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Quan%ta%ve Tools for Benefit/Risk Op%miza%on in Medical Imaging MIRD CommiAee Pamphlet Wesley Bolch, PhD, PE, DABHP, FHPS, FAAPM Medical Physics Program Department of Biomedical Engineering University of Florida, Gainesville, FL Fall 2013 Mee%ng of the Florida AAPM / Florida HPS West Palm Beach MarrioA Hotel October 2013

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Page 1: Quan%ta%ve)Toolsfor)Benefit/Risk …hpschapters.org/florida/PPT1.pdfassigned)to)male)or)female)pa%entsof)body)morphometries significantly)different)from)those)of)the)ICRP)reference)individuals.))

Quan%ta%ve  Tools  for  Benefit/Risk  Op%miza%on  in  Medical  Imaging  

MIRD  CommiAee  Pamphlet  

Wesley  Bolch,  PhD,  PE,  DABHP,  FHPS,  FAAPM  Medical  Physics  Program  

Department  of  Biomedical  Engineering  University  of  Florida,  Gainesville,  FL  

     

Fall  2013  Mee%ng  of  the  Florida  AAPM  /  Florida  HPS  West  Palm  Beach  MarrioA  Hotel  

October  2013  

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Presenta%on  Outline  

1.   Mo%va%on  for  imaging  dose  reduc%on  and  op%miza%on    2.   Effec%ve  dose  for  quan%fying  the  risk  –  what  is  it  and  where  

does  it  come  from?  

3.   Alterna%ves  to  the  Effec%ve  Dose  –  organ  specific  cancer  risks  

4.   Methods  of  quan%fying  the  benefits  of  medical  imaging  

5.   Upcoming  MIRD  Pamphlet  and  Book  on  this  topic  

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NCRP  Report  160  Ionizing  Radia%on  Exposure  of  the  US  Popula%on    

Early  1980s   2006  ~15%  medical   ~48%  medical  

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Smith-­‐Bindman  et  al    -­‐  JAMA  2010  (1996  to  2010)  

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Smith-­‐Bindman  et  al    -­‐  JAMA  2010  (1996  to  2010)  

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Smith-­‐Bindman  et  al    -­‐  JAMA  2010  (1996  to  2010)  

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Smith-­‐Bindman  et  al    -­‐  JAMA  2010  (1996  to  2010)  

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Poten%al  Stochas%c  Effects  from  CT  

RBM  Dose  from    pediatric  head  CT  

Brain  Dose  from    pediatric  head  CT  

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Demonstrated  Determinis%c  Effects  from  CT  

Cedars-­‐Sinai  Medical  Center    –  Overexposure  of  206  stroke  pa%ents  

undergoing  brain  perfusion  studies    –  Modifica%on  of  imaging  protocols  without  

understanding  or  considera%on  of  radia%on  exposure  

–  Epila%on      

Mad  River  Community  Hospital  2-­‐year-­‐old  male  scanned  151  %mes  over  65  min  Erythema  shown  and  cataracts  expected  Doses  es%mated  to  be  from  2.8  to  11  Gy  Life%me  fatal  cancer  risk  –  es%mated  at  39%  

 

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Effec%ve  Dose  The  effec%ve  dose  is  a  dosimetry  quan%ty  defined  by  the  Interna%onal  Commission  on  Radiological  Protec%on  (ICRP)  and  is  widely  used  as  a  dose  metric  for  stochas%c  risk  following  ionizing  radia%on  exposure.        It  is  widely  used  in  medical  imaging  to  compare  and  contrast  radia%on  risks  associated  with  radiography,  computed  tomography,  fluoroscopy,  and  nuclear  medicine  imaging.      Ques%ons:  What  is  the  history  of  its  development?  

   What  are  the  proper  uses  of  this  quan%ty?      What  are  the  alterna%ves  when  used  improperly?    

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ICRP  System  of  Radia%on  Protec%on  Three  tenets  of  the  ICRP  system…  Jus%fica%on  

 No  prac%ce  shall  be  adopted  unless  its  introduc%on  produces  a  net  posi%ve  benefit        Very  applicable  to  pa%ent  exposures!  

