Malin Båtsman
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Malin Båtsman has a total of 6 co-authors. Here are the top co-authors by number of shared publications:
- Sara Strandberg
Department of Diagnostics and Intervention, Diagnostic Radiology, Umeå University, Umeå, Sweden
2 shared publications - Ulrika Ottander
Department of Clinical Sciences, Obstetrics and Gynecology, Umeå University, Umeå, Sweden
2 shared publications - Assel Kabibulatova
Scientific Research Institute of Radiology Named After ZH.H. Khamzabayev, Astana Medical University, Astana 010000, Kazakhstan
1 shared publication - Karolina Rosendahl
Department of Diagnostics and Intervention, Umeå University, Umeå, Sweden
1 shared publication - Mehzabin Kazi
Department of Diagnostics and Intervention, Diagnostic Radiology, Umeå University, SE-90187 Umeå, Sweden
1 shared publication - Peter Berglund
Department of Diagnostics and Intervention, Diagnostic Radiology, Umeå University, SE-90187 Umeå, Sweden
1 shared publication
Latest Publications
- Open Access
- 23 March 2026
- Published by Wolters Kluwer Health in Annals of Medicine & Surgery
- Vol. 88 (4) , 2532-2539
2[18F]-FDG-PET/CT and 2[18F]-FDG-PET/MRI in primary staging of epithelial ovarian cancer – an early interim analysis of a prospective clinical trial
Objective: In epithelial ovarian cancer (EOC), 2-fluorine-18-fluoro-deoxy-glucose (2-[18F]-FDG)-positron emission tomography (PET) with computed tomography (CT) outperforms CT and magnetic resonance imaging (MRI) in metastasis detection. The aim of this early interim study was to assess feasibility of the study workflow to evaluate accuracy of 2[18F]-FDG-PET/CT and 2[18F]-FDG-PET/MRI compared to stand-alone modalities in primary EOC staging. Methods: The first seven consecutive EOC participants in the prospective PRODIGYN study (NCT05855941) were included. All underwent 2[18F]-FDG-PET/CT and 2[18F]-FDG-PET/MRI at baseline and 6/7 at 3-month evaluation. Molecular imaging-based stage according to International Federation of Gynaecology and Obstetrics (miFIGO) with 2[18F]-FDG-PET/CT and 2[18F]-FDG-PET/MRI was compared to conventional radiological FIGO stage (crFIGO) with CT and MRI, using histopathological FIGO (pFIGO) as reference. At 3 months, therapy response assessment was performed with RECIST 1.1 and PERCIST. Results: At baseline, lymph node metastases were found in 3/7 with both modalities, and distant metastases in 2/7 with 2[18F]-FDG-PET/CT and 1/7 with PET/MRI. miFIGO was higher than crFIGO in 2/7, lower in 2/7, and the same in 3/7. At the 3-month therapy response assessment, RECIST 1.1 showed complete response in all, and PERCIST in 5/6, with partial response in 1/6. Conclusion: The PRODIGYN study workflow appears feasible for accuracy assessment of 2[18F]-FDG-PET/CT and 2[18F]-FDG-PET/MRI compared to stand-alone modalities in primary EOC staging. Early data indicate a possible added value of 2[18F]-FDG-PET/CT and 2[18F]-PET/MRI.
- 23 March 2026
- Published by Wolters Kluwer Health in Annals of Medicine & Surgery
- Vol. 88 (4) , 2532-2539
Open Access2[18F]-FDG-PET/CT and 2[18F]-FDG-PET/MRI in primary staging of epithelial ovarian cancer – an early interim analysis of a prospective clinical trial
Objective: In epithelial ovarian cancer (EOC), 2-fluorine-18-fluoro-deoxy-glucose (2-[18F]-FDG)-positron emission tomography (PET) with computed tomography (CT) outperforms CT and magnetic resonance imaging (MRI) in metastasis detection. The aim of this early interim study was to assess feasibility of the study workflow to evaluate accuracy of 2[18F]-FDG-PET/CT and 2[18F]-FDG-PET/MRI compared to stand-alone modalities in primary EOC staging. Methods: The first seven consecutive EOC participants in the prospective PRODIGYN study (NCT05855941) were included. All underwent 2[18F]-FDG-PET/CT and 2[18F]-FDG-PET/MRI at baseline and 6/7 at 3-month evaluation. Molecular imaging-based stage according to International Federation of Gynaecology and Obstetrics (miFIGO) with 2[18F]-FDG-PET/CT and 2[18F]-FDG-PET/MRI was compared to conventional radiological FIGO stage (crFIGO) with CT and MRI, using histopathological FIGO (pFIGO) as reference. At 3 months, therapy response assessment was performed with RECIST 1.1 and PERCIST. Results: At baseline, lymph node metastases were found in 3/7 with both modalities, and distant metastases in 2/7 with 2[18F]-FDG-PET/CT and 1/7 with PET/MRI. miFIGO was higher than crFIGO in 2/7, lower in 2/7, and the same in 3/7. At the 3-month therapy response assessment, RECIST 1.1 showed complete response in all, and PERCIST in 5/6, with partial response in 1/6. Conclusion: The PRODIGYN study workflow appears feasible for accuracy assessment of 2[18F]-FDG-PET/CT and 2[18F]-FDG-PET/MRI compared to stand-alone modalities in primary EOC staging. Early data indicate a possible added value of 2[18F]-FDG-PET/CT and 2[18F]-PET/MRI.
