CT number distribution and its association with local control and as a marker of lung tumor response to radiation

Rulon Mayer, Kristi Stanton, Larry Kleinberg, Anuradha Chakravarthy, Elliot Fishman

Research output: Contribution to journalArticlepeer-review

Abstract

An early noninvasive indicator of tumor response to therapy and the ability to predict clinical outcome may potentially enhance disease management. Currently, however, tumor response to therapy is often delayed, potentially compromising disease management. We examined the computed tomography (CT) number or Hounsfield unit distribution to follow lung tumor response to radiation treatment. To help interpret the results, we examined whether the CT number distribution follows a simple two-component model. The CT number distribution was derived from a CT-simulator for 11 patients with lung cancer before and after the initial radiation treatment (1-1.5 months, average 3,407 cGy). Clinical outcomes were followed in 8 patients who received 5,5806,660 cGy. All patients were scanned serially, using identical radiation imaging parameters (voltage, current, scan time, and slice thickness) in a CT-simulator. The lung tumors were digitally contoured, and software windows were applied to avoid inclusion of lung tissue in the analysis. Histograms and statistical analysis of the CT numbers for the tumor were generated. Radiation-induced CT number or Hounsfield unit (HU) shifts exceeding a threshold (13 HU) in lung tumors were associated with (P = 0.04) local control (≥ 10 months). Initial lung tumor size (below 100 cm3) was less well-associated with local control (P = 0.26). The change in standard deviation of the CT numbers (derived from the more careful contouring and using software windows) induced by radiation treatment correlated with the change in average CT number (R2 = 0.71). The change in standard deviation did not correlate with a change in tumor volume (R2 = 0.02). Radiation treatments reduced the average CT number (P < 0.001). In summary, radiation reduces the CT number and this reduction may be associated with local control at 10 months. A two-component model is consistent with lung tumor number distribution and its response to radiation.

Original languageEnglish (US)
Pages (from-to)281-288
Number of pages8
JournalRadiation Oncology Investigations
Volume6
Issue number6
DOIs
StatePublished - Dec 1 1998

Keywords

  • Lung tumors
  • Quantitative computed tomography
  • Radiation therapy
  • Tumor response

ASJC Scopus subject areas

  • Radiological and Ultrasound Technology
  • Radiation
  • Oncology
  • Radiology Nuclear Medicine and imaging

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