whereas hypothyroidism occurred in all cases with hypoechogenicity of more than 68.9%. The receiving operating characteristic curve demonstrated that 48.3% was the best cut-off for identifying hypothyroid patients with sensitivity, specificity and diagnostic accuracy of 88.9%, 86.3% and 87.6%, respectively. CONCLUSIONS: In conclusion, the grey-scale quantitative analysis has provided a measure of thyroid hypoechogenicity associated with the appearance of hypothyroidism during the course of HT. The results of the present study would encourage the application of the computerized grey-scale analysis as complementary tool to US evaluation in the patients affected by HT.