Purpose: Continuous wound infiltration (CWI) has been introduced as a component of multimodal analgesia to counteract the adverse effects of the most frequently used opioids. Advantages of reduced-port laparoscopic surgery (RPLS) include cosmetic benefits and decreased postoperative pain. We aimed to investigate the effect of CWI in patients using intravenous (IV) patient-controlled analgesia (PCA) for pain management after RPLS for colorectal cancer.Methods: This retrospective study included 25 patients who received both CWI (0.5% ropivacaine infused over 72 hours) and IV PCA (fentanyl citrate) and 52 patients who received IV PCA alone. The primary endpoint was pain scores on postoperative days (PODs) 0, 1, and 2. Univariate and multivariate analyses were conducted to determine the factors affecting the pain score on POD 0.Results: On POD 0, the mean numeric rating scale score was significantly lower in the CWI group than in the control group (3.2±0.8 vs. 3.7±0.9, P=0.042). However, the scores were comparable between the groups during the rest of the period. Within 24 hours of surgery, the CWI group consumed fewer opioids (0.7±0.9 vs. 1.3±1.1, P=0.018) and more nonsteroidal anti-inflammatory drugs (2.0±1.4 vs. 1.3±1.4, P=0.046) than the control group. Time to removal of IV PCA was significantly longer in the CWI group than in the control group (4.4±1.6 days vs. 3.4±1.0 days, P=0.016).Conclusion: CWI with ropivacaine and IV PCA was more effective than IV PCA alone in controlling postoperative pain within 24 hours of surgery, and opioid use could be reduced further.

Background/Objectives: Ultrasound is the standard imaging modality to evaluate the inflammatory changes in hand joints of rheumatoid arthritis (RA) patients. However, it is operator-dependent and takes a long time to examine. In this study, we developed a radiograph-based deep learning (DL) model to support prioritization of finger joints for ultrasound (US) examination in RA patients. Methods: In this retrospective study, hand radiographs from RA patients who underwent same-day US examination of bilateral finger joints were analyzed. A DL model was developed using hand radiographs from 270 patients (2043 finger joints) to estimate joint-level likelihood of inflammatory activity. US findings served as the reference standard for model training, while clinical findings of joint tenderness and swelling were incorporated as additional tabular inputs. Model performance was evaluated in a temporal-split test cohort consisting of 40 patients (270 joints) and compared with the performance of a clinical-only logistic regression model based on joint tenderness and swelling. Results: In the test set, the DL model demonstrated higher sensitivity (82.1% vs. 38.5%), negative predictive value (96.8% vs. 90.3%), and F1-score (69.6% vs. 48.4%) than the clinical-only model. Although the area under the receiver operating characteristic curve did not differ significantly between models (p = 0.43), precision–recall (PR) analysis showed superior performance of the DL model, with a higher area under the PR curve (0.625 vs. 0.540). At the threshold maximizing the F1-score, DL-assisted triage reduced the number of finger joints selected for US examination by approximately 80%. Conclusions: A radiograph-based DL model can support efficient prioritization of finger joints for US examination in RA, offering a practical approach to enhance joint-level US triage in routine clinical practice.

Le TD, et al. J Korean Soc Radiol. 2026 Sep;87(5):786-801. https://doi.org/10.3348/jksr.2026.0082