Download Beyond Images: Characterizing Melanoma Tumors in FDG-PET/CT Scans Undergraduate Category: Physical and Health Sciences Degree Level: B.S. in Physics

Undergraduate
Category:PhysicalandHealthSciences
DegreeLevel:B.S.inPhysics
AbstractID#1254
Beyond Images: Characterizing Melanoma Tumors in FDG-PET/CT Scans
Dena Guo1, Keisha McCall2,4, Amanda Abbott2,4, Heather Jacene2, Christopher Sakellis2, F. Stephen Hodi3., Annick D. Van den Abbeele2,4
1Northeastern
University Dept. of Physics; Dana-Farber Cancer Institute 2Dept .of Imaging, 3Dept. of Medical Oncology, and 4 Center for Biomedical Imaging
New Therapies, New Measures
Melanoma Characterization
Relevance to Nanomedicine
Melanoma is an aggressive form of skin cancer: 5-year survival
rates plummet from 90% in early stages to 10% in advanced,
metastatic melanoma.1 Immunotherapy is a novel approach that
does improve survival rates.2 However, traditional anatomic and
functional tumor response assessment criteria do not fully
describe tumor response to immunotherapy because of its novel
action mechanisms on the microenvironment. Radiomics aims to
analyze imaging features to assess tumor's phenotype
changes.3
All Metastatic Melanoma Tumors
With the development of novel therapeutics such as
nanoparticles and immunotherapy, and new hybrid imaging
technologies such as PET/CT and PET/MRI, there are new
opportunities to better assess response to treatment. These
opportunities include radiomics features of medical imaging,
which allow clinicians to design therapies that are personalized
to each patient.
Radiomics Approach
7 measures showed a significant change in all tumors from
baseline to the first follow up (signed-rank, p < 0.05).
• SUVpeak, SULpeak, SUVmedian, Energy, Mean Absolute
Deviation, Root Mean Square, Entropy
1 measure showed a significant change in all tumors from
baseline to the second follow up (signed-rank, p < 0.05).
• SUVmin
No measure showed a significant change from baseline to both
follow up sessions.
44 patients | 189 tumors | 3 FDG-PET/CT Scans
Baseline
Scan(S0)
Immunotherapy
Tumors
Identifiedby
Radiologist
8 weeks
FollowUp
Scan(S1)
Tumors
Contouredby
Reader
Immunotherapy
8 weeks
PETSUV
Information
Exported
FollowUp
Scan(S2)
Analysis
Tumors Grouped by Patient Outcome
At baseline, both outcome groups did not have significantly
different medians for any measure.
The characteristics of metastatic melanoma tumors and their
response to immunotherapy were successfully described using
radiomics measures.
• SUVmax, SUVpeak, SULpeak, SUVmedian, Energy, Range,
Root Mean Square, Uniformity
Although none of the 15 radiomics measures had predictive
value, 8 measures had prognostic value in categorizing positive
versus negative outcome groups after initiation of treatment.
Further studies and comprehensive statistical analysis are still
required to confirm these observations and explore the potential
of radiomics in assessing therapeutic response.
• Standardized Uptake Values: SUVmax, SUVmin,
SUVmedian,
SUVpeak, SULpeak, Energy
These measures were then compared at S0, S1, and S2 for:
• All 189 metastatic melanoma tumors
• Tumors were grouped based on the clinical outcome of
the
patients (- outcome, + outcome).
Conclusions
However, 8 measures showed a significant difference between
the two outcome groups in both follow up sessions (rank sum, p
< 0.05).
Analyzed 15 first-order gray level statistics radiomics
measures:
• Heterogeneity Values: Kurtosis, Skewness, Mean
Absolute Deviation, Range, Root Mean Square, Standard
Deviation, Variation, Entropy, Uniformity
Hybrid imaging FDG-PET/CT. Anatomical (CT) and functional (PET) imaging
provide two complementary components for characterizing the effect of
therapies.
Bibliography
Radiomics Measures Over Time. The SUVmax and Uniformity of individual tumors
did not significantly change (signed-rank, p > 0.05) from baseline to either follow
up session. However, there were significant differences (rank sum, p < 0.05) in the
average SUVmax and average Uniformity between the two outcome groups, as
shown by the asterisks.
Acknowledgments
This CaNCURE co-op research project was supported by
National Cancer Institute grant #1CA174650-02.
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