Algorithm for Surgical Management of Symptomatic Hand and Digital Neuromas

Area of Science:

• Hand surgery
• Peripheral nerve injury
• Neuroma treatment

Background:

• Symptomatic neuromas in the hand cause significant pain and functional loss.
• Surgical options for neuromas have evolved from passive to active techniques.
• A clear guide for selecting surgical approaches for hand neuromas is lacking.

Purpose of the Study:

• To develop a pragmatic, anatomy-driven algorithm for surgical decision-making in hand neuroma treatment.
• To integrate findings from a scoping review with established peripheral nerve surgery principles.
• To provide a clear overview of surgical options for symptomatic neuromas distal to the wrist.

Main Methods:

• Conducted a scoping review of surgical treatments for symptomatic neuromas distal to the wrist.
• Integrated review findings with established peripheral nerve surgery principles.
• Developed an anatomy-driven treatment algorithm to guide operative decisions.

Main Results:

• Literature on neuroma surgery is largely retrospective with varied techniques and outcomes.
• Many patients experience pain improvement after surgery, but direct technique comparisons are limited.
• The algorithm prioritizes reconstruction (primary repair or interposition) when feasible; otherwise, it details nerve-end management options.

Conclusions:

• A structured approach can streamline the evaluation and treatment selection for hand neuromas.
• The proposed algorithm offers a reproducible pathway for contemporary surgical management.
• This framework supports practical considerations for managing hand and digital neuromas.