Predictors of thermal increase in magnetic resonance–guided focused ultrasound treatment for essential tremor: histogram analysis of skull density ratio values for 1024 elements

Ken Iijima MD1, Hajime Yokota MD, PhD2, Toshio Yamaguchi MD, PhD3, Masayuki Nakano MD, PhD4, Takahiro Ouchi MD5, Futaba Maki MD, PhD5, Masahito Takasaki MD6, Yasuhiro Shimizu MD, PhD1, Hiroki Hori RT, PhD1, Hirokazu Iwamuro MD, PhD7, Jinichi Sasanuma MD, PhD4, Kazuo Watanabe MD, PhD4, and Takashi Uno MD, PhD2
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  • 1 Department of Diagnostic Radiology, Shin-Yurigaoka General Hospital, Kawasaki, Kanagawa;
  • | 2 Department of Diagnostic Radiology and Radiation Oncology, Graduate School of Medicine, Chiba University, Chiba;
  • | 3 Research Institute for Diagnostic Radiology, Shin-Yurigaoka General Hospital, Kawasaki, Kanagawa;
  • | 4 Department of Neurosurgery, Shin-Yurigaoka General Hospital, Kawasaki, Kanagawa;
  • | 5 Department of Neurology, Shin-Yurigaoka General Hospital, Kawasaki, Kanagawa;
  • | 6 Department of Anesthesiology, Shin-Yurigaoka General Hospital, Kawasaki, Kanagawa; and
  • | 7 Department of Neurosurgery, Juntendo University, Tokyo, Japan
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OBJECTIVE

Sufficient thermal increase capable of generating thermocoagulation is indispensable for an effective clinical outcome in patients undergoing magnetic resonance–guided focused ultrasound (MRgFUS). The skull density ratio (SDR) is one of the most dominant predictors of thermal increase prior to treatment. However, users currently rely only on the average SDR value (SDRmean) as a screening criterion, although some patients with low SDRmean values can achieve sufficient thermal increase. The present study aimed to examine the numerical distribution of SDR values across 1024 elements to identify more precise predictors of thermal increase during MRgFUS.

METHODS

The authors retrospectively analyzed the correlations between the skull parameters and the maximum temperature achieved during unilateral ventral intermediate nucleus thalamotomy with MRgFUS in a cohort of 55 patients. In addition, the numerical distribution of SDR values was quantified across 1024 elements by using the skewness, kurtosis, entropy, and uniformity of the SDR histogram. Next, the authors evaluated the correlation between the aforementioned indices and a peak temperature > 55°C by using univariate and multivariate logistic regression analyses. Receiver operating characteristic curve analysis was performed to compare the predictive ability of the indices. The diagnostic performance of significant factors was also assessed.

RESULTS

The SDR skewness (SDRskewness) was identified as a significant predictor of thermal increase in the univariate and multivariate logistic regression analyses (p < 0.001, p = 0.013). Moreover, the receiver operating characteristic curve analysis indicated that the SDRskewness exhibited a better predictive ability than the SDRmean, with area under the curve values of 0.847 and 0.784, respectively.

CONCLUSIONS

The SDRskewness is a more accurate predictor of thermal increase than the conventional SDRmean. The authors suggest setting the SDRskewness cutoff value to 0.68. SDRskewness may allow for the inclusion of treatable patients with essential tremor who would have been screened out based on the SDRmean exclusion criterion.

ABBREVIATIONS

AUC = area under the curve; MRgFUS = magnetic resonance–guided focused ultrasound; ROC = receiver operating characteristic; SDR = skull density ratio.

Illustration from Serrato-Avila (pp 1410–1423). Copyright Johns Hopkins University, Art as Applied to Medicine. Published with permission.

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