 Op%miza%on  

 All  exposures  shall  be  kept  as  low  as  reasonably  achievable,  economic  and  social  factors  being  taken  into  account    Good  use  of  effec%ve  dose  (or  alterna%ves)  in  medical  imaging  

 Limita%on  

 Doses  to  the  individual  shall  not  exceed  the  limits  recommended  for  the  appropriate  circumstances  by  the  ICRP    Pa%ent  exposures  are  not  regulated  –  defer  to  op%miza%on!  

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History  of  the  Effec%ve  Dose  

Radiat  Env  Biophys  1975  

ICRP  Publica%on  14  (1969)*  

ICRP  Pub  26  (1977)   ICRP  Pub  60  (1991)   ICRP  Pub  103  (2007)  *Radiosensi%vity  and  spa%al  distribu%on  of  dose  

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History  of  the  Effec%ve  Dose  

Radiat  Env  Biophys  1975  

ICRP  Publica%on  14  (1969)  

ICRP  Pub  26  (1977)  

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ICRP  Publica%on  26  -­‐  1977  Absorbed  Dose  (  D  )  and  Dose  Equivalent  (  H  )  

Absorbed  Dose  𝑫=   𝒅𝜺 /𝒅𝒎           where  𝒅𝜺   is  the  mean  energy  imparted  by  ionizing  

radia%on  to  maAer  of  mass  dm  (unit  –  Gy  =  J/kg  )      

Dose  Equivalent  𝑯=𝑫𝑸𝑵    where  Q  is  the  quality  factor  and  N  is  the  product  of      where  Q  is  the  quality  factor  and  N  is  the  product  of  

all  other  modifying  factors  (unit  –  Sv)    Q  based  upon  RBE  values  for  stochas%c  effects  in  humans.      Qphotons  =  Qelectrons

 =  1    and  Qalphas  =  20      func%on  of  L∞    in  water  

 N  could  account  for  factors  such  as  the  absorbed  dose  rate  or  frac%ona%on  scheme,  but  it  was  assigned  a  value  of  1  in  ICRP  26    

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ICRP  Publica%on  26  -­‐  1977  Effec%ve  Dose  Equivalent  (  HE  )  

Under  condi%ons  of  non-­‐uniform  irradia%on,  where  various  organ  and  %ssues  each  receive  a  dose  equivalent  HT  ,  the  effec%ve  dose  equivalent  is  defined  as  the  hypothe%cal,  uniform,  whole-­‐body  dose  equivalent  which,  if  delivered  to  the  individual,  would  result  in  the  same  total  detriment  (fatal  cancer  risk  /  gene%c  damage  to  offspring).    Define  RT    -­‐    Life%me  risk  of  fatal  cancer  or  gene%c  damage  per  

unit  dose  equivalent  to  %ssue  T  (unit  –  Sv  -­‐1)        These  values  of  RT  used  in  ICRP  26  were  derived  from  our  understanding  of  radia%on  cancer  risks  as  of  the  early  1970s.    Note  –  implicit  assump%on  is  the  linear  no-­‐threshold  model  (LNT)  

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ICRP  Publica%on  26  -­‐  1977  Effec%ve  Dose  Equivalent  (  HE  )  

Consider  a  radiopharmaceu%cal  that  localized  in  the  liver    Components  of  “risk”  are  thus  es%mated  from  both  the  self-­‐dose  to  the  liver:        and  the  photon  cross-­‐dose  to  other  organs:  

𝑹𝒊𝒔𝒌↓𝑳𝒊𝒗𝒆𝒓  𝑪𝒂𝒏𝒄𝒆𝒓 =   𝑯↓𝑳𝒊𝒗𝒆𝒓 (𝒎𝑺𝒗)∙   𝑹↓𝑳𝒊𝒗𝒆𝒓 ( 𝒎𝑺𝒗↑−𝟏 )  

