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We describe 25 patients who were treated for a tumour of the proximal femur by resection and replacement with an uncemented, bipolar, modular prosthesis. When followed up after more than ten years four prostheses (16%) had required revision. Two joints showed wear and another necrosis of the acetabulum. One patient with loosening of the stem had been treated by radiotherapy to the femur. Articular cartilage seemed to be a reliable barrier to acetabular wear. Very few signs of the formation of particulate debris were observed. The most obvious feature in the bone-stem relationship was stress shielding, seen as osteoporosis of the proximal part of the femur around the stem in 68%. Functional activity was satisfactory in 68% of the patients. A better system of reattachment of the soft tissues is needed to avoid pain and a persistent limp.

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ObjectiveThe aim of this retrospective study is to analyze and classify magnetic resonance imaging (MRI) features of primary myxofibrosarcoma (MFS) of the extremities and their correlation with patients’ prognosis (local recurrence [LR] and sarcoma‐specific survival [OS]).MethodsNinety‐four patients with primary MFS of the extremities were included. All MRI were performed with 1.5 Tesla magnet using a standard protocol. The presence of a “tail pattern” was recorded. Myxoid tumor component and contrast enhancement of the tumor were evaluated and graded with semiquantitative method using a newly proposed classification.ResultsA tail‐like pattern was observed in 32% MFS; most of the tumors presented with high myxoid features and high grade of gadolinium (Gd) enhancement. Type 3 myxoid characteristics (P = 0.003) were most often observed in FNCLCC grade 3 tumors. Estimated LR‐free survival rate was 70.3% at 3 and 58.4% at 5 years. A higher LR‐rate was observed in those tumors presenting a tail‐like pattern at MRI (P = 0.039), in those with myxoid features type 2 and 3 (0.047) and in those with Gd enhancement grade 2 or 3 (P = 0.029). A worse OS was observed in Gd enhancement grade 3 (P = 0.013) and in deep tumors (P = 0.031).ConclusionsMFS features on preoperative MRI can be useful in order to identify risk classes of LR and OS. These data may suggest that patients with a tail‐like pattern, high Gd enhancement and high myxoid features should be followed up more carefully after surgery.

We describe and model the evolution of a recent landslide, tsunami, outburst flood, and sediment plume in the southern Coast Mountains, British Columbia, Canada. On November 28, 2020, about 18 million m3 of rock descended 1,000 m from a steep valley wall and traveled across the toe of a glacier before entering a 0.6 km2 glacier lake and producing >100‐m high run‐up. Water overtopped the lake outlet and scoured a 10‐km long channel before depositing debris on a 2‐km2 fan below the lake outlet. Floodwater, organic debris, and fine sediment entered a fjord where it produced a 60+km long sediment plume and altered turbidity, water temperature, and water chemistry for weeks. The outburst flood destroyed forest and salmon spawning habitat. Physically based models of the landslide, tsunami, and flood provide real‐time simulations of the event and can improve understanding of similar hazard cascades and the risk they pose.

We present a workflow for investigating large, slow-moving landslides which combines the synthetic aperture radar (SAR) technique, GIS post-processing, and airborne laser scanning (ALS), and apply it to Fels landslide in Alaska, US. First, we exploit a speckle tracking (ST) approach to derive the easting, northing, and vertical components of the displacement vectors across the rock slope for two five-year windows, 2010–2015 and 2015–2020. Then, we perform post-processing in a GIS environment to derive displacement magnitude, trend, and plunge maps of the landslide area. Finally, we compare the ST-derived displacement data with structural lineament maps and profiles extracted from the ALS dataset. Relying on remotely sensed data, we estimate that the thickness of the slide mass is more than 100 m and displacements occur through a combination of slumping at the toe and planar sliding in the central and upper slope. Our approach provides information and interpretations that can assist in optimizing and planning fieldwork activities and site investigations at landslides in remote locations.