Clinical Research Directory

The Effect of Nerve Blocks on Analgesia in Breast Cancer Surgery

Postoperative pain following modified radical mastectomy remains a significant clinical concern and may adversely affect patient recovery, opioid consumption, and overall patient satisfaction. Ultrasound-guided regional anesthesia techniques have gained increasing importance as part of multimodal analgesia strategies in breast surgery. The serratus anterior plane (SAP) block is a commonly used interfascial plane block for postoperative analgesia in thoracic and breast procedures. Recently, the serratus posterior superior intercostal plane (SPSIP) block has emerged as a novel regional anesthesia technique with potentially wider thoracic dermatomal spread and effective analgesic properties. This prospective randomized controlled study aims to compare the postoperative analgesic efficacy of the SPSIP block and SAP block in patients undergoing modified radical mastectomy under general anesthesia. Patients will be randomly allocated into two groups to receive either ultrasound-guided SPSIP block or SAP block preoperatively. Primary outcomes will include postoperative pain scores and opioid consumption within the first 24 hours after surgery. Secondary outcomes will include time to first analgesic request, rescue analgesic requirements, intraoperative hemodynamic parameters, postoperative nausea and vomiting, block-related complications, and patient satisfaction. The study is designed to evaluate whether SPSIP block provides superior postoperative analgesia compared with SAP block in modified radical mastectomy surgery.

Deep Learning for Musculoskeletal Complications in Breast Cancer

Survival after breast cancer has increased due to early diagnosis and advances in treatment methods. Musculoskeletal problems related to cancer and its treatment constitute a significant part of the daily practice of physiatrists and rehabilitation specialists involved in oncological rehabilitation. Lymphedema can occur at any stage of a patient's life following breast cancer. Patients with breast cancer-related lymphedema require lifelong treatment, and as the stage of lymphedema progresses, response to therapy decreases. Advanced stages of lymphedema negatively affect functional status, and patients experience difficulties in performing activities of daily living. Axillary web syndrome (AWS) is characterized by a taut cord extending from the axilla to the volar surface of the wrist, typically appearing within the first 8 weeks postoperatively. AWS can complicate the administration of radiotherapy. Shoulder dysfunction may occur independently or in association with AWS. In particular, scapular dyskinesis developing after mastectomy can lead to secondary shoulder conditions such as rotator cuff syndrome or adhesive capsulitis, which are commonly observed in these patients. Peripheral neuropathy is frequently seen in patients receiving chemotherapy, adversely affecting daily life and sometimes preventing continuation of treatment. Other complications related to chemotherapy and radiotherapy include cardiotoxicity, pulmonary toxicity, fatigue, osteoporosis, and cognitive impairment. There are also specific painful syndromes that may occur after breast cancer, including post-mastectomy pain syndrome, phantom breast pain, and musculoskeletal symptoms associated with aromatase inhibitors. All these conditions can significantly impair daily functioning and even hinder continuation of cancer treatment. Therefore, predicting these complications and implementing or developing preventive interventions is crucial. If it is possible to predict the early development of lymphedema, axillary web syndrome, peripheral neuropathy, and painful syndromes after breast cancer, early intervention may prevent progression. This study is designed to develop and validate a predictive model using deep learning methods to determine the risk of these complications in patients undergoing breast cancer surgery. Among deep learning architectures, ResNet50, AlexNet, GoogleNet, and UNet, which have been widely used in recent studies, are planned to be implemented. Additionally, based on the results of this study, a risk calculation program will be developed, allowing clinicians to input baseline patient data and calculate the individual patient's risk for each complication prior to treatment. No specific risk is expected in the study.