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MRI and MRSI of prostate cancer State-of-the-art

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MRI and MRSI of prostate cancer State-of-the-art Powered By Docstoc
					   What is the appropriate margin
    for focal therapy of prostate
  cancer when using MRI/MRSI for
         treatment planning?



Proposed secondary study for ACRIN 6659 data


    Fergus Coakley MD, Professor of Radiology and Urology,
 Chief, Abdominal Imaging, University of California San Francisco
 Objective

 Determine the appropriate margin for
  focal therapy of prostate cancer when
  planned from MRI/MRSI
 Background

 Increasing interest in focal therapy as
  “middle way” for prostate cancer treatment
  – Active surveillance – minimalist
  – Definitive treatment (RRP or RT) – high morbidity

 Three requirements for focal therapy:
  – Clinical selection – no consensus
  – Radiological selection – MRI criteria on next slide
  – Adequate margin – purpose of this proposal
 UCSF selection study

 88 patients with MRI/MRSI before RRP
  and with detailed tumor maps
  – MRI/MRSI reviewed by two independent readers
  – Dominant treatable foci = largest lesion & > 0.5cc

 Results:
  – ALL visible lesions on T2 with ≥0.54 cm 3 of
    concordant MRSI abnormality (n = 27 and 25 for
    reader 1 and 2, respectively) were correctly
    identified dominant treatable tumor foci
  Proposal (two steps)

 Apply UCSF criteria to ACRIN database
  – T2 visible & ≥0.54 cm3 concordant MRSI
  – Two readers (remote or travel to ACRIN HQ?)
  – Anticipate small number will meet criteria (<10?)

 Co-register digital pathology with T2
  – Pick largest/best T2 image and “best match”
    pathology slide
  – Morph gland outline on pathology to T2 (allows
    margin measurement using MRI calipers)
  – Measure maximum margin (per quadrant and
    separate capsular from non-capsular?)
              Example




“Best match” T2 MRI and pathology slice
      Example




“Morph” pathology to T2
      Example




“Morph” pathology to T2
              Example




Measure margins – maximum capsular and
    non-capsular plus by quadrant?
  Analysis

 Presumably will be essentially
  descriptive – what margin would have
  encompassed all the tumors?

 Issues for discussion:
  –   Explore additional selection criteria?
  –   More than two reads?
  –   Can readings be done remotely?
  –   Who will fuse images and measure margins?
  –   Funding level? Travel and/or time?

				
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