Evaluation of Intraoperative Usage of Sentinella in Detecting Sentinel Lymph Nodes

The aim of this study is to investigate whether the Sentinella camera improves intraoperative detection and removal of sentinel lymph nodes (SLNs) when used in conjunction with standard detection methods. Of primary interest is whether the Sentinella camera identifies additional tumor-positive SLNs that are missed using traditional imaging techniques. Other outcomes related to the standard of care use of the Sentinella camera may also be assessed.

Sentinella is an FDA-approved, high-resolution, portable gamma camera that gives valuable visual guidance to surgeons in certain types of cancer surgeries where no, or only limited, visual guidance was possible previously. The significance of this new aid is the improved possibility of locating and removing all lymph nodes that drain directly from tumors-so-called "SLNs"-in order to accurately assess both the staging of the cancer as well as the best possible operative and post-operative treatment. Sentinella can confirm that no significant lymph nodes are missed and document this "clean field" on the patient's permanent record.

Usually, there is more than one SLN. False-negative SLN biopsy results may impair patient outcome for several reasons: missed nodes might lead to recurrence that can be potentially difficult to treat on occasions, involved nodes may be a potential secondary source of distant metastases, and understaging affects decisions about systemic therapy and specific radiation therapy. Missing SLNs is one of the main factors which increase the false-negative rates.

Sentinel node biopsy is undoubtedly the standard of care for breast cancer and melanoma because of the vital information the histological status of these nodes gives. Correct identification of these SLNs is challenging because of limitations of current preoperative imaging and the lack of visualization in the OR:

* What appears to be a single node in a preoperative lymphoscintigraphy or SPECT can turn out to be 2 or more different nodes that are close together. This is due to relatively low spatial resolution of these technologies.
* Structures can be "hidden" by other structures such as the principle tumor/injection site, making identification difficult or impossible. In these cases, Sentinella will discover the structure upon removal of the principle tumor and aid the surgeon in its removal.
* Currently used gamma probes give only audible and non-recorded aid to surgeons and can easily miss structures when they are more than 2 cm deep in tissue.

Sentinella gives additional visual information to surgical teams that can improve patient outcomes. It does not replace, but rather compliments current standard procedures, and it offers precise documentation of each step of the procedure to be kept permanently on the patient's record.

1. After standard injection of radiotracer and imaging are performed preoperatively, Sentinella can be used in the OR to identify the position of the structures and mark the skin for surgeon's reference.
2. Before removal, Sentinella can be used to visualize and quantify the radioactivity of each structure. This information is stored for future reference.
3. Upon removal of each structure, Sentinella can be used to verify ex-vivo the activity of the structure removed.
4. After removal and verification of all the structures planned, Sentinella is used to confirm that no active structure is left in and to document the resulting "clean field"

The current standard of care for surgical SLN biopsy involves use of a gamma probe. In this study, the investigators will prospectively collect Sentinella images obtained during this standard of care procedure and compare and correlate the findings with other standard of care imaging studies, and treatment and outcome information.

Eligibility Criteria:
Inclusion Criteria:

* All melanoma patients, with a Breslow thickness \>1mm, who are seen at CPMC for sentinel node biopsy will be eligible to participate in this study provided that they have given consent.