Background Well differentiated liposarcoma (WDLPS) can be difficult to distinguish from lipoma. Currently, this distinction is made by testing for MDM2 amplification, which requires a biopsy. The aim of this study was to develop a noninvasive method to predict MDM2 amplification status using radiomics features derived from MRI. Methods Patients with an MDM2‐negative lipoma or MDM2‐positive WDLPS and a pretreatment T1‐weighted MRI scan who were referred to Erasmus MC between 2009 and 2018 were included. When available, other MRI sequences were included in the radiomics analysis. Features describing intensity, shape and texture were extracted from the tumour region. Classification was performed using various machine learning approaches. Evaluation was performed through a 100 times random‐split cross‐validation. The performance of the models was compared with the performance of three expert radiologists. Results The data set included 116 tumours (58 patients with lipoma, 58 with WDLPS) and originated from 41 different MRI scanners, resulting in wide heterogeneity in imaging hardware and acquisition protocols. The radiomics model based on T1 imaging features alone resulted in a mean area under the curve (AUC) of 0·83, sensitivity of 0·68 and specificity of 0·84. Adding the T2‐weighted imaging features in an explorative analysis improved the model to a mean AUC of 0·89, sensitivity of 0·74 and specificity of 0·88. The three radiologists scored an AUC of 0·74 and 0·72 and 0·61 respectively; a sensitivity of 0·74, 0·91 and 0·64; and a specificity of 0·55, 0·36 and 0·59. Conclusion Radiomics is a promising, non‐invasive method for differentiating between WDLPS and lipoma, outperforming the scores of the radiologists. Further optimization and validation is needed before introduction into clinical practice.

Objective: To assess tumor behavior and the efficacy of active surveillance (AS) in patients with desmoid-type fibromatosis (DTF). Summary of Background Data: AS is recommended as initial management for DTF patients. Prospective data regarding the results of AS are lacking. Methods: In this multicenter prospective cohort study (NTR4714), adult patients with non-intraabdominal DTF were followed during an initial AS approach for 3 years. Tumor behavior was evaluated according to Response Evaluation Criteria in Solid Tumors. Cumulative incidence of the start of an active treatment and progression-free survival (PFS) were calculated using the Kaplan-Meier method. Factors predictive for start of active treatment were assessed by Cox regression analyses. Results: A total of 105 patients started with AS. Median tumor size at baseline was 4.1cm (interquartile range 3.0–6.6). Fifty-seven patients had a T41A CTNNB1 mutation; 14 patients a S45F CTNNB1 mutation. At 3 years, cumulative incidence of the start of active treatment was 30% (95% confidence interval [CI] 21–39) and PFS was 58% (95% CI 49–69). Median time to start active treatment and PFS were not reached at a median follow-up of 33.7 months. During AS, 32% of patients had stable disease, 28% regressed, and 40% demonstrated initial progression. Larger tumor size (≥5 cm; hazard ratio = 2.38 [95% CI 1.15–4.90]) and S45F mutation (hazard ratio = 6.24 [95% CI 1.92–20.30]) were associated with the start of active treatment. Conclusions: The majority DTF patients undergoing AS do not need an active treatment and experience stable or regressive disease, even after initial progression. Knowledge about the natural behavior of DTF will help to tailor the follow-up schedule to the individual patient.

Desmoid-type fibromatosis (DTF) is a rare, soft tissue tumor of mesenchymal origin which is characterized by local infiltrative growth behavior. Besides “wait and see,” surgery and radiotherapy, several systemic treatments are available for symptomatic patients. Recently, targeted therapies are being explored in DTF. Unfortunately, effective treatment is still hampered by the limited knowledge of the molecular mechanisms that prompt DTF tumorigenesis. Many studies focus on Wnt/β-catenin signaling, since the vast majority of DTF tumors harbor a mutation in the CTNNB1 gene or the APC gene. The established role of the Wnt/β-catenin pathway in DTF forms an attractive therapeutic target, however, drugs targeting this pathway are still in an experimental stage and not yet available in the clinic. Only few studies address other signaling pathways which can drive uncontrolled growth in DTF such as: JAK/STAT, Notch, PI3 kinase/AKT, mTOR, Hedgehog, and the estrogen growth regulatory pathways. Evidence for involvement of these pathways in DTF tumorigenesis is limited and predominantly based on the expression levels of key pathway genes, or on observed clinical responses after targeted treatment. No clear driver role for these pathways in DTF has been identified, and a rationale for clinical studies is often lacking. In this review, we highlight common signaling pathways active in DTF and provide an up-to-date overview of their therapeutic potential.

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PurposeSporadic desmoid-type fibromatosis (DTF) is a rare, chronic, non-metastasising, disease of the soft tissues. It is characterised by local invasive and unpredictable growth behaviour and a high propensity of local recurrence after surgery thereby often having a great impact on health-related quality of life (HRQL). This study aims to review currently used HRQL measures and to asses HRQL issues among DTF patients.MethodsA mixed methods methodology was used consisting of (1) a systematic literature review, according to the PRISMA guidelines (2009), using search terms related to sporadic DTF and HRQL in commonly used databases (e.g. Embase, Medline Ovid, Web of science, Cochrane Central, Psyc Info, and Google scholar), to provide an overview of measures previously used to evaluate HRQL among DTF patients; (2) focus groups to gain insight into HRQL issues experienced by DTF patients.ResultsThe search strategy identified thirteen articles reporting HRQL measures using a wide variety of cancer-specific HRQL tools, functional scores, symptom scales (e.g. NRS), and single-item outcomes (e.g. pain and functional impairment). No DTF-specific HRQL tool was found. Qualitative analysis of three focus groups (6 males, 9 females) showed that participants emphasised the negative impact of DTF and/or its treatment on several HRQL domains. Six themes were identified: (1) diagnosis, (2) treatment, (3) follow-up and recurrence, (4) physical domain, (5) psychological and emotional domain, and (6) social domain.ConclusionA DTF-specific HRQL tool and consensus regarding the preferred measurement tool among DTF patients is lacking. Our study indicates that HRQL of DTF patients was negatively affected in several domains. A DTF-specific HRQL measure could improve our understanding of short- and long-term effects and, ideally, can be used in both clinic and for research purposes.