𝑹𝒊𝒔𝒌↓𝑳𝒆𝒖𝒌𝒆𝒎𝒊𝒂 =   𝑯↓𝑹𝑩𝑴 ∙   𝑹↓𝑹𝑩𝑴   

𝑹𝒊𝒔𝒌↓𝑲𝒊𝒅𝒏𝒆𝒚𝒔 =   𝑯↓𝑲𝒊𝒅𝒏𝒆𝒚𝒔 ∙   𝑹↓𝑲𝒊𝒅𝒏𝒆𝒚𝒔   

𝑹𝒊𝒔𝒌↓𝑳𝒖𝒏𝒈𝒔 =   𝑯↓𝑳𝒖𝒏𝒈𝒔 ∙   𝑹↓𝑳𝒖𝒏𝒈𝒔   

𝑹𝒊𝒔𝒌↓𝑻𝒐𝒕𝒂𝒍 =   𝑹𝒊𝒔𝒌↓𝑳𝒊𝒗𝒆𝒓 +   𝑹𝒊𝒔𝒌↓𝑹𝑩𝑴 +   𝑹𝒊𝒔𝒌↓𝑲𝒊𝒅𝒏𝒆𝒚𝒔 +   𝑹𝒊𝒔𝒌↓𝑳𝒖𝒏𝒈𝒔   

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ICRP  Publica%on  26  -­‐  1977  What  then  is  the  effec%ve  dose  equivalent  HE  ?  

“Real”  non-­‐uniform  exposure  of  the  pa%ent  

“Hypothe%cal”    uniform  exposure  of  the  reference  pa%ent    yielding  same  total  risk  

This  is  the  pa%ent’s  “effec%ve  dose  equivalent”  HE  

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ICRP  Publica%on  26  -­‐  1977  Effec%ve  Dose  Equivalent  (  HE  )  

(█■𝑻𝒐𝒕𝒂𝒍  𝑹𝒊𝒔𝒌  𝒇𝒓𝒐𝒎   𝒖𝒏𝒊𝒇𝒐𝒓𝒎  𝒊𝒓𝒓𝒂𝒅𝒊𝒂𝒕𝒊𝒐𝒏 )=(█■𝑻𝒐𝒕𝒂𝒍  𝑹𝒊𝒔𝒌  𝒇𝒓𝒐𝒎   𝒏𝒐𝒏𝒖𝒏𝒊𝒇𝒐𝒓𝒎  𝒊𝒓𝒓𝒂𝒅𝒊𝒂𝒕𝒊𝒐𝒏 )    𝑯  ↓𝑻𝑩   (∑𝒊↑▒𝑹↓𝑻↓𝒊   )= 𝑯↓𝑻↓𝟏  𝑹↓𝑻↓𝟏  +   𝑯↓𝑻↓𝟐  𝑹↓𝑻↓𝟐  +   𝑯↓𝑻↓𝟑  𝑹↓𝑻↓𝟑  +…+   𝑯↓𝑻↓𝑵  𝑹↓𝑻↓𝑵      𝑯  ↓𝑻𝑩   (∑𝒊↑▒𝑹↓𝑻↓𝒊   )=  (∑𝒊↑▒𝑯↓𝑻↓𝒊  𝑹↓𝑻↓𝒊   )      𝑯↓𝑬 =𝑯  ↓𝑻𝑩   =  ∑𝒊↑▒𝑯↓𝑻↓𝒊       (𝑹↓𝑻↓𝒊  /∑𝒊↑▒𝑹↓𝑻↓𝒊    )  =    ∑𝒊↑▒𝑯↓𝑻↓𝒊   𝒘↓𝑻↓𝒊    =    ∑𝑻↑▒𝑯↓𝑻  𝒘↓𝑻     𝑯↓𝑬   =    ∑𝑻↑▒𝒘↓𝑻  𝑯↓𝑻   

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ICRP  Publica%on  26  -­‐  1977  Source  of  the  Tissue  Weigh%ng  Factors  wT  

Tissue   Risk  (mSv-­‐1)   Biological  Effect   wT  

Gonads   4  x  10  -­‐6   Risk  to  1st  two  genera%ons  

0.25  

Breast   2.5  x  10  -­‐6   Cancer   0.15  

Red  Marrow   2  x  10  -­‐6   Leukemia   0.12  

Lungs   2  x  10  -­‐6   Cancer   0.12  

Thyroid   0.5  x  10  -­‐6   Cancer   0.03  

Bone  Endosteum   0.5  x  10  -­‐6   Cancer   0.03  

Remainder   5  x  10  -­‐6   Cancer   0.30  

Totals   16.5  x  10  -­‐6   1.00  

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History  of  the  Effec%ve  Dose  

Radiat  Env  Biophys  1975  

ICRP  Publica%on  14  (1969)  

ICRP  Pub  26  (1977)   ICRP  Pub  60  (1991)  

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ICRP  Publica%on  60  –  1991  Effec%ve  Dose  (  E  )  

Absorbed  Dose  DT,R      is  defined  as  the  mean  absorbed  dose  to  %ssue  T  delivered  

by  radia%on  type  R      

Equivalent  Dose  HT  is  defined  as  the  product  of  the  mean  absorbed  dose  and  a  

radia%on  weigh%ng  factor  wR    

𝑯↓𝑻   =    ∑𝑹↑▒𝒘↓𝑹  𝑫↓𝑻,𝑹   

Value  of  wR    have  been  selected  by  the  ICRP  to  be  representa%ve  of  values  of  RBE  of  that  radia%on  for  the  induc%on  of  stochas%c  effects  at  low  absorbed  doses.      

