MAMMOGRAPHY QC: MORE THAN PHANTOM IMAGES. Stephanie Schofield RTR QC Technologist Nova Scotia Health Authority

Transcription

1 1 MAMMOGRAPHY QC: MORE THAN PHANTOM IMAGES Stephanie Schofield RTR QC Technologist Nova Scotia Health Authority

2 Disclaimer 2 I have nothing to disclose.

3 Outline 3 QC tests for the mammography technologist Quality Flat field Artifact SNR/CNR Phantom Importance of Image Quality (QA) Positioning Review of CARJ article MAP Reviewing Daily quality

4 Quality 4 Assurance: A system of activities that when implemented will improve patient care Control: a set of specific tests looking for defects that will cause a reactive process The QC tests performed have changed over the years The constant is the mammography technologist

5 The Mammography Technologist 5 Performs QA every time they image a patient Ensure there are no issues with your equipment that need service Evaluate images: diagnostic vs. repeat Evaluate for artifacts or any issues with images that seem unusual or different. Always seeking ways to improve System, Positioning, Work flow

6 6 QC Tests Radiation Protection and Quality Standards in Mammography - Safety Procedures for the Installation, Use and Control of Mammographic X-ray Equipment: Safety Code 36

7 QC in N.S. 7 We have 1 Medical Physicist For the Academic centre and zone We are working on a provincial QC manual. outcomes and processes Currently no provincial QC program Currently, the MAP recommends the frequency of some specific tests AND to ensure you meet the manufacturers specifications. Be kind to your service engineers.

8 Artifact (flat field) Detection 8 The PMMA: treat it like the fragile beast it is Raw vs. Processed Window (light to black) If processed view on WW/WL that is mid grey appropriate for breast tissue View 1:1 pixel or Magnify Look for: Blotches/streaks Any textured appearances Any observable lines or structures (collimator cut off or ghosting) Black or white pixels An artifact is significant if it mimics or obscures anatomical features.

9 Artifact 9 Do a calibration and recheck All artifacts should be discussed with service personnel or physicist ASAP

10 SNR/CNR 10 Signal to Noise Ratio Measure of sensitivity of a system. How good is your signal relative to the background noise. = (Meanbackground - DCoffset) / (SDbackground) Contrast to Noise Ratio Signal intensity differences between two areas =(Meanbackground - Meanmass)/(SDbackground )

11 SNR/CNR 11 SNR > 40 CNR >2 CNR variation less than 15% 0.4cm 2 ROI in large mass and just outside (manufacturer) For DC offset (check manufactures Manual or physicist report) Use the same kvp RAW!!! (vs. windowed) Record the mean/sd

12 Recording results 12 Date Initials kvp mas Mean Bkgd. SD Bkgd. Mean Mass SD Mass SNR (>40) CNR (>2) CNR variation QC 05-Jan slc %SS 12-Jan KJT %SS 19-Jan DDH %SS 26-Jan SLM %SS 02-Feb slc %SS 09-Feb slm %SS 16-Feb slm %SS 23-Feb slm %SS 01-Mar DDH %SS 08-Mar slm %SS 15-Mar KJT %SS 23-Mar slc %SS

13 CNR: Size matters 13 ROI size Backgrou nd SD Mass SD SNR CNR 0.1cm cm cm cm Make sure the same size ROI is used each time.

14 The phantom 14 Positioning is important ( I have seen it all sorts of directions) Consistent kvp Anode/filter combination that is used clinically Raw Vs. Processed (raw for CNR/SNR, but you may find it easier to do processed)

15 Phantom Analysis: Did you know? 15 You can get 0.5 points if you see more than half of the next object You lose 0.5 point for an artifact resembling one of the objects You must have a score of 4 fibres 3 specks 3 masses

16 Fibres 16 What is the score for fibres? = 4 Must minus 0.5 for the fibre-like artifact

17 Specks 17 What is my score? 3.5 Magnify the specks for better viewing Start with the largest speck group 1 pt for 4+ specks 0.5 pt for 2-3 specks From largest to smallest stop counting when you reach a score of 0 or 0.5 Then subtract 0.5 for any artifact

18 Mass 18 Mass gets 1 point for correct location and appears generally circular (3/4 of perimeter is visualized) Mass gets 0.5 point if it appears in correct location but does not look circular Stop counting points when you get a score of 0 or 0.5 Subtract any artifact deductions Score??? 3.5

19 What does Mammography QA look 19 like to you? Reflection of what your role is Bits completed by different people MAP MQSA Radiologist Outcomes Physicists QC Technologists QC

20 Ask yourself? 20 Are we evaluating and monitoring every aspect of mammography? Are we all doing a good job? How do we know? How do we get better? (if we need to)

21 MAP 21 Positioning deficiencies Poor visualization of posterior tissues Sagging breast Inadequate amount of pectoral muscle shown on image (not within 1 cm of nipple level) Inadequate inframammary fold (IMF) Non-standard angulation Pectoral muscle concave/thin Breast positioned too high on image receptor Posterior nipple line (PNL) on CC not within 1 cm of MLO PNL Excessive exaggeration on CC Portion of breast cut off Skin folds Other body parts projected over breast There are 12 positioning DEFICIENCIES

22 Clinical Images: MAP Evaluation 22 Compression Exposure Level Contrast Sharpness Noise Artifact Exam ID They do a great job evaluating the images we send.

23 2014: MAP Success % 95% 90% 85% 80% 75% 86% Canada Accreditation Success Rate 92% NS Does this program tell us how technologists perform everyday? Does having accreditation mean we do a great job everyday?

