Abstract. This paper presents a method for extracting lymph node regions from 3-D abdominal CT images using 3-D minimum directional difference filter. In the case of surgery of colonic cancer, resection of metastasis lesions is performed with resection of a primary lesion. Lymph nodes are main route of metastasis and are quite important for deciding resection area. Diagnosis of enlarged lymph nodes is quite important process for surgical planning. However, manual detection of enlarged lymph nodes on CT images is quite burden task. Thus, development of lymph node detection process is very helpful for assisting such surgical planning task. Although there are several report that present lymph node detection, these methods detect lymph nodes primary from PET images or detect in 2-D image processing way. There is no method that detects lymph nodes directly from 3-D images. The purpose of this paper is to show an automated method for detecting lymph nodes from 3-D abdominal CT images. This method employs a 3-D minimum directional difference filter for enhancing blob structures with suppressing line structures. After that, false positive regions caused by residua and vein are eliminated using several kinds of information such as size, blood vessels, air in the colon. We applied the proposed method to three cases of 3-D abdominal CT images. The experimental results showed that the proposed method could detect 57.0 % of enlarged lymph nodes with 58 FPs per case.
Occasionally, we have experienced cases of patients with mild articulating pain who have been introduced to opioids. We considered the possibility that physician assessment alone might be insuf cient. We developed and examined the usefulness of a system that helps pharmacists perform a pain assessment prior to consultation and suggest prescriptions for analgesics.From March 1, 2020 to December 31, 2020, the number of prescription suggestions and the rate at which they were adopted were investigated in patients who were instructed before opioid introduction. The number of patients instructed was 226, whereas the number of prescription suggestions was 231, with an adoption rate of 98.3%. The 23 patients who did not use opioids showed signi cantly improved mean pain scores, from a median NRS of 3 -2 (P = 0.0123), with the most intense pain decreasing from a median NRS of 7 -5 (P = 0.0154). We believe that pain assessment before opioid induction facilitated the selection of an appropriate analgesic. However, among the nine patients who were instructed after opioid introduction, two expressed minor pain. We believe that the pharmacist's prescription suggestion, which is tailored to the patientʼs life background and general condition, promoted the selection of an appropriate analgesic.In conclusion, pharmacists should evaluate pain and prescription suggestions before introducing opioids as a strategy to support medical treatment and promote appropriate opioid use, thereby suggesting their active utilization in clinical practice throughout Japan.
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