   They  replace  the  quality  factor  Q    

𝑹𝑩𝑬↓𝒂𝒍𝒑𝒉𝒂   =     (𝑫↓𝒙−𝒓𝒂𝒚𝒔 /𝑫↓𝒂𝒍𝒑𝒉𝒂𝒔  )↓𝑺𝒂𝒎𝒆  𝑩𝒊𝒐𝒍  𝑬𝒇𝒇𝒆𝒄𝒕   𝒘↓𝑹   

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ICRP  Publica%on  60  –  1991  Radia%on  Weigh%ng  Factors  wR  

Note  –    These  values  of  wR  are  appropriate  for  stochas%c  effects  only!    Values  RBE  for  alphas,  for  example,  are  only  5  for  determinis%c  effects  

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ICRP  Publica%on  60  –  1991  Revised  Tissue  Factors  wT  

ICRP  Publica%on  26  Values  of  wT  were  based  upon  fatal  cancer  risks  or  severe  gene%c  damage    

ICRP  Publica%on  60    Values  of  wT  were  based  upon  the  concept  of  “detriment”  which  included:    •  Risk  of  fatal  cancer  •  Allowance  for  years  of  life  lost  due  to  differences  in  latency  periods  •  Allowance  for  cancer  induc%on  for  non-­‐fatal  cancers  •  Allowance  for  the  risk  of  severe  hereditary  disease  

   

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ICRP  Publica%on  60  –  1991  Revised  Tissue  Factors  wT  

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ICRP  Publica%on  60  –  1991  Revised  Tissue  Factors  wT  

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ICRP  Publica%on  60  –  1991  Revised  Tissue  Factors  wT  

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ICRP  Publica%on  60  –  1991  Revised  Tissue  Factors  wT  

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ICRP  Publica%on  60  –  1991  Revised  Tissue  Factors  wT  

Footnotes  to  ICRP  60  Table  of  wT  values  

Age  and  sex  averaging  

Defining  the  remainder  %ssues  

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ICRP  Publica%on  60  –  1991  Revised  Tissue  Factors  wT  

Footnotes  to  ICRP  60  Table  of  wT  values  

The  “splirng  rule”  

Note  –  the  “splirng  rule”  was  dropped  in  ICRP  103  

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History  of  the  Effec%ve  Dose  

Radiat  Env  Biophys  1975  

ICRP  Publica%on  14  (1969)  

ICRP  Pub  26  (1977)   ICRP  Pub  60  (1991)   ICRP  Pub  103  (2007)  

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ICRP  Publica%on  103  –  2007  Revised  Tissue  Factors  wT  

Fast  forward  from  1991  to  the  mid-­‐2000s…  •  Some  15  years  of  addi%onal  follow  up  of  the  Bomb  Survivors  •  Epidemiological  studies  of  other  exposed  popula%ons  •  Cancer-­‐specific  advances  treatment  outcomes  

Time  to  once  again  update  %ssue  weigh%ng  factors…  

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ICRP  Publica%on  103  –  2007    

Organ  /  wT   ICRP  26   ICRP  60   ICRP  103  

Bladder   0.05   0.04  

Bone  marrow   0.12   0.12   0.12  

Brain   0.01  

Breast   0.15   0.05   0.12  

Colon   0.12   0.12  

Endosteum   0.03   0.01   0.01  

Esophagus   0.05   0.04  

Liver   0.05   0.04  

Lung   0.12   0.12   0.12  

Skin   0.01   0.01  

Salivary  Glands   0.01  

Stomach   0.12   0.12  

Thyroid   0.03   0.05   0.04  

Gonads   0.25   0.20   0.08  

Remainder   0.30   0.05   0.12  

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ICRP  Publica%on  103  –  2007  Effec%ve  Dose  Belongs  to  the  Reference  Person  Only!  

