Elka B Rubin1, Valentina Mazzoli1, Marianne Black1, Arjun D Desai1, Kate Young1, Feliks Kogan1, Ashwin Sreedhar1, Dominic J Vincentini1, Katelin A Knox1, Tomoo Yamada1, Andrew McCabe2, Marc Safran1, Sharmila Majumdar3, Hollis G Potter4, and Garry E Gold1
1Stanford University, Stanford, CA, United States, 2Santa Clara University, Santa Clara, CA, United States, 3University of California San Francisco, San Francisco, CA, United States, 4Hospital for Special Surgery, New York, NY, United States
Synopsis
Basketball players place high loads on their knee joints that
can lead to chronic knee injuries. In
this study, we used advanced MRI methods and a cluster analysis to
longitudinally study cartilage structure and potential early degenerative
changes in Division 1 (D1) basketball players and swimmers. Pre-season and
post-season quantitative results indicate an increase in T2 and T1p
relaxation times in the central compartment of the femoral cartilage in the
basketball players compared to the swimmers. The results of this study suggest
that microstructural changes in knee cartilage can occur in one season of D1
college play.
Introduction
Jumping and impact athletes put extra mechanical stress on
their joints which can lead to chronic knee injuries. In professional
basketball players, patellofemoral injuries are the most common cause of missed
games1. Advanced MRI methods offer a way to non-invasively study
early changes in knee articular cartilage2 and a player's overall risk of
degenerative disease progression. In this multicenter study, we use advanced
quantitative MRI metrics of T1ρ and T2 to longitudinally
study early cartilage changes in Division 1 (D1) basketball players compared with
D1 swimmers. The aim of this study is to investigate the effect of one season of
(D1) basketball play on the imaging findings of an athlete's articular cartilage
microstructure.Methods
In this multicenter longitudinal study, National Collegiate
Athletic Association (NCAA) athletes underwent an MRI before and after their NCAA season using a GE 3T SIGNA Premier scanner (GE Healthcare,
Milwaukee, WI, USA) and a 16-channel flexible phased-array, receive-only coil (NeoCoil,
Pewaukee, WI, USA). The study included 14 D1 basketball players (8 female) and
4 D1 swimmers (3 female). Athletes were scanned using an MRI protocol (Table 1) that included a 3D sagittal combined T1ρ/T2
magnetization-prepared angle-modulated portioned k-space spoiled gradient echo snapshots (MAPSS) sequence3.
T2 and T1ρ relaxation time maps were computed using a
mono-exponential fit of signal data acquired at various echo/spin-lock (TE/TSL)
times (Table 1). Subsequently, we utilized a cluster analysis method4
to identify differences in 2D T1p and T2 relaxation
mapping over time in basketball players and swimmers. Within the cluster
analysis, we identified clusters or contiguous pixels with a size great than
12.4 mm2 where T2 and T1p increases were greater
than two standard deviations above the changes seen in the comparison population of swimmers. Projection maps
were subtracted (post-season) – (pre-season) to create difference maps that we
used to identify clusters in the basketball players based off of a
predetermined intensity and size threshold calculated off of the swimmer’s
average changes in T2 and T1p relaxation times. The intensity and size threshold were 3.42ms and 15 pixels for T2 and 5.1265ms and 15 pixels for T1p. To calculate the difference in T1ρ and
T2 relaxation times during the season the (post-season) –
(pre-season) results were calculated. A generalized linear model was used to
compare the T1ρ and T2 relaxation times of the basketball
players to those of the swimmers.Results
A summary of NCAA pre-season and post-season T2
and T1p relaxation times for patellar and femoral cartilage is in Figure
1. Basketball players showed significantly less of a decrease in relaxation
times during their NCAA season in the anterior and central compartments of
their femoral cartilage compared to the swimmers. The basketball players had significantly less of a decrease in the medial
anterior compartment in T1p (p = 0.0233) and
T2 (p = 0.0253) and lateral anterior compartment
in T1p (p = 0.005) and T2 (p < 0.001) of their femoral cartilage (Figure 2). With regards to the cluster analysis, the percentage of cluster area with significant positive clusters in the femoral cartilage was
significantly higher in the basketball players compared to the swimmers for T2
(p = 0.009) and for T1p (p = 0.021) (Figure 3). The cluster analysis
of the femoral cartilage showed that athletes with significant clusters had a
positive cluster in the medial central compartment and a negative cluster in
the lateral central compartment or vice versa depending on the athlete (Figure 4).Discussion
Generally, T2 and T1p relaxation times
are affected by hydration levels in the cartilage and an increase in the relaxation
times are respectively associated with collagen matrix change or a loss of
cartilage proteoglycan content5. During the course of the NCAA
season both populations had a general decrease in relaxation times in their
femoral cartilage. The larger decrease in T1p and T2 relaxation
times in the swimmers compared to the basketball players may indicate that
swimming has less of a negative impact on joint health compared to basketball.
This could indicate that the swimmer’s off-season puts more stress on their
joints due to increased dry land workouts (weight-lifting and running) and that their in-season loading is beneficial to the swimmer's cartilage
health. Our cluster analysis showed significant positive clusters in one side of the
central (weight-bearing) compartment of their femoral cartilage which indicated that players may placing more load on one side of their knee compared to the other.Conclusion
Knowledge of injury patterns can help to guide treatments
and inform strategies for keeping athletes healthy. It is evident based on the significant change in quantitative values over the course of the season that sports can impact the health of a player’s articular cartilage over a relatively short period of time. This work demonstrates the
immediate effects of a season of play and possible positive or negative effects
that may occur during an athlete’s season and can be used to inform strategies
related to training and rest across a season. Future studies will focus first on the
difference between post-season quantitative MR metrics compared with the
following pre-season in order to measure the effect of the off-season and later on 3 year longitudinal results.Acknowledgements
This work was
funded by the NBA and GE Healthcare Orthopedics and Sports Medicine
Collaboration.
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