Desmoid-type fibromatosis: Tumour response assessment using magnetic resonance imaging signal and size criteria

Imaging-Based Deep Learning for Predicting Desmoid Tumor Progression

Desmoid tumors (DTs) are non-metastasizing and locally aggressive soft-tissue mesenchymal neoplasms. Those that become enlarged often become locally invasive and cause significant morbidity. DTs have a varied pattern of clinical presentation, with up to 50-60% not growing after diagnosis and 20-30% shrinking or even disappearing after initial progression. Enlarging tumors are considered unstable and progressive. The management of symptomatic and enlarging DTs is challenging, and primarily consists of chemotherapy. Despite wide surgical resection, DTs carry a rate of local recurrence as high as 50%. There is a consensus that contrast-enhanced magnetic resonance imaging (MRI) or, alternatively, computerized tomography (CT) is the preferred modality for monitoring DTs. Each uses Response Evaluation Criteria in Solid Tumors version 1.1 (RECIST 1.1), which measures the largest diameter on axial, sagittal, or coronal series. This approach, however, reportedly lacks accuracy in detecting response to therapy and fails to detect tumor progression, thus calling for more sophisticated methods. The objective of this study was to detect unique features identified by deep learning that correlate with the future clinical course of the disease. Between 2006 and 2019, 51 patients (mean age 41.22 ± 15.5 years) who had a tissue diagnosis of DT were included in this retrospective single-center study. Each had undergone at least three MRI examinations (including a pretreatment baseline study), and each was followed by orthopedic oncology specialists for a median of 38.83 months (IQR 44.38). Tumor segmentations were performed on a T2 fat-suppressed treatment-naive MRI sequence, after which the segmented lesion was extracted to a three-dimensional file together with its DICOM file and run through deep learning software. The results of the algorithm were then compared to clinical data collected from the patients' medical files. There were 28 males (13 stable) and 23 females (15 stable) whose ages ranged from 19.07 to 83.33 years. The model was able to independently predict clinical progression as measured from the baseline MRI with an overall accuracy of 93% (93 ± 0.04) and ROC of 0.89 ± 0.08. Artificial intelligence may contribute to risk stratification and clinical decision-making in patients with DT by predicting which patients are likely to progress.

Desmoid-type fibromatosis: toward a holistic management

PURPOSE OF REVIEW

Desmoid-type fibromatosis, a rare locally aggressive fibroblastic proliferation, is a treatment challenge. This review aimed to explore recent data about the management of desmoid-type fibromatosis.

RECENT FINDINGS

New data underline the role of kinases and ɣ-secretase in stimulating cell proliferation and invasiveness in desmoid-type fibromatosis. This explains the proven activity of multikinase inhibitors (sorafenib or pazopanib) in the management of desmoid-type fibromatosis or the emerging role of a ɣ-secretase inhibitor. An international guideline for management was recently published, and this guideline take into account patient point of view. Lastly, recent studies highlight the multidimensional burden of desmoid-type fibromatosis, particularly health-related quality of life (HRQoL).

SUMMARY

Active surveillance with planned MRI is the first-line management in desmoid-type fibromatosis. A site-specific and stepwise approach should be considered for progressive desmoid-type fibromatosis. Further, a risk-benefit analysis that considers the side effects and long-term sequelae should be conducted before deciding to start any treatment. A less aggressive approach should be considered. Multikinase inhibitors are effective, but their tolerability and side effects should be discussed with the patients. The symptoms and HRQoL should be integrated in decision-making. Desmoid-type fibromatosis patients should be offered support to address their needs supportive care.

Desmoid tumors: To treat or not to treat, That is the question

Desmoid tumors (DTs) are a rare disease of intermediate malignancy characterized histologically by a locally aggressive, monoclonal, fibroblastic proliferation and clinically by a variable and often unpredictable course. For decades, surgical resection has been the standard initial treatment approach; however, more recently, a paradigm shift toward a more conservative treatment strategy has been introduced. More than 5 years ago, The Desmoid Tumor Working Group started a consensus initiative in Europe with the aim of harmonizing the strategy among clinicians and setting up treatment recommendations for patients with DTs. This review summarizes the latest joint, global, evidence-based guideline approach to DT management. Moreover, a number of gray areas in the treatment recommendations are discussed, and possible future perspectives on the treatment armamentarium for patients with DTs are presented.