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MIRD  Statements  on  HE  and  E  

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MIRD  Statements  on  HE  and  E  

What  effec%ve  dose  can  be  used  for…  

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MIRD  Statements  on  HE  and  E  

What  effec%ve  dose  cannot  be  used  for…    Accordingly,  the  effec%ve  dose  for  medical  exposures  cannot  be  assigned  as  an  index  of  stochas%c  risk  to  a  single  individual  pa%ent  (male  or  female),  nor  can  it  be  assigned  to  male  or  female  pa%ents  of  body  morphometries  significantly  different  from  those  of  the  ICRP  reference  individuals.    These  limita%ons  stem  from  the  fact  that  wT  is  both  sex-­‐  and  age-­‐averaged.    As  a  result,  the  sex-­‐averaged  value  of  wT  for  the  breasts  provides  no  informa%on  on  the  risk  of  breast  cancer  in  male  pa%ents.  Similarly,  the  age-­‐averaged  value  of  wT  for  the  thyroid  overemphasizes    the  risk  of  thyroid  cancer  in  adult  pa%ents  and  conversely  underemphasizes  that  risk  in  children.    

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Alterna%ves  to  the  Effec%ve  Dose  

As  presented  previously  in  the  MIRD  Course  on  Dose  Reduc%on  in  Pediatric  Nuclear  Medicine…    Age,  gender,  and  organ  specific  cancer  risk  models  are  available  from  the  documents  such  as  the  BEIR  VII  report  and  EPA  Blue  Book  which  require  knowledge  of  the  mean  absorbed  dose  to  different  organs…the  very  same  values  needed  to  es%mate  the  effec%ve  dose.  

hAp://www.epa.gov/rpdweb00/docs/bluebook/bbfinalversion.pdf  

hAp://www.nap.edu/catalog.php?record_id=11340  

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History  of  the  BEIR  Reports  BEIR  III  (1980):  General  es%mates  of  radia%on  risk  at  low  doses  BEIR  V  (1990):  General  es%mates  of  radia%on  risk  at  low  doses  BEIR  VII  (2005):  General  es%mates  of  radia%on  risk  at  low  doses  

In  the  15  years  since  the  publica%on  of  the  BEIR  V  report  on  low-­‐LET  radia%on,  substan%al  new  informa%on  on  radia%on-­‐induced  cancer  had  become  available  from  the  Hiroshima  and  Nagasaki  atomic  bomb  survivors  (LSS  –  Life  Span  Study),  where  slightly  less  than  half  of  the  original  survivors  were  s%ll  alive  as  of  2000.      The  commiAee  evaluated  nearly  13,000  incidences  of  cancer  and  approximately  10,000  cancer  deaths  in  contrast  to  fewer  than  6000  cancer  deaths  available  to  the  BEIR  V  commiAee.  Also,  since  comple%on  of  the  1990  report,  addi%onal  evidence  had  emerged  from  the  LSS  sugges%ng  that  other  health  effects,  such  as  cardiovascular  disease  and  stroke,  could  result  from  radia%on  exposure.  

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BEIR  VII  Models  

The  BEIR  VII  CommiAee  used  excess  rela%ve  risk  (ERR)  and  excess  absolute  risk  (EAR)  to  project  radiogenic  cancer  risks  to  the  U.S.  popula%on  for  each  cancer  site.      Defini%on  –  Incidence  Rate  𝝀    Incidence  refers  to  new  cases  of  disease  occurring  among  previously  unaffected  individuals.    It  is  calculated  as  the  number  of  new  cases  of  the  disease  occurring  in  the  popula%on  in  a  specified  %me  interval  divided  by  the  sum  of  observa%on  %mes  in  that  interval  for  all  individuals  who  were  disease  free  at  the  beginning  of  each  %me  interval.    

