Incremental Learning Meets Transfer Learning: Application to Multi-site Prostate MRI Segmentation

Many medical datasets have recently been created for medical image segmentation tasks, and it is natural to question whether we can use them to sequentially train a single model that (1) performs better on all these datasets, and (2) generalizes well and transfers better to the unknown target site domain. Prior works have achieved this goal by jointly training one model on multi-site datasets, which achieve competitive performance on average but such methods rely on the assumption about the availability of all training data, thus limiting its effectiveness in practical deployment. In this paper, we propose a novel multi-site segmentation framework called incremental-transfer learning (ITL), which learns a model from multi-site datasets in an end-to-end sequential fashion. Specifically, "incremental" refers to training sequentially constructed datasets, and "transfer" is achieved by leveraging useful information from the linear combination of embedding features on each dataset. In addition, we introduce our ITL framework, where we train the network including a site-agnostic encoder with pre-trained weights and at most two segmentation decoder heads. We also design a novel site-level incremental loss in order to generalize well on the target domain. Second, we show for the first time that leveraging our ITL training scheme is able to alleviate challenging catastrophic forgetting problems in incremental learning. We conduct experiments using five challenging benchmark datasets to validate the effectiveness of our incremental-transfer learning approach. Our approach makes minimal assumptions on computation resources and domain-specific expertise, and hence constitutes a strong starting point in multi-site medical image segmentation

Novel technique to fenestrate an aortic dissection flap using electrocautery

Chronic distal thoracic dissections treated with thoracic endovascular repair are prone to type Ib false lumen perfusion. When the supraceliac aorta is of normal caliber, fenestration of the dissection flap proximal to the visceral vessels creates a seal zone for the thoracic stent graft and eliminates the type Ib false lumen perfusion. We describe a novel way of crossing the septum using electrocautery delivered through a wire tip then fenestrating the septum using electrocautery delivered over a 1-mm area of uninsulated wire to cut the septum. We believe the use of electrocautery creates a controlled and deliberate aortic fenestration during endovascular repair of a distal thoracic dissections

Novel technique to fenestrate an aortic dissection flap using electrocautery

Chronic distal thoracic dissections treated with thoracic endovascular repair are prone to type Ib false lumen perfusion. When the supraceliac aorta is of normal caliber, fenestration of the dissection flap proximal to the visceral vessels creates a seal zone for the thoracic stent graft and eliminates the type Ib false lumen perfusion. We describe a novel way of crossing the septum using electrocautery delivered through a wire tip then fenestrating the septum using electrocautery delivered over a 1-mm area of uninsulated wire to cut the septum. We believe the use of electrocautery creates a controlled and deliberate aortic fenestration during endovascular repair of a distal thoracic dissections

Acute Limb Ischemia: Patient-reported Quality of Life and Ambulation Outcomes

Objectives: There are few studies describing quality of life (QoL) and ambulation status after acute limb ischemia (ALI). We used a vascular disease-specific questionnaire (VascuQoL-6) and a generic quality of life assessment (European Quality of Life 5D-5L [EQ-5D]) to assess these outcomes. Methods: Using a prospectively collected, single-institution ALI database, the EQ-5D and VascuQoL-6 surveys were administered. Patient demographics, medical history, inpatient variables, outcomes, and ambulatory functional status at last follow-up were collected. Univariate analyses were used to correlate the VascuQoL-6 composite score and the EQ-5D index score with the collected variables. Results: Between May 2016 and February 2022, 234 patients were entered into the database; of these, 40 responded to our surveys (17%). Average age was 59 years, 55% were male, and 45% were Black. Rutherford class on presentation was 1 in 10 patients, 2a in 11 patients, 2b in 17 patients, and 3 in two patients. Three patients underwent medical management only, four patients had a primary amputation, 10 patients underwent endovascular revascularization, and 22 patients underwent an open revascularization. At 30 days, 93% of patients (37/40) had limb salvage; however, by 1 year, this decreased to 60% (22/37). Functional status at last follow-up (mean, 15-18 months) included 23 patients with normal ambulation, 10 patients with partially limited ambulation (neurological deficit or chronic pain), five ambulatory on prosthetics after amputation, and two non-ambulatory after amputation. Average VascuQoL-6 score was 16.8 (of a max of 24) for normal ambulation, 13.8 for partially limited ambulation, and 15.8 for prosthetic ambulation after amputation (P-value =.223). The VascuQoL-6 composite score was associated with age (inversely correlated; P \u3c.001) and EQ-5D score (P \u3c.001) only. The EQ-5D was also significant for age (inversely correlated; P =.032) and VascuQoL-6 composite score (P \u3c.001), whereas ambulatory functional status approached significance (P =.079). Rutherford classification, etiology, type of revascularization, length of stay, limb salvage, and functional ambulatory status did not correlate with QoL outcomes on either assessment. Conclusions: When comparing QoL after acute limb ischemia, younger patients had worse functional outcomes. There was no statistically significant difference in QoL for presenting Rutherford classification, limb salvage, type of revascularization, or functional ambulatory status

