Case presentation: We report a case 41 years old female presented with lesion on the scalp and sternal mass, increasing in size with itchiness and erythematous for 6 months duration. Further CECT scan of brain and neck shows features of malignant left frontal scalp lesion with poor plane with overlying skin and underlying skull bone and CECT of thorax shows a large, irregular heterogeneously enhancing mass with necrotic center noted at right hilar within superior segment of right lower lobe, encasing right middle and lower lobe bronchi. Wedge biopsy of scalp lesion showed an intradermal lesion extensively infiltrating by malignant gland accompanied by desmoplasia and the tumor cells are seen extending into the surgical margins suggestive of ductal eccrine carcinoma.Clinical Discussion:This case highlights the importance and challenges in achieving early diagnosis coupled with the scarcity of information on these leads to difficulty in managing this patient.
Conclusion: In managing Ductal Eccrine Carcinoma tumor, standard method of treatment for has not been established. However, wide surgical excision is the treatment of choice for localized lesions. Regarding prognosis, there is conflicting data published which we describe in this article.
METHODS: A user-friendly software was developed to accurately predict the individual size-specific dose estimation of paediatric patients undergoing computed tomography (CT) scans of the head, thorax, and abdomen. The software includes a calculation equation developed based on a novel SSDE prediction equation that used a population's pre-determined percentage difference between volume-weighted computed tomography dose index (CTDIvol) and SSDE with age. American Association of Physicists in Medicine (AAPM RPT 204) method (manual) and segmentation-based SSDE calculators (indoseCT and XXautocalc) were used to assess the proposed software predictions comparatively.
RESULTS: The results of this study show that the automated equation-based calculation of SSDE and the manual and segmentation-based calculation of SSDE are in good agreement for patients. The differences between the automated equation-based calculation of SSDE and the manual and segmentation-based calculation are less than 3%.
CONCLUSION: This study validated an accurate SSDE calculator that allows users to enter key input values and calculate SSDE.
IMPLICATION FOR PRACTICE: The automated equation-based SSDE software (PESSD) seems a promising tool for estimating individualised CT doses during CT scans.