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BEIR  VII  Models  

Defini%ons  –  Model  Parameters      AAained  age  of  an  individual        a    Age  at  exposure  to  radia%on        e    Time  since  exposure          t  =  a  -­‐  e    Radia%on  organ  dose  (in  Sv)        D    Sex  of  individual  (1  –  female  and  0  –  male)    s    Study  popula%on  specific  factors      p    

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BEIR  VII  Models  Excess  Rela%ve  Risk  (ERR)  Model      𝝀↓𝑰 (𝒂,𝒆,𝑫,𝒔,𝒑)=   𝝀↓𝑰↑𝟎 (𝒂,  𝒔,  𝒑)  [𝟏+𝑫⋅ 𝑬𝑹𝑹 (𝒂,  𝒆,  𝒔)]        𝝀↓𝑴 (𝒂,𝒆,𝑫,𝒔,𝒑)=   𝝀↓𝑴↑𝟎 (𝒂,  𝒔,  𝒑)  [𝟏+𝑫⋅ 𝑬𝑹𝑹 (𝒂,  𝒆,  𝒔)]        where      𝝀↓𝑰 (𝒂,𝒆,𝑫,𝒔,𝒑)      =  projected  cancer  incidence  rate  in  exposed  persons     𝝀↓𝑴 (𝒂,𝒆,𝑫,𝒔,𝒑)  =  projected  cancer  mortality  rate  in  exposed  persons      𝝀↓𝑰↑𝟎 (𝒂,  𝒔,  𝒑)    =      baseline  cancer  incidence  rate  by  age  and  sex    

   (i.e.,  rate  for  an  unexposed  popula%on)       𝝀↓𝑴↑𝟎 (𝒂,  𝒔,  𝒑)    =      baseline  cancer  mortality  rate  by  age  and  sex    

   (i.e.,  rate  for  an  unexposed  popula%on)    𝑬𝑹𝑹 (𝒂,  𝒆,  𝒔)  =    excess  rela%ve  risk  per  unit  dose        (i.e.,  propor%onal  increase  in  incidence  rate)  

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BEIR  VII  Models  Excess  Absolute  Risk  (EAR)  Model      𝝀↓𝑰 (𝒂,𝒆,𝑫,𝒔,𝒑)=   𝝀↓𝑰↑𝟎 (𝒂,  𝒔,  𝒑)+  𝑫  ⋅   𝑬𝑨𝑹 (𝒂,  𝒆,  𝒔)           𝝀↓𝑴 (𝒂,𝒆,𝑫,𝒔,𝒑)=   𝝀↓𝑴↑𝟎 (𝒂,  𝒔,  𝒑)+  𝑫  ⋅   𝑬𝑨𝑹 (𝒂,  𝒆,  𝒔)  ⋅   𝝀↓𝑴↑𝟎 (𝒂,  𝒔,  𝒑)/𝝀↓𝑰↑𝟎 (𝒂,  𝒔,  𝒑)         where      𝑬𝑨𝑹 (𝒂,  𝒆,  𝒔)  =    excess  absolute  incidence  risk  per  unit  dose    

   (i.e.,  addi%onal  contribu%on  to  the  incidence  rate)      𝝀↓𝑴↑𝟎 (𝒂,  𝒔,  𝒑)/𝝀↓𝑰↑𝟎 (𝒂,  𝒔,  𝒑)     =      lethality  frac%on  (ra%o  of  mortality/incidence  rates)    

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BEIR  VII  Models  

Func%onal  Form  for  ERR  and  EAR      𝑬𝑹𝑹 (𝒂,  𝒆,  𝒔)    𝒐𝒓     𝑬𝑨𝑹 (𝒂,  𝒆,  𝒔)  =   𝜷↓𝒔   ⋅  𝒆𝒙𝒑(𝜸𝒆↑∗ )  ⋅   (𝒂/𝟔𝟎)↑𝜼        where      𝜷↓𝒔   is  the  sex-­‐dependent  model  parameter  in  units  of  (Sv  -­‐1)  for  the  rela%ve  risk  model  and  in  (per  10,000  person-­‐Sv)  for  the  absolute  risk  model      γ  and  η  are  model  constants  showing  dependences  on  e  and  a,  respec%vely      𝒆↑∗ =   𝒎𝒊𝒏(𝒆,  𝟑𝟎)−  𝟑𝟎/𝟏𝟎       

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BEIR  VII  Models  Model  Parameter  Values  

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BEIR  VII  Models  Age  Dependence  for  Cancer  Incidence  

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BEIR  VII  Models  Age  Dependence  for  Cancer  Mortality  

