Gamma Knife Radiosurgery as a Therapeutic Strategy for Intracranial Sarcomatous Metastases

Purpose: To determine the indication and outcomes for Gamma Knife stereotactic radiosurgery (GKSRS) in the care of patients with intracranial sarcomatous metastases. Methods and Materials: Data from 21 patients who underwent radiosurgery for 60 sarcomatous intracranial metastases (54 parenchymal and 6 dural-based) were studied. Nine patients had radiosurgery for solitary tumors and 12 for multiple tumors. The primary pathology was metastatic leiomyosarcoma (4 patients), osteosarcoma (3 patients), soft-tissue sarcoma (5 patients), chondrosarcoma (2 patients), alveolar soft part sarcoma (2 patients), and rhabdomyosarcoma, Ewing's sarcoma, liposarcoma, neurofibrosarcoma, and synovial sarcoma (1 patient each). Twenty patients received multimodality management for their primary tumor, and 1 patient had no evidence of systemic disease. The mean tumor volume was 6.2 cm 3 (range, 0.07-40.9 cm 3), and a median margin dose of 16 Gy was administered. Three patients had progressive intracranial disease despite fractionated whole-brain radiotherapy before SRS. Results: A local tumor control rate of 88% was achieved (including patients receiving boost, up-front, and salvage SRS). New remote brain metastases developed in 7 patients (33%). The median survival after diagnosis of intracranial metastasis was 16 months, and the 1-year survival rate was 61%. Conclusions: Gamma Knife radiosurgery was a well-tolerated and initially effective therapy in the management of patients with sarcomatous intracranial metastases. However, many patients, including those who also received fractionated whole-brain radiotherapy, developed progressive new brain disease. © 2010 Elsevier Inc. All rights reserved.

Stereotactic radiosurgery for arteriovenous malformations, Part 2: management of pediatric patients:management of pediatric patients

The authors conducted a study to define the long-term outcomes and risks of stereotactic radiosurgery (SRS) for pediatric arteriovenous malformations (AVMs).

Stereotactic radiosurgery for arteriovenous malformations, Part 3: outcome predictors and risks after repeat radiosurgery:outcome predictors and risks after repeat radiosurgery

The object of this study was to evaluate the outcomes and risks of repeat stereotactic radiosurgery (SRS) for incompletely obliterated cerebral arteriovenous malformations (AVMs).

Aneurysms increase the risk of rebleeding after stereotactic radiosurgery for hemorrhagic arteriovenous malformations

BACKGROUND AND PURPOSE:
The purpose of this study was to define the risk of rebleeding after stereotactic radiosurgery (SRS) for hemorrhagic arteriovenous malformations with or without associated intracranial aneurysms.

METHODS:
Between 1987 and 2006, we performed Gamma Knife SRS on 996 patients with brain arteriovenous malformations; 407 patients had sustained an arteriovenous malformation hemorrhage. Sixty-four patients (16%) underwent prior embolization and 84 (21%) underwent prior surgical resection. The median target volume was 2.3 mL (range, 0.1-20.7 mL). The median margin dose was 20 Gy (range, 13.5-27 Gy).

RESULTS:
The overall rate of total obliteration defined by angiography or MRI was 56%, 77%, 80%, and 82% at 3, 4, 5, and 10 years, respectively. Before obliteration, 33 patients (8%) sustained an additional hemorrhage after SRS. The overall annual hemorrhage rate until obliteration after SRS was 1.3%. The presence of a patent aneurysm was significantly associated with an increased rehemorrhage risk after SRS (annual hemorrhage rate, 6.4%) compared with patients with a clipped or embolized aneurysm (annual hemorrhage rate, 0.8%; P=0.033).

CONCLUSIONS:
When an aneurysm is identified in patients with arteriovenous malformations selected for SRS, additional endovascular or surgical strategies should be considered to reduce the risk of bleeding during the latency interval.

Stereotactic radiosurgery for arteriovenous malformations, Part 1:management of Spetzler-Martin Grade I and II arteriovenous malformations

The aim of this paper was to define the outcomes and risks of stereotactic radiosurgery (SRS) for Spetzler-Martin Grade I and II arteriovenous malformations (AVMs).

Stereotactic radiosurgery for arteriovenous malformations, Part 4:management of basal ganglia and thalamus arteriovenous malformations

The authors conducted a study to define the long-term outcomes and risks of stereotactic radiosurgery (SRS) for arteriovenous malformations (AVMs) of the basal ganglia and thalamus.

Stereotactic radiosurgery for arteriovenous malformations, Part 5:management of brainstem arteriovenous malformations

In this paper, the authors' goal was to define the long-term outcomes and risks of stereotactic radiosurgery (SRS) for arteriovenous malformations (AVMs) of the medulla, pons, and midbrain.

Picking up the Pieces: Self-Healing in reconfigurable networks

We consider the problem of self-healing in networks that are reconfigurable in the sense that they can change their topology during an attack. Our goal is to maintain connectivity in these networks, even in the presence of repeated adversarial node deletion, by carefully adding edges after each attack. We present a new algorithm, DASH, that provably ensures that: 1) the network stays connected even if an adversary deletes up to all nodes in the network; and 2) no node ever increases its degree by more than 2 log n, where n is the number of nodes initially in the network. DASH is fully distributed; adds new edges only among neighbors of deleted nodes; and has average latency and bandwidth costs that are at most logarithmic in n. DASH has these properties irrespective of the topology of the initial network, and is thus orthogonal and complementary to traditional topology- based approaches to defending against attack. We also prove lower-bounds showing that DASH is asymptotically optimal in terms of minimizing maximum degree increase over multiple attacks. Finally, we present empirical results on power-law graphs that show that DASH performs well in practice, and that it significantly outperforms naive algorithms in reducing maximum degree increase.