24 Clinical Image Quality in Daily Practice of Breast Cancer Mammography Screening 24 (Guertin MH et al, 2014) August 2014 the CARJ published a study where two radiologists independently evaluated the clinical image quality of a random subsample of 197 screening mammograms performed in , based on the criteria by CAR (MAP) found that that positioning is not meeting the standards set by the CAR guidelines

25 Study found 25 Approximately half of the studies failed CAR quality standards (49.7%) Positioning is the largest contributor to a fail 90% of MAP fails were positioning Discovered an association between BMI and quality Little information regarding daily quality, but recommend performance targets Variations between the 2 evaluators

26 What Can We Learn 26 The MAP evaluates what is considered the best of your images. The standard for this evaluation should be high. 2 sets of images from 1 or 2 technologists The MAP does not expect that every daily Mammography case will be an accreditation case Despite positioning being extremely important we have yet to change how we evaluate it Touchy subject for technologists Must emphasize continuous quality improvement Must focus on the positive of meeting standards or performance indicators and not failing them

27 Quality Initiative 27 The purpose: to demonstrate our commitment to providing quality imaging at all times. By auditing our work we will be able to quantify how well we do and identify any areas that require improvement. Primary Focus: positioning and image quality equipment issues and patient dose 2 parts random audit technologist submission KEEP IT POSITIVE!!!!

28 Random Audit 28 8 cases for each technologist (13) Used the positioning deficiencies criteria from MAP Reversed the criteria to the positive Measure successes Yes/no if each image met specific criteria Looking to find how each technologist performs in each criteria over all the images in the audit to identify strengths or weaknesses Collected DICOM header file data: dose, compression thickness and force, MLO angulations, kvp, mas

29 Data 29 Critique Element Pt ID: RCC LCC RMLO LMLO adequate amount of pectoral muscle shown on image ( within 1 cm of nipple level) yes yes Pectoral muscle convex (not concave/thin) no yes adequate Inframammory fold (IMF) yes yes Breast up and out (not sagging) yes yes MLO angle Posterior nipple line (PNL) on CC within 1cm of PNL on MLO yes No No Excessive exaggeration yes yes visualization of posterior tissues yes yes yes yes none or only 1 minor skin folds yes yes yes yes Breast free of other body parts yes yes yes yes free of motion yes yes yes yes free of grid lines yes yes yes yes free of artefacts yes yes yes yes Sharp and no noise yes yes yes yes Comments

30 DICOM 30 Technical Element RCC LCC RMLO LMLO Unit BSC MG5 Compression thickness Compression force kvp Anode filter W/Rh W/Rh W/Rh W/Rh mas Organ dose

31 CC Results 31 Tech PNL within 1cm of MLO No excessive exaggeration 1 88% 100% 2 69% 100% 3 81% 94% 4 88% 100% 5 88% 100% 6 94% 100% 7 69% 100% 8 50% 100% 9 88% 100% 10 69% 100% 11 88% 100% 12 94% 100% 13 88% 100% Average: 81% 100%

32 MLOs 32 Technologist Adequate pec shown Pec convex or straight Adequate IMF Breast up (not sagging) 1 100% 75% 69% 94% 2 88% 100% 88% 88% 3 94% 81% 81% 100% 4 100% 100% 94% 100% 5 100% 81% 81% 100% 6 94% 94% 89% 100% 7 94% 94% 88% 94% 8 88% 94% 94% 100% 9 100% 81% 81% 100% % 75% 100% 100% 11 88% 75% 94% 100% 12 88% 88% 81% 94% 13 88% 75% 63% 88% Average 94% 86% 85% 97%

33 Angles 33 tech min max

34 Compression Tech 1 Tech 2 Average Compression Force Tech 3 Tech 4 Tech 5 Tech 6 Tech 7 Tech 8 Tech 9 Tech 10 Tech 11 Tech 12 Tech 13

35 Technologists Submission 35 The technologists are asked that they submit cases 1-2 times a year that they feel would meet MAP standards. It is important for the technologists to realize that they can achieve these high quality images. Every technologist has this ability You can not meet the standards if you do not know what they are

36 Is it worth the work?? 36 FDA/MQSA EQUIP: Enhancing Quality Using the Inspection Program 1. Does the facility have procedures for corrective action when clinical images are of poor quality? 2. Does the facility have procedures to ensure that clinical images continue to comply with the clinical image quality standards established by the facility s accreditation body? Image attributes for each technologist and images accepted by each interpreting physician. Documentation and feedback mechanism

37 Future 37 Structured problem solving using statistical means to verify performance produce better long term solutions.j Papp The Digital DI department Image Quality Scores/Performance Indicators High level analytics: Combining dicom information with quality indicators Looking for root causes MAP critique scores/ MLO angle Dose/density/unit kvp/unit/patient density Compression/tech

38 Thank you 38 Special Thanks to: Dr. Sian Iles Dr. Judy Caines Elise LeBlanc Elena Tonkopi Dr. Mohamed Abdolell Dr. Jennifer Payne

39 References 39 ACR AAPM SIIM PRACTICE PARAMETER FOR DETERMINANTS OF IMAGE QUALITY IN DIGITAL MAMMOGRAPHY 2014 NS Breast Screening CAR MAP Digital Accreditation Application Clinical Image Quality in Daily Practice of Breast Cancer Mammography Screening (Guertin, Theberge, Dufresne, Zomahoun, Major, Tremblay, Ricard, Shumak, Wadden, Pelletier, Brisson HC safety Code 36: Mammography Equipment Katherine Steigerwald MAP Coordinator Quality Management in the Imaging Sciences, J Papp FDA website OBSP Digital Mammography QC for the Technologist