- Open Access
- 11 October 2025
- Published by MDPI AG in Diagnostics
- Vol. 15 (20) , 2560
Imaging-Based Pre-Operative Differentiation of Ovarian Tumours—A Retrospective Cross-Sectional Study
Objectives: This study aimed to investigate the diagnostic performance of imaging-based biomarkers from computed tomography (CT) and magnetic resonance imaging (MRI) for prediction of malignant and borderline malignant ovarian tumours. Methods: 195 consecutive patients with suspected primary epithelial ovarian cancer were included from the retrospective “Prognostic and Diagnostic Added Value of Medical Imaging in Staging and Treatment Planning of Gynaecological Cancer” (PRODIGYN) study. The radiological stage, according to the International Federation of Gynaecology and Obstetrics system (rFIGO), magnetic resonance imaging (MRI)-based Ovarian-Adnexal Reporting and Data System (O-RADS-MRI) score, and the mean apparent diffusion coefficient (ADCmean) were investigated for prediction of ovarian malignancy, with histopathology as reference. The same imaging biomarkers were applied to the borderline tumour cohort (n = 33) to predict malignant/adverse features, such as micro-invasion. Results: The rFIGO stage demonstrated high accuracy for ovarian malignancy, with an area under the curve (AUC) of 0.98 (95% confidence interval (CI) = 0.97–0.99). On lesion level, the sensitivity and specificity of the O-RADS-MRI score to predict ovarian malignancy, after adjusting for correlated data structure, was 1 (CI: 0.96–1) and 0.82 (CI: 0.70–0.90), respectively. The performance of ADCmean to predict ovarian malignancy on lesion level was moderately high, with AUC = 0.78 (95% CI 0.68, 0.88). Discrimination of adverse features in borderline tumours was not improved. Conclusions: rFIGO and O-RADS-MRI showed excellent performance and outperformed ADCmean as predictive tools for ovarian malignancy but could not predict adverse features in borderline tumours.
- 11 October 2025
- Published by MDPI AG in Diagnostics
- Vol. 15 (20) , 2560
Open AccessImaging-Based Pre-Operative Differentiation of Ovarian Tumours—A Retrospective Cross-Sectional Study
Objectives: This study aimed to investigate the diagnostic performance of imaging-based biomarkers from computed tomography (CT) and magnetic resonance imaging (MRI) for prediction of malignant and borderline malignant ovarian tumours. Methods: 195 consecutive patients with suspected primary epithelial ovarian cancer were included from the retrospective “Prognostic and Diagnostic Added Value of Medical Imaging in Staging and Treatment Planning of Gynaecological Cancer” (PRODIGYN) study. The radiological stage, according to the International Federation of Gynaecology and Obstetrics system (rFIGO), magnetic resonance imaging (MRI)-based Ovarian-Adnexal Reporting and Data System (O-RADS-MRI) score, and the mean apparent diffusion coefficient (ADCmean) were investigated for prediction of ovarian malignancy, with histopathology as reference. The same imaging biomarkers were applied to the borderline tumour cohort (n = 33) to predict malignant/adverse features, such as micro-invasion. Results: The rFIGO stage demonstrated high accuracy for ovarian malignancy, with an area under the curve (AUC) of 0.98 (95% confidence interval (CI) = 0.97–0.99). On lesion level, the sensitivity and specificity of the O-RADS-MRI score to predict ovarian malignancy, after adjusting for correlated data structure, was 1 (CI: 0.96–1) and 0.82 (CI: 0.70–0.90), respectively. The performance of ADCmean to predict ovarian malignancy on lesion level was moderately high, with AUC = 0.78 (95% CI 0.68, 0.88). Discrimination of adverse features in borderline tumours was not improved. Conclusions: rFIGO and O-RADS-MRI showed excellent performance and outperformed ADCmean as predictive tools for ovarian malignancy but could not predict adverse features in borderline tumours.