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BEIR  VII  Models  

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BEIR  VII  Models  The  parameter  life%me  aAributable  risk  or  LAR  approximates  the  probability  that  a  given  radia%on  exposure  at  age  e  will  result  in  a  premature  cancer  incidence  or  death  at  age  a.  This  probably  can  be  thought  of  as  weighted  sums  of  the  age-­‐specific  excess  probabili%es  of  radia%on-­‐induced  cancer  incidence  or  death  –  given  by  the  func%on              M(D,  e,  a).    The  dependence  on  sex  is  implied.      𝑳𝑨𝑹(𝑫,𝒆)=  ∫𝒆+𝑳↑𝟏𝟏𝟎▒𝑴(𝑫,𝒆,𝒂)  ⋅ 𝑺(𝒂)/𝑺(𝒆)   𝒅𝒂   

where      𝑴(𝑫,𝒆,𝒂)  =    risk  at  aAained  age  a  from  radia%on  dose  D  at  age  e  

   (based  on  either  ERR  or  EAR  models  and  can  be  either        for  cancer  incidence  or  cancer  mortality)  

   𝑺(𝒂)    =    probability  of  surviving  to  age  a    𝑺(𝒆)    =    probability  of  surviving  to  age  e      L    =    minimum  latency  period    

   (2  years  for  leukemia  and  5  years  for  solids  cancers)  

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BEIR  VII  Models  Baseline  rates  for  Cancer  Incidence  (blue)  and  Cancer  Mortality  (green)  

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BEIR  VII  Models  

Equa%ons  for  LAR  Calcula%ons    Cancer  Incidence      𝑴↓𝑰 (𝑫,𝒆,𝒂)  =     𝑬𝑹𝑹↓𝑰 (𝑫,𝒆,𝒂)  ⋅   𝝀↓𝑰↑𝟎 (𝒂)  ERR  Model      𝑴↓𝑰 (𝑫,𝒆,𝒂)  =     𝑬𝑨𝑹↓𝑰 (𝑫,𝒆,𝒂)    EAR  Model          Cancer  Mortality      𝑴↓𝑴 (𝑫,𝒆,𝒂)  =     𝑬𝑹𝑹↓𝑰 (𝑫,𝒆,𝒂)  ⋅   𝝀↓𝑴↑𝟎 (𝒂)  ERR  Model      𝑴↓𝑴 (𝑫,𝒆,𝒂)  =     𝑬𝑨𝑹↓𝑰 (𝑫,𝒆,𝒂)⋅   𝝀↓𝑴↑𝟎 (𝒂)/𝝀↓𝑰↑𝟎 (𝒂)   EAR  Model  

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BEIR  VII  Models  Ques%on  Which  model  to  use  then  in  providing  final  es%mates  of  LAR  –  those  based  upon  rela%ve  or  absolute  risk  model?      Answer  BEIR  VII  commiAee  adopted  geometric  averaging  of  LAR  values      𝑳𝑨𝑹=   (𝑳𝑨𝑹↓𝑬𝑹𝑹 )↑𝒘   ⋅   (𝑳𝑨𝑹↓𝑬𝑨𝑹 )↑𝟏−𝒘           Thyroid  cancer:        w  =  1.0        (100%:0%  weigh%ng)      Breast  cancer:    w  =  0.0        (0%:100%  weigh%ng)      Lung  cancer:    w  =  0.3          (30%:70%  weigh%ng)      All  other  cancers:    w  =  0.7    (70%:30%  weigh%ng)          Note  –  EPA  has  chosen  to  use  a  straight  arithme%c  weigh%ng  

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BEIR  VII  Models  LAR  Tables  for  Cancer  Incidence  

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BEIR  VII  Models  LAR  Tables  for  Cancer  Mortality  

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BEIR  VII  Models  Summary  

BEIR  VII  provides  LAR  incidence  and  mortality  es%mates  for  all  solid  cancers,  for  leukemia,  and  following  specific  cancer  sites:  

•  Stomach  •  Colon  •  Liver    •  Lung  •  Bladder  •  Thyroid  

•  Prostate  •  Breast  (Female)  •  Uterus  •  Ovary  •  Other  Sites  (opera%onally  

equivalent  to  remainder  in  the  effec%ve  dose)  

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2011  EPA  Blue  Book  Updates  to  BEIR  VII  Models  

•  In  addi%on  to  the  sites  men%oned  in  BEIR  VII,  EPA  es%mates  LARs  for  the  following  addi%onal  sites:  -­‐  Kidney  -­‐  Bone  Endosteum  -­‐  Skin  –  fatal  cancers  only  