Weakly Supervised Deep Learning for Aortic Valve Finite Element Mesh Generation from 3D CT Images

Finite Element Analysis (FEA) is useful for simulating Transcather Aortic Valve Replacement (TAVR), but has a significant bottleneck at input mesh generation. Existing automated methods for imaging-based valve modeling often make heavy assumptions about imaging characteristics and/or output mesh topology, limiting their adaptability. In this work, we propose a deep learning-based deformation strategy for producing aortic valve FE meshes from noisy 3D CT scans of TAVR patients. In particular, we propose a novel image analysis problem formulation that allows for training of mesh prediction models using segmentation labels (i.e. weak supervision), and identify a unique set of losses that improve model performance within this framework. Our method can handle images with large amounts of calcification and low contrast, and is compatible with predicting both surface and volumetric meshes. The predicted meshes have good surface and correspondence accuracy, and produce reasonable FEA results

Single-center Experience with JETi Hydrodynamic Thrombectomy System for Arterial Occlusions of the Extremities

Objectives: Percutaneous aspiration thrombectomy is a new modality for treating patients with acute limb ischemia (ALI). We report our experience and outcomes using the JETi hydrodynamic thrombectomy system (Abbott Vascular, Abbott Park, IL) to treat acute arterial occlusions of the extremities. Methods: This a single-center retrospective review of patients with acute occlusions of peripheral arteries or grafts treated with the JETi from September 2020 to December 2022. JETi was used either as primary intervention or as an adjunct to treat distal vessel thrombus after proximal open thrombectomy. The primary outcome for success was defined as \u3e50% luminal opening post-intervention. Indications, limb salvage, and major adverse events were reviewed. Results: The JETi was used in 59 procedures (56 acute lower extremity ischemia [ALEI], three acute upper extremity ischemia [AUEI]) to treat 124 arteries in 57 patients. Mean age was 62 years (range, 29-95 years), and 49% were male. The mean duration of symptoms before hospitalization was 4.8 days (range, 0 hours to 21 days) for ALEI. The primary outcome was achieved in 102 of 124 (83%) arteries by JETi alone. Additional modalities including open thrombectomy, angioplasty, and stenting were used in five arteries to achieve the primary outcome. Seventeen arteries failed to achieve primary outcome with JETi with or without an adjunct. Reasons for failure were attributed to small artery size and chronic nature of the clot. Complete luminal patency with JETi thrombectomy alone was achieved in 52 arteries (42%). Additionally, 55 arteries underwent additional procedures (angioplasty and stenting) to restore complete luminal patency, which was successfully achieved in 49 vessels (89%) (Table). Average estimated blood loss in JETi-only procedures was 335 mL and 384 mL in those who underwent adjunctive procedures to achieve the primary outcome. Complications included distal embolization (5), access site hematoma (3), and acute kidney injury (AKI) (8). Two AKIs were attributed to rhabdomyolysis with creatine phosphokinas \u3e10,000 IU/L; none of whom needed dialysis. There was a single 30-day mortality. Six patients required major limb amputations within 30 days – two after unsuccessful recanalization and one each for severe gangrene despite restoration of in-line flow, reocclusion of a distal bypass graft, recurrent ALEI postoperative day 15 with non-viable muscle on exploration, and a delayed compartment syndrome diagnosis. Conclusions: Success of the JETi to remove the targeted clot was 83%. The JETi system is an efficacious and safe tool for use in the treatment of acute artery occlusion

Doubling of Decipher Biopsy Genomic Score Is Related to Disease Reclassification on Subsequent Surveillance Biopsy but Not Adverse Features on Radical Prostatectomy

The utility of serial Decipher biopsy scores in a true active surveillance population is still unknown. In a man on active surveillance for low-risk prostate cancer, a doubling of the Decipher biopsy score within genomic low-risk category from first to the second biopsy related to biopsy reclassification to Gleason grade group 4 on the third biopsy. However, the final pathology at radical prostatectomy showed Gleason grade group 2 with an organ-confined disease. This case suggests that the genomic risk category of Decipher biopsy scores during active surveillance may be more informative than either the interval genomic score change or the biopsy Gleason grade group