Background and Aim: Breast cancer is the most common cancer among women which leaves a profound impact on their psychosocial health and pain experience. The aim of this study was to determine the effect of group psychotherapy based on Acceptance and Commitment Therapy (ACT) on pain-related anxiety and cognitive emotion regulation of women with breast cancer. 
Methods & Materials: In this quasi-experimental study, subjects were 68 women with breast cancer refereed to Shahid Ghazi Hospitalin Tabriz, Iran who were selected using a convenience sampling method. Then, they were randomly assigned into two groups of intervention (n = 34) and control (n = 34). The intervention group underwent eight 90-min sessions of ACT-based group therapy, while the control group received no any intervention. They completed Pain Anxiety Symptom Scale Short Form and Cognitive Emotion Regulation Questionnaire before and one week after treatment. Collected ata were analyzed by using t test, chi-square test, ANCOA and MANCOVA. 
Ethical Considerations This study has obtained its ethical approval from the Research Ethics Committee of Tabriz University of Medical Sciences (code: IR.TBZMED.REC.1397.287) and has been registered by Iranian Registry of Clinical Trials (code: IRCT2017100615590N5).
Results: The ACT-based intervention improved the dimensions of pain-related anxiety (8.44±1.5) and cognitive regulation of negative (8.40±3.5) and positive (8.39±7.5) affects (P<0.001).
Conclusion: ACT-based intervention can help breast cancer patients to accept their negative thoughts and current conditions. 

Background and Aim: Breast cancer is the abnormal cell growth in the breast. In both benign and malignant masses, there is rapid and high cell growth. Nowadays, due to the development of technologies, the diagnosis of diseases has become non-invasive and physicians attempts to diagnose the disease without surgery and based on internal organ images.
Methods & Materials: In this study, by using images prepared from the Digital Database for Screening Mammography (DDSM), a new method is proposed for detecting cancerous masses in the mammographic images using geometric features extraction and optimization of Support Vector Machine (SVM) parameters to classify breast cancer masses automatically. First, images were pre-processed and then boundaries were determined using threshold method. Next, morphological operators were used to improve these boundaries and the segmentation of images was carried out to classify cancerous masses. Finally, by using the SVM parameter optimization method, Grasshopper Optimization Algorithm (GOA), and 4-fold crossvalidation method, data were classified into two groups of benign and malignant (cancer) masses.
Ethical Considerations Images from DDSM database were used in this research, all images are open access in this database.
Results: The accuracy, sensitivity and specificity values for applying the Radial Basis Function (RBF) kernel in SVM classifier (before optimization process) were obtained 97%, 100% and 96, respectively. After optimization of SVM parameters by the GOA, it was reported 100% for all accuracy, sensitivity and specificity indices for applying linear kernel function, indicating the high accuracy of the proposed method. The average values of accuracy, sensitivity and specificity indices for applying all three SVM kernel functions after optimization were 95.83, 100 and 94.81%, respectively.
Conclusion: The extracted geometrical features from breast cancer masses are highly efficient for model training and the diagnosis of breast cancer. The GOA could improve the overall accuracy of the proposed method by optimizing the SVM parameters. The results showed the higher performance of the proposed method compared to other methods.

Background and Aim: Breast cancer is among the most prevalent cancers in women with extensive associated biopsychological problems. The present study aimed to determine the effects of holographic reprocessing therapy on cognitive flexibility and posttraumatic growth in women with breast cancer.
Methods & Materials: This was a quasi-experimental study with pretest-posttest and a control group design. The statistical population included all patients with breast cancer who underwent mastectomy and who were being treated in the chemotherapy ward of Imam Khomeini Hospital in Ardabil City, Iran, in 2020.
By convenience sampling method, 30 women with breast cancer were selected and randomly divided into the experimental and control groups (n=15/group). The experimental group, while receiving pharmacotherapy, collectively underwent holographic reprocessing therapy in 9 one-hour sessions (two sessions per week) for 5 weeks; however, the control group received only pharmacotherapy. Both research groups were assessed in pretest and posttest phases by the Cognitive Flexibility Inventory (Dennis & Vander Wal, 2010) and the Posttraumatic Growth Inventory (Tedeschi & Calhoun, 1996). Finally, the obtained data were analyzed using Multivariate Analysis of Covariance (MANCOVA) in SPSS v. 23.
Ethical Considerations: All study subjects provided a signed written informed consent form. The Research Ethics Committee of Ardabil University of Medical Sciences approved this study (Code: IR.ARUMS.REC.1399.393).
Results: The current study results indicated that holographic reprocessing therapy was effective on cognitive flexibility (F= 42.319, P<0.01) and posttraumatic growth (F= 18.300, P<0.01) in women with breast cancer; this method also increased their cognitive flexibility and posttraumatic growth.
Conclusion: Considering psychological factors and information processing methods in patients with cancer is highly important. Thus, counselors and psychotherapists are advised to use holographic reprocessing therapy as a complementary treatment without adverse effects along with medical treatments to reduce the psychosocial problems caused by the disease.