•  Different  Breast  Cancer  mortality  model  is  used  (complex)  -­‐  Accounts  for  long  survival  %mes  between  incidence  and  death  

•  Different  Thyroid  model  is  used  (similar  to  NCRP  Report  159)  -­‐  Explicitly  accounts  for  the  dependence  of  ERR  on  both  age-­‐at-­‐exposure  and  %me-­‐since-­‐exposure    

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MIRD  CommiAee  Ac%vi%es    In  a  forthcoming  MIRD  Pamphlet,  LAR  es%mates  for  addi%onal  

sites  were  developed  in  collabora%on  with  David  Pawel,  biosta%s%cian  at  EPA    

-­‐  Oral  cavity  -­‐  Pancreas  -­‐  Gallbladder    -­‐  Central  Nervous  System  (CNS)  -­‐  Esophagus  -­‐  Rectum  

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Example  –  Thyroid  Cancer  Incidence    

For  thyroid  cancer,  the  modest  discon%nui%es  evident  in  LAR  at  ages  5,  10,  and  15  are  an  ar%fact  of  the  categoriza%on  used  for  age-­‐at-­‐exposure  in  the  thyroid  risk  model.  

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Example  –  Breast  Cancer  Incidence    

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Example  –  Benefit  to  Risk  Ra%o  in  NM?  

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Example  –  Benefit  to  Risk  Ra%o  in  NM?  

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Review  by  Pat  Zanzonico  (2010  SNM)  •  Conventional pre-op work-up → Thoracotomy: 81% (78 / 97)

Thoracotomy futile: 41% (39 / 78) •  Conventional pre-op work-up → Thoracotomy: 65% (60 / 92)

w/ PET Thoracotomy futile: 21% (19 / 60) •  Surgery (Sx)-related mortality: 6.5% •  w/ PET → Avoided futile Sx: 20%

Dat

a Ex

trap

olat

ion

•  New lung cancers in US (2006): 174,470 /yr •  Conventional pre-op work-up → Futile-Sx deaths: 3,766 /yr •  Conventional pre-op work-up → Futile-Sx deaths: 1,547 /yr

+ PET •  Gross benefit of pre-op PET - Lives saved w/ PET: 2,219 /yr •  18FDG ED / 10 mCi: 7 mSv •  Excess cancer deaths: 61 /yr •  Net benefit of pre-op PET - Lives saved w/ PET: 2,158 /yr

B/R Ratio - 36

Van Tinteren et al. Lancet 359: 1388, 2002

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Alterna%ves  to  the  Effec%ve  Dose  

Thus,  as  a  metric  for  op%miza%on  of  benefit  (e.g.,  image  quality)  and  risk  (cancer  induc%on)  in  medical  imaging,  direct  conversion  of  mean  organ  dose  to  cancer  risk  is  increasingly  used  as  an  alterna%ve  to  the  effec%ve  dose.    One  advantage  over  the  effec%ve  dose  is  that  one  can  then  compare  that  risk  to  other  risks  (or  benefits)  in  the  medical  treatment  of  pa%ents.  

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MIRD  Pamphlet  Outline  

1.  Introduc%on  –  ongoing  efforts  to  minimize  radia%on  exposure  in  imaging  

2.  Stochas%c  effects  from  ionizing  radia%on  3.  ICRP  dosimetry  quan%%es  related  to  stochas%c  risk  4.  Quan%fica%on  of  stochas%c  risk  in  medical  imaging    5.  Quan%fica%on  of  medical  benefit  in  medical  imaging  6.  Examples  of  risks  and  benefits  associated  with  medical  

imaging  of  pa%ents  7.  Conclusions  

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Forthcoming  Book  by  Hendee  &  Dauer    

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Forthcoming  Book  by  Hendee  &  Dauer    Introduc*on    Part  I.        Jus%fica%on  in  Medical  Imaging  Part  II.      Radia%on  Dose  In  Medical  Imaging  –    

 Defining,  Measuring  and  Assessing  Part  III.  Radia%on  Risks  in  Medical  Imaging  Part  IV.    Op%miza%on  and  Dose  Reduc%on  in  Medical  Imaging  Part  V.    Shared  Decision  Making  in  Medical  Imaging  Part  VI.    Medical  Imaging  Safety  Approaches    Conclusions  

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This  concludes  my  presenta%on    I  would  be  happy  to  entertain  any  ques%ons!  


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