COVID-19 vaccination and low cervical lymphadenopathy in the two week neck lump clinic - a follow up audit

The UK COVID vaccination programme has progressed at an astonishing rate since the first patients received their doses in December 2020. It is well known that other vaccines including influenza and human papilloma virus (HPV) can result in reactive lymphadenopathy in the axilla and/or neck. Patients are now presenting via the two week wait neck lump clinic with supraclavicular fossa and low neck lymphadenopathy related to COVID vaccination, and to similar one stop breast clinics with axillary lymph nodes. In an audit of 80 patients seen over a period of one month, we found COVID vaccine-related low neck lymphadenopathy in four cases (5%), with an additional rectal cancer patient thought to have metastatic disease who presented with a Virchow type node. COVID vaccine-related lymphadenopathy should be considered in the differential diagnosis of low-neck nodes if they occurred shortly after vaccination, but it is important to exclude sinister disease using ultrasound and other investigations as necessary.

Supraclavicular lymphadenopathy following COVID-19 vaccination: an increasing presentation to the two-week wait neck lump clinic?

The first COVID-19 vaccination was given in December 2020 and there is an effort to vaccinate the international population on a massive scale. Common side effects from the vaccine include headache and tiredness. Regional lymphadenopathy has been described in relation to other vaccines. We describe two cases of supraclavicular reactive lymphadenopathy presenting in patients who had the COVID vaccination in the ipsilateral arm. Awareness of this diagnosis is important for patients presenting to the neck lump clinic.

A mathematical morphology approach to Euclidean distance transformation

A distance transformation technique for a binary digital image using a gray-scale mathematical morphology approach is presented. Applying well-developed decomposition properties of mathematical morphology, one can significantly reduce the tremendous cost of global operations to that of small neighborhood operations suitable for parallel pipelined computers. First, the distance transformation using mathematical morphology is developed. Then several approximations of the Euclidean distance are discussed. The decomposition of the Euclidean distance structuring element is presented. The decomposition technique employs a set of 3 by 3 gray scale morphological erosions with suitable weighted structuring elements and combines the outputs using the minimum operator. Real-valued distance transformations are considered during the processes and the result is approximated to the closest integer in the final output image.

Edge location to subpixel values in digital imagery

A new method for locating edges in digital data to subpixel values and which is invariant to additive and multiplicative changes in the data is presented. For one-dimensional edge patterns an ideal edge is fit to the data by matching moments. It is shown that the edge location is related to the so-called ``Christoffel numbers.'' Also presented is the study of the effect of additive noise on edge location. The method is extended to include two-dimensional edge patterns where a line equation is derived to locate an edge. This in turn is compared with the standard Hueckel edge operator. An application of the new edge operator as an edge detector is also provided and is compared with Sobel and Hueckel edge detectors in presence and absence of noise.

Three-dimensional shape analysis using local shape descriptors

The three-dimensional shape analysis problem is a very demanding test of shape analysis algorithms. Previous approaches to the problem have employed global features such as moments and Fourier descriptors. Global features lack the capacity for solving the partial shape recognition problem, in which only part of the unknown shape is available. Previous approaches to local shape analysis have employed structural (syntactic) methods, but these methods have so far failed to solve the three-dimensional problem. This paper describes a hybrid structural/statistical local shape analysis algorithm which is applied to the three-dimensional problem.

Effect of spatial frequency on the visibility of unstructured patterns

Threshold measurements have been made on random patterns that have been computer filtered to contain only certain spatial frequencies. The dependence of threshold on the spatial-frequency distribution of the energy in the patterns was measured. The results indicate that the visibility of an unstructured pattern is dependent on the spatial-frequency content of the pattern. Near threshold, narrow-band noise is much more visible than wide-band noise. The narrow-band noise visibility is caused by the presence of structure in the pattern, some of which is rotation sensitive. For wider-band noise, the modulation transfer function is circularly symmetric. The visibility of very-wide-band noise near threshold depends only on the luminance variations concentrated within a one-octave spatial-frequency band.