Can the overlooked lung cancer be detectedby the BS / TS algorithm ?

Hiroshi Moriya MD. PhD.1, Motoharu. Hakozaki MD2, Yukiko Kumasaka MD. PhD.1,
1 Image Diagnosis Center, Ohara General Hospital, Fukushima, Japan

2 Department of Radiology, Fukushima Medical University, Fukushima, JapanPurposeIn the Mayo Lung Project, a retrospective study reported that
90% of lung cancer cases were visible in past chest
roentgenogram for months or even years. Thus, the purpose ofthis study is to evaluate the added value of bone-suppression
algorithm (BS) and temporal-subtraction algorithm (TS) on thedetection and diagnostic confidence of early lung cancers in
the roentgenogram which the specialist overlooked. (Fig.1)

Materials and methods
ClearRead Xray (Bone Suppress and Compare: Riverain Technologies) were used.

Pathologically confirmed 36 lung cancers. All cases examined chest roentgenogram annually. The
roentgenogram that could not point out the lesions at that time (1 and 2 years before) wereanalyzed by BS and TS. Four data sets (Chest roentgenogram only, CR+BS, CR+TS, CR+BS+TS)
were prepared for this evaluation.

Two radiologists visually graded the diagnostic confidence on a 5-point scale from 1 (definitelyabsent) to 5 (definitely present). The value of these algorithm were assessed in a receiveroperating characteristic curve analysis.
Radiologist A: Resident with few opportunities to diagnose chest roentgenogram.
Radiologist B: Chest radiologist with many opportunities to diagnose chest roentgenogram.

Results
Radiologist A: The number of true positive was 1 in the Data set A, 6 in the Data set B, 14 in theData set C and 12 in the Data set D. AUC (area under the curve) of ROC was 0.52 for Data set A,0.64 for Data set B, 0.81 for Data set C and 0.77 for Data set D.
Radiologist B: The number of true positive was 16 in Data set A, 16 in Data set B, 20 in Data set C
and 20 in Data set D. AUC of ROC was 0.86 for Data set A, 0.86 for Data set B, 0.95 for Data set C
and 0.95 for Data set D. (Fig.2)
By using bone-suppression algorithm and temporal-subtraction algorithm, it became possible todetect lung cancer in an earlier stage. This is particularly effective for those who have little
experience in image interpretation.

Case presentation of 20 cases that had findings (Fig.3 - Fig.22)
Original chest roentgenogram image, bone-suppression algorithm image (BS) , temporalsubtraction algorithm image (TS) and CT image when lung cancer is detected (approximately one
year after the chest roentgenogram) are presented.

ROC

Chest roentgenogram
onlyRadiologist A (Resident with few opportunities
to diagnose chest roentgenogram)

AUC (area under the curve) of ROC
0.52 for Chest roentgenogram only
0.64 for CR+BS
0.81 for CR+TS
0.77 for CR+BS+TSCR+BS

CR+TS

CR+BS+TS

Radiologist B(Chest radiologist with many
opportunities to diagnose chest roentgenogram

AUC (area under the curve) of ROC
0.86 for Chest roentgenogram only
0.86 for CR+BS
0.95 for CR+TS
0.95 for CR+BS+TS

３１TS

OriginalBS
CT one year after CR１３TS

OriginalBS
CT one year after CR

２TS
BS

Original
CT one year after CR

１０TSBS

Original
CT one year after CR

８TSBS

Original
CT one year after CR

３TS

OriginalBS
CT one year after CR

１TSBS
Original
CT one year after CR

２４
CT one year after CROriginalBSTS

CT one year after CR

２３Original

BSTS

１２Original

CT one year after CRBSTS

１４TSOriginalBS
CT one year after CR

２６TSBS
Original

CT one year after CR

９TSBSOriginal

CT one year after CR

３６TSBS
Original

CT one year after CR

３２TSBS
Original
CT one year after CR4OriginalBS

CT one year after CR

２１TSOriginalBS

CT one year after CR１６TS

OriginalBS

CT one year after CR

２７TSOriginalBS

CT one year after CR

１５TSBS
Original

CT one year after CR３３Original

BSTSConclusion
By using bone-suppression algorithm and temporal-subtraction
algorithm, it became possible to detect lung cancer in an earlierstage.

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